MELP-to-LPC transcoder (23-Feb-2010)

This application is a continuation application of U.S. patent application Ser. No. 11/051,664, filed Feb. 4, 2005, which is a continuation application of U.S. patent application Ser. No. 09/822,503, filed Apr. 2, 2001 (abandoned).

FIELD OF THE INVENTION

The present invention relates to speech coders and speech coding methods. More specifically, the present invention relates to a system and method for transcoding a bit stream encoded by a first speech coding format into a bit stream encoded by a second speech coding format.

BACKGROUND OF THE INVENTION

The term speech coding refers to the process of compressing and decompressing human speech. Likewise, a speech coder is an apparatus for compressing (also referred to herein as coding) and decompressing (also referred to herein as decoding) human speech. Storage and transmission of human speech by digital techniques has become widespread. Generally, digital storage and transmission of speech signals is accomplished by generating a digital representation of the speech signal and then storing the representation in memory, or transmitting the representation to a receiving device for synthesis of the original speech.

Digital compression techniques are commonly employed to yield compact digital representations of the original signals. Information represented in compressed digital form is more efficiently transmitted and stored and is easier to process. Consequently, modern communication technologies such as mobile satellite telephony, digital cellular telephony, land-mobile telephony, Internet telephony, speech mailboxes, and landline telephony make extensive use of digital speech compression techniques to transmit speech information under circumstances of limited bandwidth.

A variety of speech coding techniques exist for compressing and decompressing speech signals for efficient digital storage and transmission. It is the aim of each of these techniques to provide maximum economy in storage and transmission while preserving as much of the perceptual quality of the speech as is desirable for a given application.

Compression is typically accomplished by extracting parameters of successive sample sets, also referred to herein as “frames”, of the original speech waveform and representing the extracted parameters as a digital signal. The digital signal may then be transmitted, stored or otherwise provided to a device capable of utilizing it. Decompression is typically accomplished by decoding the transmitted or stored digital signal. In decoding the signal, the encoded versions of extracted parameters for each frame are utilized to reconstruct an approximation of the original speech waveform that preserves as much of the perceptual quality of the original speech as possible.

Coders which perform compression and decompression functions by extracting parameters of the original speech are generally referred to as parametric coders or vocoders. Instead of transmitting efficiently encoded samples of the original speech waveform itself, parametric coders map speech signals onto a mathematical model of the human vocal tract. The excitation of the vocal tract may be modeled as either a periodic pulse train (for voiced speech), or a white random number sequence (for unvoiced speech). The term “voiced” speech refers to speech sounds generally produced by vibration or oscillation of the human vocal cords. The term “unvoiced” speech refers to speech sounds generated by forming a constriction at some point in the vocal tract, typically near the end of the vocal tract at the mouth, and forcing air through the constriction at a sufficient velocity to produce turbulence. Speech coders which employ parametric algorithms to map and model

There are several types of vocoders on the market and in common usage, each having its own set of algorithms associated with the vocoder standard. Three of these vocoder standards are:

• • 1. LPC-10 (Linear Prediction Coding): a Federal Standard, having a transmission rate of 2400 bits/sec. LPC-10 is described, e.g., in T. Tremain, “The Government Standard Linear Prediction Coding Algorithm: LPC-10,” Speech Technology Magazine, pp. 40-49, April 1982).
  • 2. MELP (Mixed Excitation Linear Prediction): another Federal Standard, also having a transmission rate of 2400 bits/sec. A description of MELP can be found in A. McCree, K. Truong, E. George, T. Barnwell, and V. Viswanathan, “A 2.4 kb/sec MELP Coder Candidate for the new U.S. Federal Standard,” Proc. IEEE Conference on Acoustics, Speech and Signal Processing, pp. 200-203, 1996.
  • 3. TDVC (Time Domain Voicing Cutoff): A high quality, ultra low rate speech coding algorithm developed by General Electric and Lockheed Martin having a transmission rate of 1750 bits/sec. TDVC is described in the following U.S. Pat. Nos. 6,138,092; 6,119,082; 6,098,036; 6,094,629; 6,081,777; 6,081,776; 6,078,880; 6,073,093; 6,067,511. TDVC is also described in R. Zinser, M. Grabb, S. Koch and G. Brooksby, “Time Domain Voicing Cutoff (TDVC): A High Quality, Low Complexity 1.3-2.0 kb/sec Vocoder,” Proc. IEEE Workshop on Speech Coding for Telecommunications, pp. 25-26, 1997.

When different units of a communication system use different vocoder algorithms, transcoders are needed (both ways, A-to-B and B-to-A) to communicate between and amongst the units. For example, a communication unit employing LPC-10 speech coding can not communicate with a communication unit employing TDVC speech coding unless there is an LPC-to-TDVC transcoder to translate between the two speech coding standards. Many commercial and military communication systems in use today must support multiple coding standards. In many cases, the vocoders are incompatible with each other.

Two conventional solutions that have been implemented to interconnect communication units employing different speech coding algorithms consist of the following:

• • 1) Make all new terminals support all existing algorithms. This “lowest common denominator” approach means that newer terminals cannot take advantage of improved voice quality offered by the advanced features of the newer speech coding algorithms such as TDVC and MELP when communicating with older equipment which uses an older speech coding algorithm such as LPC.
  • 2) Completely decode the incoming bits to analog or digital speech samples from the first speech coding standard, and then reencode the analog speech samples using the second speech coding standard. This process is known a tandem connection. The problem with a tandem connection is that it requires significant computing resources and usually results in a significant loss of both subjective and objective speech quality. A tandem connection is illustrated in FIG. 1. Vocoder decoder 102 and D/A 104 decodes an incoming bit stream representing parametric data of a first speech coding algorithm into an analog speech sample. A/D 106 and vocoder encoder 108 reencodes the analog speech sample into parametric data encoded by a second speech coding algorithm.

What is needed is a system and method for transcoding compressed speech from a first coding standard to a second coding standard which 1) retains a high degree of speech quality in the transcoding process, 2) takes advantage of the improved voice quality features provided by newer coding standards, and 3) minimizes the use of computing resources. The minimization of computing resources is especially important for space-based transcoders (such as for use in satellite applications) in order to keep power consumption as low as possible.

SUMMARY OF THE INVENTION

The system and method of the present invention comprises a compressed domain universal transcoder architecture that greatly improves the transcoding process. The compressed domain transcoder directly converts the speech coder parametric information in the compressed domain without converting the parametric information to a speech waveform representation during the conversion. The parametric model parameters are decoded, transformed, and then re-encoded in the new format. The process requires significantly less computing resources than a tandem connection. In some cases, the CPU time and memory savings can exceed an order of magnitude.

The method more generally comprises transcoding a bit stream representing frames of data encoded according to a first compression standard to a bit stream representing frames of data according to a second compression standard. The bit stream is decoded into a first set of parameters compatible with a first compression standard. Next, the first set of parameters are transformed into a second set of parameters compatible with a second compression standard without converting the first set of parameters to an analog or digital waveform representation. Lastly, the second set of parameters are encoded into a bit stream compatible with the second compression standard.

BRIEF DESCRIPTION OF THE DRAWINGS

FIG. 1 depicts a block diagram illustrating a conventional tandem connection.

FIG. 2 depicts a block diagram illustrating the general architecture of the compressed domain universal transcoder of the present invention.

FIG. 3 depicts a block diagram illustrating an LPC-to-MELP transcoding process.

FIG. 4 depicts a block diagram illustrating a MELP-to-LPC transcoding process.

FIG. 5 depicts a block diagram illustrating a LPC-to-TDVC transcoding process.

FIG. 6 depicts a block diagram illustrating a MELP-to-TDVC transcoding process.

FIG. 7 depicts a block diagram illustrating a TDVC-to-LPC transcoding process.

FIG. 8 depicts a block diagram illustrating a TDVC-to-MELP transcoding process.

FIG. 9 depicts a block diagram illustrating a Compressed Domain Conference Bridge.

FIG. 10 depicts a dual synthesizer state diagram.

FIG. 11 depicts a Compressed Domain Voice Activation Detector (CDVAD).

FIG. 12A depicts a block diagram illustrating a multi-frame encoding and decoding process.

FIG. 12B depicts 5-bit and 4-bit quantizer tables used for multi-frame gain encoding and decoding.

DETAILED DESCRIPTION OF THE INVENTION

1. Compressed Domain Universal Transcoder

The transcoding technology of the present invention greatly improves the transcoding process. The transcoder directly converts the speech coder parametric information in the compressed domain without converting the parametric information to an analog speech signal during the conversion. The parametric model parameters are decoded, transformed, and then re-encoded in the new format. The process requires significantly less computing resources than the tandem connection illustrated in FIG. 1. In some cases, the CPU time and memory savings can exceed an order of magnitude.

In general terms, the transcoder of the present invention performs the following steps: 1) decode the incoming bit stream into the vocoder parameters, 2) transform the vocoder parameters into a new set of parameters for the target output vocoder, and 3) encode the transformed parameters into a bit stream compatible with the target output coder.

FIG. 2 is a block diagram illustrating the general transcoding process 200 of the present invention. The process 200 shown in FIG. 2 is the general conversion process that is used to convert an incoming bit stream encoded with a first coding standard to an output bit stream encoded with a second coding standard. For example, an incoming bit stream encoded with the LPC coding standard could be converted to the MELP coding standard, or an incoming bit stream encoded in MELP coding standard could be converted to the TDVC coding standard. The process shown in FIG. 2 illustrates the general process of the present invention that applies to all of the possible conversions (e.g. LPC to MELP, LPC to TDVC, MELP to LPC, etc). Each of the six individual transcoder conversions between LPC, MELP, and TDVC will later be described individually in more detail below with respect to sections 2-7 below and FIGS. 3-8.

As shown in FIG. 2, an incoming bit stream is received by demultiplexing and FEC (forward error correction decoding) step 201. The incoming bit stream represents frames containing parameters of a first coding standard such as LPC-10, MELP, or TDVC. This first coding standard will also be referred to as the “input coding standard.” In step 201, forward error correction decoding is performed on the incoming data frames, and the copies of each frame are distributed to steps 202, 204, 206, and 208, respectively. FEC adds redundant bits to a block of information to protect from errors.

There are four basic types of parameters used in low rate vocoders: 1) gross spectrum, 2) pitch, 3) RMS power (or gain), and 4) voicing. Within these four categories of parameter types, each coding standard employs different numbers and kinds of parameters. For example, LPC-10 employs one voicing parameter comprised of only a single voicing bit per half-frame of data, whereas MELP employs a total of seven voicing parameters per frame (five voicing parameters representing bandpass voicing strengths, one overall voiced/unvoiced flag, and one voicing parameter called the “jitter flag”) in an effort to enhance speech quality.

In steps 202, the spectral parameters of the first coding standard are decoded from the incoming data frames. In step 204, the voicing parameters of the first coding standard are decoded from the incoming data frames. In step 206, the pitch parameters of the first coding standard are decoded from the incoming data frames. In step 208, the gain parameters of the first coding standard are decoded from the incoming data frames.

In step 210, 212, 214, and 216, the decoded parameters of the input coding standard are converted to spectrum, voicing, pitch and gain parameters, respectively, of the output coding standard. Each type of conversion is described in detail in the sections below for each specific type of transcoder conversion. Note that the conversion from input coding standard parameters to output coding standard parameters is not always a simple one to one conversion of parameters. For example, the output voicing parameters could be a function of both the input voicing parameters and the input spectrum parameters (this is true, for example, for the MELP to LPC transcoding conversion, described below). Other operations are also used in the conversion process to improve the output sound quality such as interpolation operations, smoothing operations, and formant enhancement described further in sections 2-7 below.

The parameters produced by the conversion steps 210, 212, 214, and 216 will be either floating point numbers or fixed point numbers, depending on the particular output coding standard. For example, the MELP and TDVC standards use floating point numbers, whereas the LPC-10 standard uses fixed point numbers.

Encoding steps 218, 220, 222, and 224 encode and quantize the output spectrum, voicing, pitch and gain parameters, respectively, using the standard quantization/encoding algorithms of the output coding standard. Lastly, in step 226, the output parameters are combined into frames, forward error correction encoding is performed, and the output bit stream representing frames of the output coding standard are transmitted.

Each of the following individual transcoding processes will now be described in detail.

• • 1. LPC to MELP Transcoder
  • 2. LPC to TDVC Transcoder
  • 3. MELP to LPC Transcoder
  • 4. MELP to TDVC Transcoder
  • 5. TDVC to LPC Transcoder
  • 6. TDVC to MELP Transcoder

The general transcoding method illustrated in FIG. 2 and the conversion techniques described below can also be applied to create trancoders for conversion between other coding standards besides LPC, MELP, and TDVC that are currently in usage or being developed.

2. LPC-to-MELP Transcoder

FIG. 3 illustrates a transcoding method 300 for converting a bit stream representing frames encoded with the LPC-10 coding standard to a bit stream representing frames encoded with the MELP coding standard. In step 302, an incoming bit stream is received. The incoming bit stream represents LPC-10 frames containing LPC-10 parameters. Forward error correction (FEC) decoding is performed on the incoming bit stream. The incoming bit stream is also decoded by extracting LPC-10 spectrum, pitch, voicing, and gain parameters from the incoming bit stream. The parameters are then distributed to spectrum conversion step 304, voicing conversion step 312, pitch conversion step 316 and gain conversion step 322. Each of these conversion processes will now be described in detail.

a. Spectrum Conversion

The LPC-10 spectrum parameters are referred to as “reflection coefficients” (RCs) whereas the MELP spectrum parameters are referred to as “line spectrum frequencies” (LSFs). The conversion of RCs to LSFs is performed in steps 304, 306, 3108, and 310, and will now be described in detail.

In step 304, the LPC-10 reflection coefficients (RC) are first converted to their equivalent normalized autocorrelation coefficients (R). The LPC-10 reflection coefficients (RC) are also converted to their equivalent predictor filter coefficients (A); the predictor filter coefficients (A) are saved for later use in formant enhancement step 308. Both of these conversions (RC→R, RC→A) are performed by using well known transformations. In order to avoid truncation effects in subsequent steps, the autocorrelation conversion (RC→R) recursion is carried out to 50 lags (setting RCs above order 10 to zero). The resulting values for the autocorrelation coefficients (R) are stored symmetrically in a first array.

In step 306, the “preemphasis” is removed from the LPC-10 autocorrelation (R) coefficients. To explain why this is performed, first an explanation of preemphasis is provided as follows. When encoding speech according to the LPC speech coding algorithm standard, an operation known as “preemphasis” is performed on the sampled speech signal prior to spectral analysis. Preemphasis is performed by applying a first order FIR filter prior to spectral analysis. This preemphasis operation attenuates the bass frequencies and boosts the treble frequencies. The purpose of preemphasis is to aid in the computations associated with a fixed point processor; preemphasis makes it less likely for the fixed point processor to get an instability from an underflow or an overflow condition.

Newer speech coding algorithms such as MELP and TDVC do not perform preemphasis because they were designed for modern signal processing hardware that has wider data paths. Therefore, a MELP synthesizer expects spectral coefficients that were produced directly from the sampled speech signal without preemphasis.

Because LPC uses preemphasis, while MELP does not, in step 306 the preemphasis effects are removed from the LPC-10 spectral coefficients. Preemphasis removal is performed as follows. The symmetrical autocorrelation coefficients (HH) of a deemphasis filter are calculated beforehand and stored in a second array matching the format of the first array of autocorrelation coefficients (R) created in step 304. The deemphasis filter is a single pole IIR filter and is generally the inverse of the preemphasis filter used by LPC-10, but different preemphasis and deemphasis coefficients may be used. The LPC-10 standard uses 0.9375 for preemphasis and 0.75 for deemphasis. Because the deemphasis filter has IIR characteristics, the autocorrelation function is carried out to 40 time lags. The autocorrelation values are obtained by convolving the impulse response of the filter.

A modified set of spectral autocorrelation coefficients is calculated via convolving the R values with the HH values as follows:

R ′ ⁡ ( k ) = ∑ l ⁢ R ⁡ ( i + k ) * HH ⁡ ( i )

The resulting modified autocorrelation coefficients R′ will be referred to herein as “deemphasized” autocorrelation coefficients, meaning that the LPC-10 preemphasis effects have been removed. Note that by removing the preemphasis in the correlation domain (i.e. removing the preemphasis from autocorrelation coefficients rather than the reflection coefficients or filter coefficients), computational complexity can be reduced.

The deemphasized autocorrelation coefficients R′ are then converted to deemphasized reflection coefficients (RC′) and deemphasized predictor filter coefficients (A′), using well known conversion formulas. The stability of the synthesis filter formed by the coefficients is checked; if the filter is unstable, the minimum order stable model is used (e.g. all RC′ coefficients up to the unstable coefficient are used for the conversion to A′ coefficients). The RC and RC′ values are saved for use by the “Compute LPC Gain Ratio” step 320, described further below.

In step 308, formant enhancement is performed. The perceptual quality produced by low rate speech coding algorithms can be enhanced by attenuating the output speech signal in areas of low spectral amplitude. This operation is known as formant enhancement. Formant enhancement sharpens up the spectral peaks and depresses the valleys to produce a crisper sound that is more intelligible. Format enhancement is conventionally performed during the process of decoding the bit stream into an analog speech signal. However, according to the present invention, it has been found that formant enhancement can be used to in the transcoding process 300 to produce a better sounding speech output.

Two methods of formant enhancement are described in detail in sections 12 and 13 below. Section 12 describes a method of formant enhancement performed in the correlation domain. Section 13 describes a second method of formant enhancement performed in the frequency domain. Both formant enhancement methods utilize both the non-deemphasized filter coefficients (A) and the deemphasized filter coefficients (A′). Both methods of formant enhancement produce good results. Which one is preferable is a subjective determination made by the listener for the particular application.

Formant enhancement step 310 outputs “enhanced” deemphasized LPC-10 filter coefficients (A″), wherein the term “enhanced” means that formant enhancement has been performed. The transcoding process of the present invention illustrated in FIG. 3 could potentially be performed without formant enhancement step 308. However, formant enhancement has been found to substantially improve the speech quality and understandability of the MELP output.

In step 310, the enhanced deemphasized LPC-10 filter coefficients (A″) are converted to MELP line spectrum frequencies (LSFs). This conversion is made by using well known transformations. In step 310, the MELP LSFs are then adaptively smoothed. With modern vocoders like MELP and TDVC, because of the way the quantization error is handled, the voice often obtains an undesirable vibrato-like sound if smoothing is not performed. Thus, in step 310, a smoothing function is applied to reduce this undesirable vibrato effect. The smoothing function is designed to reduce small fluctuations in the spectrum when there are no large frame-to-frame spectrum changes. Large fluctuations are allowed to pass with minimum smoothing. The following C-code segment is an example of such a smoother. Note that this segment is only an example, and any algorithm having a smoothing effect similar to that described above could be used.

	for (i=0; i<10; i++) {
	delta = 10.0*(lsp[i] − oldlsp[i]);
	if (delta < 0.0) delta = −delta;
	if (delta > 0.5) delta = 0.5;
	lsp[i] = lsp[i]*(0.5+delta) + oldlsp[i]*(0.5−delta);
	}

where lsp[i] are the current frame's LSF coefficients, oldlsp[i] are the previous frame's LSF coefficients, and delta is a floating point temporary variable.

MELP also has the provision for encoding the first 10 harmonic amplitudes for voiced speech. These harmonic amplitudes can either be set to zero or generated as follows. U.S. Pat. No. 6,098,036 to Zinser et al., “Speech Coding System and Method Including Spectral Formant Enhancer,” discloses a spectral formant enhancement algorithm to generate these harmonic amplitudes. In particular, the process described in columns 17 and 18 can be used to generate 10 amplitudes (amp(k), k=1 . . . 10) from Equation 7 in column 18. Further enhancement may be achieved by utilizing the method described in Grabb, et al., U.S. Pat. No. 6,081,777, “Enhancement of Speech Signals Transmitted Over a Vocoder Channel”, and modifying the first three harmonic amplitudes amp(k) according to the values given in FIG. 5 and the accompanying equation.

It was found that generating harmonic amplitudes in this manner produced a superior output quality sound for the TDVC to MELP transcoder (described in section 7, below). However, the improvement for the LPC-10 to MELP transcoder was not as significant. Therefore, for the LPC-10 to MELP transcoder, it may be desirable to simply set the MELP harmonic amplitudes to zero, to reduce computational complexity.

After multiplication by a factor of 2 (to match scaling conventions), the smoothed LSFs are encoded according to the MELP quantization standard algorithm.

b. Voicing Conversion and Jitter Factor Conversion

In step 312, the LPC-10 voicing parameters are converted into MELP voicing parameters. This is not a simple one-to-one conversion because LPC-10 uses only a single voicing parameter, whereas MELP uses several voicing parameters. Thus, a method has been devised according to the present invention for assigning MELP parameters based on the LPC-10 parameters which produces superior sound quality.

The LPC-10 coding standard uses only a single voicing bit per half-frame representing either voiced or unvoiced; i.e., each half-frame is either voiced or unvoiced. In order to provide improved sound quality, the newer MELP coding standard uses seven different voicing parameters: five bandpass voicing strengths, one overall voiced/unvoiced flag, and one voicing parameter called the “jitter flag” which is used to break up the periodicity in the voiced excitation to make the speech sound less buzzy during critical transition periods.

The conversion process of the present invention uses the expanded voicing features of the MELP synthesizer to advantage during transitional periods such as voicing onset, described as follows. The LPC voicing bits are converted to MELP voicing parameters according to three different situations:

• • (1) mid-frame onset (the first LPC half-frame is unvoiced and the second half-frame is voiced).
  • (2) fully voiced (both half-frames are voiced).
  • (3) fully un-voiced mid-frame unvoiced transition (either both half-frames are unvoiced or the first frame is voiced and the second half-frame is unvoiced).

The method is illustrated by the piece of C code below. Testing has found that this method provides the superior sound performance. This method tends to provide a smoother transition from voiced to unvoiced transitions. The following C-code segment illustrates the method of converting LPC-10 voicing bits to the MELP voicing parameters:

	/* mid-frame onset */
	if ((lpc->voice[0]==0) && (lpc->voice[1]==1)) {
	melp->uv_flag = 0;
	melp->jitter = 0.25;
	for (i=0; i<NUM_BANDS-2; i++)
	melp->bpvc[i] = 1.0;
	melp->bpvc[NUM_BANDS-2] = 0.0;
	melp->bpvc[NUM_BANDS-1] = 0.0;
	}
	/* fully voiced */
	else if((lpc->voice[0]==1) && (lpc->voice[1]==1)) {
	melp->uv_flag = 0;
	melp->jitter = 0.0;
	for (i=0; i<NUM_BANDS; i++)
	melp->bpvc[i] = 1.0;
	}
	/* fully unvoiced and mid-frame unvoiced transition */
	else {
	melp->uv_flag = 1;
	melp->jitter = 0.25;
	for (i=0; i<NUM_BANDS; i++)
	melp->bpvc[i] = 0.0;
	}

where lpc→voice[0] and lpc→voice[1] are the half-frame LPC voicing bits (0=unvoiced), melp→uv_flag is the MELP overall unvoiced flag (0=unvoiced), melp→jitter is the MELP jitter flag, and melp→bpvc[i] are the MELP bandpass voicing strengths. Note that for the transition from unvoiced to voiced, the top two MELP voicing bands are forced to be unvoiced. This reduces perceptual buzziness in the output speech.

In step 314, the MELP voicing and jitter parameters are encoded according to the MELP quantization standard algorithm.

c. Pitch Conversion

In step 316, the LPC-10 pitch parameters are converted to MELP pitch parameters. The LPC-10 coding standard encodes pitch by a linear method whereas MELP encodes pitch logarithmically. Therefore, in step 316, the logarithm is taken of the LPC-10 pitch parameters to convert to the MELP pitch parameters. In step 318, the MELP pitch parameters are encoded using the MELP quantization standard algorithm.

d. Gain (RMS) Conversion

The conversion from LPC-10 RMS gain parameters to MELP gain parameters begins in step 322. In step 322, the LPC-10 RMS gain parameters are scaled to account for the preemphasis removal performed on the LPC-10 spectral coefficients in step 306. To explain, as mentioned previously, LPC-10 coding adds preemphasis to the sampled speech signal prior to spectral analysis. The preemphasis operation, in addition to attenuating the bass and increasing the treble frequencies, also reduces the power level of the input signal. The power level is reduced in a variable fashion depending on the spectrum. Therefore, the effect of removing the preemphasis in step 306 must be accounted for accordingly when converting the gains from LPC to MELP. The preemphasis removal is accounted for by scaling the gains in step 322.

In step 320, an “LPC gain ratio” is calculated for each new frame of parametric data. The LPC gain ratio is the ratio of the LPC predictor gains derived from the spectrum before and after preemphasis removal (deemphasis addition) in step 306. If,

lpcgain ⁢ ⁢ 1 = 1 ∏ i ⁢ ( 1 - rc 2 ⁡ ( i ) )
is defined as the synthesis filter gain before preemphasis removal and:

lpcgain ⁢ ⁢ 2 = 1 ∏ i ⁢ ( 1 - rc ′2 ⁡ ( i ) )
is defined as the synthesis filter gain after preemphasis removal, then the scaling factor (i.e., the LPC Gain Ratio) to be used for the LPC-10 gain is

scale = 8 * lpcgain ⁢ ⁢ 2 lpcgain ⁢ ⁢ 1

The factor of 8 is included to accommodate the 13 bit input and output sample scaling in LPC-10 (MELP utilizes 16 bit input and output samples). In step 322, the LPC RMS gain parameter is scaled by the LPC Gain Ratio calculated in step 320.

Steps 324 addresses another difficulty in the gain conversion process which is that MELP uses two gain parameters per frame, whereas LPC uses only one gain parameter per frame. MELP employs a first gain parameter for the first half frame, and a second gain parameter for the second half frame. There thus needs to be a method for assigning the two half-frame MELP gains which produce a good quality sounding output.

A simple method of assigning MELP gains would be to simply set both of the MELP gains equal to the LPC RMS gain. However, it has been found that a better result is obtained if the two MELP gains are generated by taking a logarithmic average of the LPC RMS gains from frame to frame. This is performed in steps 324 and 326. As illustrated by the C-code segment below, the first MELP frame gain is assigned to be equal to the logarithmic average of the old LPC RMS gain from the last frame and the new LPC RMS gain from the current frame. The second MELP gain is set equal to the LPC RMS gain for the current frame. This method of assigning MELP gains provides a smooth transition.

The following C-code segment illustrates this method of calculating the gains:

	melp->gain[0] = pow(10.0, 0.5*log10(LPCrmsold) +
	0.5*log10(LPCrms));
	melp->gain[1] = LPCrms;

LPCrms and LPCrmsold represent the scaled LPC RMS gains computed in step 322. LPCrms is the current frame's gain, while LPCrmsold is the previous frame's scaled gain melp→gain[0] and melp→gain[1] are the MELP half frame gains, pow( ) is the C library power function, and log 10( ) is the C-library base-10 logarithm function.

In step 326, the logarithmic value of the two MELP gains are provided to encoding step 328. In step 328, the MELP half-frame gains are encoded using the standard MELP logarithmic quantization algorithm.

In step 330, the encoded MELP spectrum, voicing, pitch, and gain parameters are inserted into MELPs frame and forward error correction (FEC) coding is performed. An output bit stream representing the MELP frames is then transmitted to a desired recipient.

3. MELP to LPC Transcoder

FIG. 4 illustrates a transcoding method 400 for converting a bit stream representing frames encoded with the MELP coding standard to a bit stream representing frames encoded with the LPC-10 coding standard. In step 402, an incoming bit stream is received. The incoming bit stream represents MELP frames containing MELP parameters. In step 402, forward error correction (FEC) decoding is performed on the incoming bit stream. The MELP frames are also decoded by extracting the MELP spectrum, pitch, voicing, and gain parameters from the MELP frames. The MELP parameters are then distributed to steps 404, 412, 416 and 420 for conversion to LPC-10 spectrum, voicing, pitch and gain parameters, respectively. Each of these conversion processes will now be described in detail.

a. Spectrum Conversion

In step 404, the MELP LSFs are converted to their equivalent normalized autocorrelation coefficients R using well known transformations. In step 406, preemphasis is added to the autocorrelation coefficients R. As mentioned previously for the LPC to MELP transcoder (section 2, above), LPC-10 speech encoders add preemphasis to the originally sampled (nominal) speech signal before the LPC-10 spectral analysis and encoding is performed. Thus, transcoder 400 must modify the autocorrelation coefficients R to produce modified autocorrelation coefficients which are equivalent to autocorrelation coefficients that would have been produced had the original nominal speech signal been preemphasized prior to LPC-10 encoding.

The LPC-10 0.9375 preemphasis coefficient must be superimposed on the spectrum. This is performed in the correlation domain by performing the following operation on the autocorrelation (R) coefficients:
R′(i)=R(i)−0.9375[R(|i−1|)+R(i+1)]+0.9375²R(i)
where R′(i) are the preemphasized autocorrelation coefficients. Note that the input set of R(i)s must be computed out to 11 lags to avoid truncation. The preemphasized autocorrelation coefficients R′ are then transformed to preemphasized predictor filter coefficients A′ using well known transformations. As noted in section 2, above, performing the preemphasis addition in the correlation domain reduces computational complexity.

In step 408, formant enhancement is performed. The purpose of formant enhancement step 408 is the same as formant enhancement step 308 described above for the LPC-10 to MELP transcoder. Two methods of formant enhancement are described in detail in sections 12 and 13 below. Section 12 describes a method of formant enhancement performed in the correlation domain. Section 13 describes a second method of formant enhancement performed in the frequency domain. Both formant enhancement methods utilize both the non-deemphasized filter coefficients (A) and the deemphasized filter coefficients (A′). Both methods of formant enhancement produce good results. Which one is preferable is a subjective determination made by the listener for the particular application. For the MELP to LPC-10 transcoder, the majority of listeners polled showed a slight preference frequency domain method.

In step 410, the formant enhanced preemphasized filter coefficients A″ are converted to LPC-10 reflection coefficients RC″ using well known transformations. Also in step 410, the reflection coefficients RC″ are encoded according to the LPC-10 quantizer tables.

b. Voicing Conversion

In step 412, the MELP voicing parameters are converted to LPC voicing parameters. As mentioned previously, the LPC-10 coding standard uses only a single voicing bit per half-frame, whereas the MELP coding standard uses seven different voicing parameters: five bandpass voicing strengths, one overall voiced/unvoiced flag, and one voicing parameter called the “jitter flag.”

Simply using the MELP overall voicing bit to determine both half frame LPC voicing bits does not provide good performance. The voicing conversion process performed in step 412 achieves better perceptual performance by assigning values to the LPC voicing bits based on the MELP bandpass voicing strengths, the MELP overall voicing bit, and the first reflection coefficient RC′[0] (after preemphasis addition) received from preemphasis addition unit 406. A preferred decision algorithm is described by the following C-code segment:

	lpc->voice[0] = lpc->voice[1] = (melp->uv_flag+1)%2;
	flag = 0;
	for (i=0; i<NUM_BANDS; i++)
	flag += (int)melp-> bpvc[i];
	if ((flag <= 4) && (rc′[0] <0.0))
	lpc->voice[0] = lpc->voice[1] = 0;

where lpc→voice[ ] are the half-frame LPC voicing bits (1=voiced), flag is an integer temporary variable, melp→uv_flag is the MELP overall unvoiced flag (0=voiced), melp→bpvc[ ] are the bandpass voicing strengths (0.0 or 1.0, with 1.0=voiced), and rc′[0] is the first reflection coefficient (computed from the spectrum after preemphasis addition).

As illustrated by the above code, initially both LPC voicing bits are set to one (voiced) if the MELP overall unvoiced flag equals zero (voiced). Otherwise, the LPC voicing bits are set to one (unvoiced). To improve the output sound performance, both LPC voicing bits are set to zero (unvoiced) if the first reflection coefficient RC′[0] is negative, and the total number of MELP bands which are voiced is less than or equal to four. The reason this last improvement is performed is as follows. The MELP voicing analysis algorithm will occasionally set a partially voiced condition (lower bands voiced, upper bands unvoiced) when the input signal is actually unvoiced. Unvoiced signals typically have a spectrum that is increasing in magnitude with frequency. The first reflection coefficient RC′[0] provides an indication the spectral slope, and when it is negative, the spectral magnitudes are increasing with frequency. Thus, this value can be used to correct the error.

Note that this type of voicing error is generally not apparent when a MELP speech decoder is used, since the signal power from the unvoiced bands masks the (incorrect) voiced excitation. However, if the error is propagated into the LPC speech decoder, it results in a perceptually annoying artifact.

In step 414, pitch and voice are encoded together using the standard LPC-10 quantization algorithm. According to the LPC standard, pitch and voicing are encoded together.

c. Pitch Conversion

In step 416, the MELP pitch parameter is converted to an LPC-10 pitch parameter by taking the inverse logarithm of the MELP pitch parameter (since the MELP algorithm encodes pitch logarithmically). In step 418, the resulting LPC-10 pitch parameter is quantized according to the LPC-10 pitch quantization table.

In step 414, pitch and voice are encoded together using the standard LPC-10 quantization algorithm.

d. Gain (RMS) Conversion

As described previously, the MELP algorithm produces two half-frame logarithmically encoded gain (RMS) parameters per frame, whereas LPC produces a single RMS gain parameter per frame. In step 420, the inverse logarithm of each MELP half-frame gain parameter is taken. In step 424, the two resulting values are scaled to account for preemphasis addition which occurred in step 406 (similar to the gain scaling step 320 for the LPC-to-MELP transcoder described above). More specifically, both gain values are scaled by the ratio of the LPC predictor gain parameters derived from the spectrum before and after preemphasis addition. This LPC gain ratio is calculated in step 422 for each new frame of parametric data. If

lpcgain ⁢ ⁢ 1 = 1 ∏ i ⁢ ( 1 - rc 2 ⁡ ( i ) )
is defined as the synthesis filter gain before preemphasis addition and

lpcgain ⁢ ⁢ 2 = 1 ∏ i ⁢ ( 1 - rc ′2 ⁡ ( i ) )
is defined as the synthesis filter gain after preemphasis addition, then the scaling factor to be used for both MELP gains is

scale = lpcgain ⁢ ⁢ 2 8 * lpcgain ⁢ ⁢ 1

The factor of 8 is included to accommodate the 13 bit input and output sample scaling in LPC-10 (MELP utilizes 16 bit input and output samples). In step 424, both gain values are scaled by the above scaling value. The output of step 424 will be referred to as the “scaled MELP gains.”

In step 426, the LPC gain parameter is nominally set to the logarithmic average of the two scaled MELP gains. An adaptive combiner algorithm is then used to preserve plosive sounds by utilizing the LPC-10 synthesizer's ability to detect and activate the “impulse doublet” excitation mode. To explain, LPC-10 synthesizers use an “impulse doublet” excitation mode which preserves plosive sounds like the sounds of the letters ‘b’ and ‘p’. If the LPC synthesizer senses a strong increase in gain, it produces an impulse doublet. This keeps the ‘b’ and ‘p’ sounds from sounding like ‘s’ or ‘f’ sounds.

The algorithm used in step 426 is described as follows. First, the LPC gain parameter is nominally set to the logarithmic average of the two scaled MELP gains. Next, if it is determined that there is a large increase between the first and second half-frame scaled MELP gains, and the current and last transcoded frames are unvoiced, then the LPC gain parameter is set equal to the second half-frame scaled MELP gain. This emulates the adaptively-positioned analysis window used in LPC analysis and preserves LPC-10 synthesizer's ability to detect and activate the “impulse doublet” excitation mode for plosives. In other words, this method preserves sharp changes in gain to allow the LPC synthesizer to reproduce the ‘b’ and ‘p’ type sounds effectively.

In step 428, the LPC gain parameter is then quantized and encoded according to the quantizer tables for the LPC-10 standard algorithm.

In step 430, the encoded LPC spectrum, voicing, pitch, and gain parameters are inserted into a LPC frame and forward error correction (FEC) coding is added. An output bit stream representing the LPC frames is produced.

4. LPC to TDVC Transcoder

FIG. 5 illustrates a transcoding method 300 for converting a bit stream representing LPC-10 encoded frames to a bit stream representing TDVC encoded frames. In step 502, an incoming bit stream is received. The incoming bit stream represents LPC-10 frames containing LPC-10 parameters. In step 302, forward error correction (FEC) decoding is performed on the incoming bit stream. The LPC-10 frames are also decoded by extracting the LPC-10 spectrum, pitch, voicing, and gain parameters from the LPC-10 frames. The LPC-10 parameters are then distributed to steps 504, 514, and 526 for conversion to LPC-10 spectrum, voicing, and gain parameters, respectively (no conversion of pitch is necessary as described below). The method of transcoding from LPC-10 parameters to TDVC parameters can be divided into 2 types of operations: 1) conversion from LPC-10 parameters to TDVC parameters, and 2) frame interpolation to synchronize the different frame sizes. The frame interpolation operations are performed in steps 508, 516, 520, and 528 for interpolation of spectrum, voicing, pitch, and gain parameters, respectively. In the discussion that follows, the conversion steps will be discussed first, followed by a discussion of the frame interpolation steps.

a. Spectrum Conversion

While the LPC-10 analysis algorithm applies preemphasis before spectral analysis, the TDVC analysis does not, so the TDVC synthesizer expects spectral coefficients that were extracted from a nominal input signal. Thus, the preemphasis effects must be removed from the LPC spectral parameters.

In step 504, the LPC-10 reflection coefficients (RC) are converted to their equivalent normalized autocorrelation coefficients (R) using well known transformations. In order to avoid truncation effects in subsequent steps, the autocorrelation conversion recursion is carried out to 50 lags (setting RCs above order 10 to zero). The resulting values for the autocorrelation coefficients (R) are stored symmetrically in a first array.

In step 506, the preemphasis is removed in the correlation domain, described as follows. The symmetrical autocorrelation coefficients (HH) of the deemphasis filter are calculated beforehand and stored in an array. The deemphasis filter is a single pole IIR filter and is generally the inverse of the preemphasis filter, but different preemphasis and deemphasis coefficients may be used. The LPC-10 standard uses 0.9375 for preemphasis and 0.75 for deemphasis. Because the deemphasis filter has IIR characteristics, the autocorrelation function is carried out to 40 lags. The autocorrelation values (HH) are obtained by convolving the impulse response of the filter.

A modified set of spectral autocorrelation coefficients is calculated via convolving the R values with the HH values:

R ′ ⁡ ( k ) = ∑ i ⁢ R ⁡ ( i + k ) * HH ⁡ ( i )

The resulting modified autocorrelation coefficients R′ are converted to both reflection coefficients (RC′) and predictor filter coefficients (A′). The stability of the synthesis filter formed by the coefficients is checked; if the filter is unstable, the minimum order stable model is used (e.g. all RC's up to the unstable coefficient are used for the conversion to A′ coefficients). The RC′ values are saved for use by step 524 in calculating the TDVC gain, discussed further below.

The final step in the preemphasis removal process is to convert the deemphasized predictor filter coefficients (A′) to line spectrum frequencies (LSF) in preparation for frame interpolation in step 508. Frame interpolation, in step 508, is described in section e. below.

b. Voicing Conversion

In step 514, LPC-10 voicing parameters are converted to TDVC voicing parameters. The TDVC voicing parameter is called the “voicing cutoff frequency parameter” fsel (0=fully unvoiced, 7=fully voiced). The TDVC voicing cutoff frequency parameter fsel indicates a frequency above which the input frame is judged to contain unvoiced content, and below which the input frame is judged to contain voiced speech. On the other hand, LPC-10 uses a simple, half-frame on/off voicing bit.

Step 514 takes advantage of the expanded fsel voicing feature of the TDVC synthesizer during transitional periods such as voicing onset. The following C-code segment illustrates a method of converting LPC-10 voicing bits to TDVC voicing cutoff frequency parameter fsel:

	/* mid-frame onset */
	if ((lpc->voice[0]==0) && (lpc->voice[1]==1))
	fselnew = 2;
	/* fully voiced */
	else if ((lpc->voice[0]==1) && (lpc->voice[1]==1))
	fselnew = 7;
	/* full unvoiced and mid-frame unvoiced transition */
	else
	fselnew = 0;

where lpc→voice[0] and lpc→voice[1] are the half-frame LPC voicing bits (0=unvoiced), and fselnew is the TDVC fsel parameter. According to the TDVC standard, fselnew=0 corresponds to 0 Hz (DC) and fselnew=7 corresponds to 4 KHz, with each fselnew value equally spaced 562 Hz apart. The effect of the method illustrated by the above code is that when a mid-frame transition from the LPC unvoiced to voiced state occurs, the TDVC voicing output changes in a gradual fashion in the frequency domain (by setting fsel to an intermediate value of 2). This prevents a click sound during voicing onset and thereby reduces perceptual buzziness in the output speech.

c. Pitch Conversion

No conversion is required to convert from the LPC-10 pitch parameter to TDVC pitch parameter; the LPC-10 pitch parameter is simply copied to a temporary register for later interpolation in step 520, described below.

d. Gain (RMS) Conversion

In step 526, an adjustment for preemphasis removal must be made to the LPC gain parameter before it can be used in a TDVC synthesizer. This preemphasis removal process is described as follows.

The LPC gain parameter is scaled by the LPC gain ratio. The LPC gain ratio is calculated in step 524 for each new frame of data. The LPC gain ratio is the ratio of LPC predictor gains derived from the spectrum before and after preemphasis removal (deemphasis addition). If

lpcgain ⁢ ⁢ 1 = 1 ∏ i ⁢ ( 1 - rc ′2 ⁡ ( i ) )
is defined as the synthesis filter gain before preemphasis addition and

lpcgain ⁢ ⁢ 2 = 1 ∏ i ⁢ ( 1 - rc ′2 ⁡ ( i ) )
is defined as the synthesis filter gain after preemphasis addition, then the scaling factor (LPC Gain Ratio) to be used for the LPC RMS is

scale = 8 * lpcgain ⁢ ⁢ 2 lpcgain ⁢ ⁢ 1

This scale factor is the LPC Gain Ratio. The factor of 8 is included to accommodate the 13 bit input and output sample scaling in LPC-10 (TDVC utilizes 16 bit input and output samples). The scaling performed by step 526 is required because the LPC RMS gain is measured from the preemphasized input signal, while the TDVC gain is measured from the nominal input signal.

e. Frame Interpolation

Because LPC-10 and TDVC use different frame sizes (22.5 and 20 msec, respectively), a frame interpolation operation must be performed. To keep time synchronization, 8 frames of LPC parameter data must be converted to 9 frames of TDVC parameter data. A smooth interpolation function is used for this process, based on a master clock counter 510 that counts LPC frames on a modulo-8 basis from 0 to 7. At startup, the master clock counter 510 is initialized at 0. A new frame of LPC parameter data is read for each count; after all interpolation operations (described below), then “new” LPC parameter data is copied into the “old” parameter data area, and the master clock counter 510 is incremented by 1, with modulo 8 addition. The following interpolation weights are used to generate a set of TDVC parameter data from the “new” and “old” transformed LPC data:

wold = 2.5 * [ clock 20 ] wnew = 1.0 - wold

Note that at startup (clock=0), wold is set to zero, while wnew is set to 1.0. This is consistent with the LPC frame read schedule, as the contents of the “old” data area are undefined at startup. When the master clock counter 510 reaches 7, two frames of TDVC data are written. The first frame is obtained by interpolating the “old” and “new” transformed LPC data using the weights given by the equations above. The second frame is obtained by using the “old” transformed LPC data only (the same result as if master clock 510 were set to 8). The master clock 510 is then reset to 0 and the process begins again.

The interpolation equations for each TDVC parameter are as follows. Linear interpolation is used for line spectrum frequencies in step 508:
lsf(i)=wold*lsfold(i)+wnew*lsfnew(i)
where lsfnew( ) and lsfold( ) correspond to the “new” and “old” LSF data sets described above. The voicing parameter fsel is also linearly interpolated in step 516:
fsel=wold*fselold+wnew*fselnew
Likewise for the pitch in step 520:
TDVCpitch=wold*LPCpitchold+wnew*LPCpitchnew
Finally, the gain (RMS) is logarithmically interpolated in step 528. Using the scaled LPC RMS values derived above, the TDVC gain can be computed using the following C-code segment:
TDVCgain=pow(10.0,wold*log 10(LPCscaledRMSold)+wnew*log 10(LPCscaledRMSnew));

The interpolated spectrum, voicing, pitch and gain parameters are then quantized and encoded according to the TDVC standard algorithm in steps 512, 528, 522, and 530, respectively. In step 532, the encoded TDVC spectrum, voicing, pitch, and gain parameters are inserted into a TDVC frame and forward error correction (FEC) coding is added. An output bit stream representing the TDVC frames is transmitted.

5. MELP to TDVC Transcoder

FIG. 6 illustrates a transcoding method 600 for converting a bit stream representing MELP encoded frames to a bit stream representing TDVC encoded frames. In step 602, an incoming bit stream is received. The incoming bit stream represents MELP frames containing MELP parameters. In step 602, forward error correction (FEC) is decoding performed on the incoming bit stream. The MELP frames are also decoded by extracting the MELP spectrum, pitch, voicing, and gain parameters from the MELP frames. The MELP parameters are then distributed to steps 604, 612, 618 and 624 for conversion to TDVC spectrum, voicing, pitch and gain parameters, respectively.

The method of transcoding from MELP to TDVC can be divided into 2 types of operations: 1) conversion from MELP parameters to TDVC parameters, and 2) frame interpolation to synchronize the different frame sizes. The frame interpolation operations are performed in steps 606, 614, 620, and 628 for interpolation of spectrum, voicing, pitch, and gain parameters, respectively. In the discussion that follows, the conversion steps will be discussed first, followed by a discussion of the frame interpolation steps.

a. Spectrum Conversion

In step 604, the MELP LSFs are scaled to convert to TDVC LSFs. Since MELP and TDVC both use line spectrum frequencies (LSFs) to transmit spectral information, no conversion is necessary except for a multiplication by a scaling factor of 0.5 (to accommodate convention differences).

b. Voicing Conversion

In step 612, the MELP voicing parameters are converted to TDVC voicing parameters. As described previously, TDVC employs a single voicing cutoff frequency parameter (fsel: 0=fully unvoiced, 7=fully voiced) while MELP uses an overall voicing bit and five bandpass voicing strengths. The TDVC voicing cutoff frequency parameter fsel (also referred to as the voicing cutoff frequency “flag”) indicates a frequency above which the input frame is judged to contain unvoiced content, and below which the input frame is judged to contain voiced speech. The value of the voicing cutoff flag ranges from 0 for completely unvoiced to 7 for completely voiced.

The following C-code segment illustrates a conversion of the MELP voicing data to the TDVC fsel parameter by selecting a voicing cutoff frequency fsel that most closely matches the upper cutoff frequency of the highest frequency voiced band in MELP:

	if (melp->uv_flag == 1)
	fselnew = 0;
	else {
	for (i=4; i>=0; i−−)
	if (melp->bpvc[i] == 1.0) break;
	r0 = 1000.0*(float)i;
	if (r0 == 0.0) r0 = 500.0;
	if (r0 < 0.0) r0 = 0.0;
	for (i=0; i<=7; i++)
	if (abs((int)((float)i*571.4286 − r0)) < 286) break;
	fselnew = i;
	}

where melp→uv_flag is the MELP overall unvoiced flag (0=voiced), melp→bpvc[ ] are the bandpass voicing strengths (0.0 or 1.0, with 1.0=voiced), r0 is a temporary floating point variable, and fselnew is the TDVC fsel parameter.

As illustrated by the above code, the highest voiced frequency band in MELP is first identified. The frequency cutoffs for the MELP frequency bands are located at 500 Hz, 1000 Hz, 2000 Hz, and 3000 Hz. The frequency cutoff of the highest voiced band in MELP is used to choose the nearest corresponding value of fsel.

c. Pitch Conversion

In step 618, the MELP pitch parameters are converted to TDVC parameter. Since MELP pitch is logarithmically encoded, the TDVC pitch parameter (pitchnew) is obtained by taking an inverse logarithm of the MELP pitch parameter, as illustrated the following equation:
pitchnew=10^MELPpitch

d. Gain Conversion

In steps 624 and 626, the MELP gain parameters are converted to TDVC. There are 2 logarithmically-encoded half frame MELP gains per frame. These are decoded to linear values and then logarithmically averaged to form a single TDVC gain per frame. (They can also be left in the log domain for averaging to save computational cycles.) The following C-code segment performs this function:
gainnew=pow(10.0, 0.5*log 10(melp→gain[0])+0.5*log 10(melp→gain[1]));
where melp→gain[0] and melp→gain[1] are the first and second MELP half-frame gains (respectively), gainnew is the “new” gain (described below in the section on frame interpolation), pow( ) is the C library power function, and log 10 is the C library base-10 logarithm function.

e. Frame Interpolation

Because MELP and TDVC use different frame sizes (22.5 and 20 msec, respectively), an interpolation operation must be performed. To keep time synchronization, 8 frames of MELP parameter data must be converted to 9 frames of TDVC parameter data. A smooth interpolation function is used for this process, based on a master clock counter 608 that counts MELP frames on a modulo-8 basis from 0 to 7. At startup, the master clock counter 608 is initialized at 0. A new frame of MELP data is read for each count; after all interpolation operations (described below), then “new” MELP data is copied into the “old” data area, and the master clock counter 608 is incremented by 1, with modulo 8 addition and “old” transformed MELP data:

wold = 2.5 * [ clock 20 ] wnew = 1.0 - wold

Note that at startup (master clock=0), wold is set to zero, while wnew is set to 1.0. This is consistent with the MELP frame read schedule, as the contents of the “old” data are is undefined at startup. When the master clock counter 608 reaches 7, two frames of TDVC data are written. The first frame is obtained by interpolating the “old” and “new” transformed MELP data using the weights given by the equations above. The second frame is obtained by using the “old” transformed MELP data only (the same result as if clock were set to 8). The master clock 608 is then reset to 0 (via the modulo-8 addition) and the process begins again.

The interpolation equations for each TDVC parameter are as follows. Linear interpolation is used for line spectrum frequencies in step 606:
TDVClsf(i)=wold*lsfold(i)+wnew*lsfnew(i)
where lsfnew( ) and lsfold( ) correspond to the “new” and “old” LSF sets described above. The voicing parameter fsel is also linearly interpolated in step 614:
TDVCfsel=wold*fselold+wnew*fselnew
Likewise for the pitch in step 620:
TDVCpitch=wold*pitchold+wnew*pitchnew
Finally, the gain (RMS) is logarithmically interpolated in step 628. Using the scaled LPC RMS gain values derived above, the TDVC gain can be computed using the following C-code segment in step 628:
TDVCgain=pow(10.0, wold*log 10(gainold)+wnew*log 10(gainnew));

The interpolated spectrum, voicing, pitch, and gain parameters may now be quantized and encoded according to the TDVC standard algorithms in steps 610, 616, 622, and 630, respectively. In step 632, the encoded TDVC spectrum, voicing, pitch, and gain parameters are inserted into a TDVC frame and forward error correction (FEC) coding is added. An output bit stream representing the TDVC frames is transmitted.

6. TDVC to LPC Transcoder

FIG. 7 illustrates a transcoding method 700 for converting from TDVC encoded frames to LPC-10 encoded frames. The transcoding conversion from TDVC to LPC-10 consists of 2 operations: 1) conversion from MELP parameters to TDVC parameters, and 2) frame interpolation to synchronize the different frame sizes.

In step 702, an incoming bit stream is received. The incoming bit stream represents TDVC frames containing TDVC parameters. In step 702, forward error correction (FEC) decoding is performed on the incoming bit stream. The TDVC frames are also decoded by extracting the TDVC spectrum, pitch, voicing, and gain parameters from the TDVC frames.

a. Spectrum Conversion, Part 1 (Step 704)

In step 704, the TDVC line spectrum frequencies (LSFs) are transformed into predictor filter coefficients (A) using well known transformations. Next, adaptive bandwidth expansion is removed from the TDVC predictor filter coefficients A. Adaptive bandwidth expansion is used by TDVC but not by LPC (i.e., adaptive bandwidth expansion is applied during TDVC analysis but not by LPC analysis). When converting from TDVC to LPC, removing the adaptive bandwidth expansion effects from the spectral coefficients sharpens up the LPC spectrum and makes the resulting output sound better. The adaptive bandwidth expansion is removed by the following process:

• • 1) The original bandwidth expansion parameter gamma is calculated via:

gamma = MIN ⁡ [ 1.0 , pitch - 20 1000 + 0.98 ]

• • where pitch is the TDVC pitch parameter.
  • 2) Next, the reciprocal of gamma is calculated (rgamma=1.0/gamma).
  • 3) The predictor filter coefficients A are then scaled according to
    a′(i)=(rgamma)ⁱa(i)
  • 4) The new coefficient set a′(i) is checked for stability. If they form a stable LPC synthesis filter, then the modified coefficients a′(i) are used for further processing; if not, the original coefficients a(i) are used.
  • 5) The selected coefficient set (either a(i) or a′(i)) is then converted back into LSFs for interpolation using well known transformations.

b. Frame Interpolation

Because LPC-10 and TDVC use different frame sizes (22.5 and 20 msec, respectively), an interpolation operation must be performed. Interpolation of the spectrum, voicing, pitch, and gain parameters is performed in steps 706, 714, 720, and 724, respectively.

To keep time synchronization, 9 frames of TDVC parameter data must be converted to 8 frames of LPC parameter data. A smooth interpolation function is used for this process, based on a master clock counter 708 that counts LPC frames on a modulo-8 basis from 0 to 7. At startup, the count is initialized to zero. On master clock=0, two sequential TDVC data frames are read and labeled as “new” and “old”. On subsequent counts, the “new” frame data is copied into the “old” frame data area, and the next TDVC frame is read into the “new” data area. All TDVC parameters are interpolated using the following weighting coefficients:

wnew = 2.5 * [ ( clock + 1 ) 22.5 ] wold = 1.0 - wnew

Note that all parameters are interpolated in their TDVC format (e.g. spectrum in LSFs and voicing in fsel units). This produces better superior sound quality output, than if interpolation is performed in the LPC format.

The following adaptive interpolation technique is also used to improve plosive sounds. If a large change is detected in the TDVC parameters, an adjustment is made to the interpolation weighting coefficients. Specifically, 1) if the spectral difference between the “new” and “old” LSF sets is greater than 5 dB and 2) if the absolute difference between the “new” and “old” fsel parameters is greater than or equal to 5, and 3) the ratio of the “new” and “old” TDVC gain parameters is greater than 10 or less than 0.1, the following adjustment is performed (C-code):

	if (master_clock <= 3) {
	wnew = 0.0;
	wold = 1.0;
	}
	else {
	wnew = 1.0;
	wold = 0.0;
	}

The Interpolation Controller 708 handles this adjustment and changes the weighting coefficients wnew and wold for all four interpolation steps 706, 714, 720, and 724. A illustrated by the above code, if master clock 708 is at the beginning portion of the interpolation cycle (less than or equal to three) then the LPC output parameters (including spectrum, voicing, pitch and gain) will be fixed to the old LPC output. If the clock is at the end portion of the interpolation cycle (greater than three), then the LPC output (spectrum, voicing, pitch and gain) is fixed to the new LPC set. This adjustment emulates the adaptively-positioned analysis window used in LPC analysis and preserves LPC-10 synthesizer's ability to detect and activate the “impulse doublet” excitation mode for plosives. This preserves the sharp difference of plosive sounds and produces a crisper sound.

c. Spectrum Conversion—Part 2

In step 706, interpolation of the spectral coefficients is performed. To generate a single set of LPC spectral coefficients from the “new” and “old” TDVC LSFs, the LSFs are linearly interpolated using the wnew and wold coefficients described above:
lsf(i)=wold*lsfold(i)+wnew*lsfnew(i)

To complete the conversion of the spectral parameters, in step 708, preemphasis is added. The LPC-10 0.9375 preemphasis coefficient must be superimposed on the spectrum, since TDVC does not use preemphasis. This is performed in the correlation domain via transforming the interpolated LSFs into predictor coefficients (A) and then transforming the predictor coefficients into their equivalent normalized autocorrelation (R) coefficients and then employing the following operation:
R′(i)=R(i)−0.9375[R(|i−1|)+R(i+1)]+0.9375²R(i)
where R′(i) are the preemphasized autocorrelation coefficients. Note that the input set of R( )s must be computed out to 11 lags to avoid truncation. The modified autocorrelation coefficients R′(i) are now transformed back to predictor coefficients A′(i) for further processing.

In step 710, formant enhancement is performed on the predictor filter coefficients A′(i). Formant enhancement has been found to improve the quality of the transcoded speech. Two methods of formant enhancement are described in detail in sections 12 and 13 below. Section 12 describes a method of formant enhancement performed in the correlation domain. Section 13 describes a second method of formant enhancement performed in the frequency domain. Both formant enhancement methods utilize both the non-deemphasized filter coefficients (A) and the deemphasized filter coefficients (A′). Both methods of formant enhancement produce good results. Which one is preferable is a subjective determination made by the listener for the particular application. For the TDVC to LPC-10 transcoder, the majority of listeners polled showed a slight preference frequency domain method.

After the formant enhancement has been applied, the predictor filter coefficients A′(i) are converted to reflection coefficients (RCs) by well known transformations and quantized according to the LPC-10 quantizer tables in step 712.

d. Voicing Conversion and Jitter Factor Conversion

Voicing conversion uses the TDVC fsel voicing parameter and the first reflection coefficient RC. First, in step 714, the TDVC fsel voicing cutoff frequency parameter is linearly interpolated using the wnew and wold coefficients described above:
fsel=wold*fselold+wnew*fselnew
where fselold is the “old” value of fsel, and fselnew is the “new” value of fsel.

In step 716, the fsel voicing parameter is converted to an LPC voicing parameter. Simply using fsel voicing parameter bit to determine both half frame LPC voicing bits is inadequate. Additional information is required for the best perceptual performance. The preferred decision algorithm is described by the following C-code segment:

	if (fsel <= 2)
	lpc->voice[0] = lpc->voice[1] = 0;
	else
	lpc->voice[0] = lpc->voice[1] = 1;
	if ((fsel <= 4) && (rc[0] < 0.0))
	lpc->voice[0] = lpc->voice[1] = 0;

where lpc→voice[ ] are the half-frame LPC voicing bits (1=voiced), fsel is the interpolated TDVC fsel voicing parameter (0=fully unvoiced 7=fully voiced), and rc[0] is the first reflection coefficient (computed from the spectrum after preemphasis addition in step 708).

As illustrated by the above code, if the TDVC voicing cutoff frequency parameter fsel is less than or equal to 2, then both LPC half frame voicing bits are set to zero (unvoiced). If fsel is greater than 2, then both LPC half frame voicing bits are set to one (voiced). The exception occurs when fsel<=4 and the first reflection coefficient RC′(0) (after preemphasis addition) is less than zero. In this case, both LPC half frame voicing bits are set to zero (unvoiced). This last exception is implemented to improve the output sound performance. The reason this last improvement is performed is as follows. The TDVC voicing analysis algorithm will occasionally set a partially voiced condition (fsel>0 but fsel<=4) when the input signal is actually unvoiced. Unvoiced signals typically have a spectrum that is increasing in magnitude with frequency. The first reflection coefficient RC′[0] provides an indication the spectral slope, and when it is negative, the spectral magnitudes are increasing with frequency. Thus, this value can be used to correct the error.

Note that this type of voicing error is generally not apparent when a TDVC speech decoder is used, since the signal power from the unvoiced portion of the excitation masks the (incorrect) voiced excitation. However, if the error is propagated into the LPC speech decoder, it results in a perceptually annoying artifact.

In step 718, pitch and voicing are encoded together using the standard LPC-10 encoding algorithm.

e. Pitch Conversion

1. A method for transcoding a bit stream encoded according to a mixed-excitation linear prediction (MELP) standard to a bit stream encoded according to a linear predictive coding (LPC) standard, comprising: decoding a bit stream into a first set of vocoder parameters compatible with the MELP standard; transforming the first set of vocoder parameters into a second set of vocoder parameters compatible with the LPC standard without converting the first set of vocoder parameters to an analog or digital waveform representation; and encoding the second set of vocoder parameters into a bit stream compatible with the LPC vocoder standard, wherein the transforming includes converting MELP spectrum parameters to LPC spectrum parameters, and wherein the converting of MELP spectrum parameters to LPC spectrum parameters includes: converting MELP line spectrum frequencies (LSF) to their equivalent normalized autocorrelation coefficients (R); and

adding preemphasis effects to the normalized autocorrelation coefficients wherein the preemphasis addition is performed according to the following equation to form preemphasized autocorrelation coefficients R′(i):
R′(i)=R(i)−0.9375[R(|i−1|)+R(i+1)]+0.9375²R(i).

2. A method for transcoding a bit stream encoded according to a mixed-excitation linear prediction (MELP) standard to a bit stream encoded according to a linear predictive coding (LPC) standard, comprising: decoding a bit stream into a first set of vocoder parameters compatible with the MELP standard; transforming the first set of vocoder parameters into a second set of vocoder parameters compatible with the LPC standard without converting the first set of vocoder parameters to an analog or digital waveform representation; and encoding the second set of vocoder parameters into a bit stream compatible with the LPC vocoder standard, wherein the transforming includes converting MELP spectrum, voicing, pitch, and gain parameters to LPC spectrum, voicing, pitch, and gain parameters, and wherein the converting of MELP voicing parameters to LPC voicing parameters includes assigning of values to LPC voicing bits including: (a) setting both half-frame LPC voicing bits to one (voiced) if a MELP overall unvoiced flag equals zero (voiced); otherwise, setting both half-frame LPC voicing bits to one (unvoiced); and (b) setting both half-frame LPC voicing bits to zero (unvoiced) if a first reflection coefficient RC′[0] (after preemphasis addition) is negative, and a total number of MELP bandpass voicing strengths which are voiced is less than or equal to four.

3. A method for transcoding a bit stream encoded according to a mixed-excitation linear prediction (MELP) standard to a bit stream encoded according to a linear predictive coding (LPC) standard, comprising: decoding a bit stream into a first set of vocoder parameters compatible with the MELP standard; transforming the first set of vocoder parameters into a second set of vocoder parameters compatible with the LPC standard without converting the first set of vocoder parameters to an analog or digital waveform representation, said transforming including converting MELP spectrum, voicing, pitch, and gain parameters to LPC spectrum, voicing, pitch, and gain parameters; and encoding the second set of vocoder parameters into a bit stream compatible with the LPC vocoder standard, wherein the converting of MELP gain parameters to LPC gain parameters includes taking an inverse logarithm of both MELP half-frame gain parameters for each MELP frame received; scaling the two resulting values by a ratio of the LPC predictor gain parameters derived from the spectrum before and after preemphasis addition; and nominally setting the LPC gain parameter to a logarithmic average of the two scaled values; and preserving plosive sounds by an adaptive combining process comprising: a) determining if there is more than a predetermined amount of increase between first and the second half-frame scaled MELP gain values and current and last transcoded frames are unvoiced; and b) if so, setting the LPC gain parameter to be equal to the second half-frame scaled MELP gain value.

4. A transcoder for transcoding a bit stream encoded according to a mixed-excitation linear prediction (MELP) standard to a bit stream encoded according to a linear predictive coding (LPC) standard, comprising: a decoder to decode a bit stream into a first set of vocoder parameters compatible with the MELP standard; a conversion unit to transform the first set of vocoder parameters into a second set of vocoder parameters compatible with the LPC standard without converting the first set of vocoder parameters to an analog or digital waveform representation; and an encoder to encode the second set of vocoder parameters into a bit stream compatible with the LPC vocoder standard, wherein the conversion unit converts the MELP spectrum parameters to LPC spectrum parameters by performing steps including: converting MELP line spectrum frequencies (LSF) to their equivalent normalized autocorrelation coefficients (R); and

adding preemphasis effects to the normalized autocorrelation coefficients; and,

wherein the conversion unit performs the preemphasis addition according to the following equation to form preemphasized autocorrelation coefficients R′(i):
R′(i)==R(i)−0.9375[R(|i−1|)+R(i+1)]+0.93752²R(i).

5. A transcoder for transcoding a bit stream encoded according to a mixed-excitation linear prediction (MELP) standard to a bit stream encoded according to a linear predictive coding (LPC) standard, comprising: a decoder to decode a bit stream into a first set of vocoder parameters compatible with the MELP standard; a conversion unit to transform the first set of vocoder parameters into a second set of vocoder parameters compatible with the LPC standard without converting the first set of vocoder parameters to an analog or digital waveform representation; and an encoder to encode the second set of vocoder parameters into a bit stream compatible with the LPC vocoder standard, wherein the conversion unit converts the MELP spectrum parameters to LPC spectrum parameters by performing steps including: converting MELP line spectrum frequencies (LSF) to their equivalent normalized autocorrelation coefficients (R); and

adding preemphasis effects to the normalized autocorrelation coefficients;

wherein the conversion unit is further configured to convert MELP voicing, pitch, and gain parameters to LPC voicing, pitch, and gain parameters;

wherein the conversion unit converts MELP voicing parameters to LPC voicing parameters by performing steps including: assigning values to LPC voicing bits based on MELP bandpass voicing strengths, a MELP overall voicing bit, and a first reflection coefficient after preemphasis addition, RC′[0]; and,

wherein the assigning of values to the LPC voicing bits includes: a) setting both half-frame LPC voicing bits to one (voiced) if a MELP overall unvoiced flag equals zero (voiced); otherwise, setting both half-frame LPC voicing bits to one (unvoiced); and b) setting both half-frame LPC voicing bits to zero (unvoiced) if the first reflection coefficient RC′[0] (after preemphasis addition) is negative, and a total number of MELP bandpass voicing strengths which are voiced is less than or equal to four.

6. The transcoder of claim 5, wherein the conversion unit converts the MELP pitch parameter to an LPC pitch parameter by taking an inverse logarithm of the MELP pitch parameter, and quantizing the resulting LPC pitch parameter according to the LPC pitch quantization table.

7. The transcoder of claim 6, wherein the LPC pitch and voice parameters are encoded together using a standard LPC quantization algorithm.

8. A transcoder for transcoding a bit stream encoded according to a mixed-excitation linear prediction (MELP) standard to a bit stream encoded according to a linear predictive coding (LPC) standard, comprising: a decoder to decode a bit stream into a first set of vocoder parameters compatible with the MELP standard; a conversion unit to transform the first set of vocoder parameters into a second set of vocoder parameters compatible with the LPC standard without convening the first set of vocoder parameters to an analog or digital waveform representation; and an encoder to encode the second set of vocoder parameters into a bit stream compatible with the LPC vocoder standard, wherein the conversion unit converts the MELP spectrum parameters to LPC spectrum parameters by performing steps including: converting MELP line spectrum frequencies (LSF) to their equivalent normalized autocorrelation coefficients (R); and

adding preemphasis effects to the normalized autocorrelation coefficients;

wherein the conversion unit converts MELP gain parameters to LPC gain parameters by performing steps including: a) taking an inverse logarithm of both MELP half-frame gain parameters for each MELP frame received; b) scaling the two resulting values by a ratio of the LPC predictor gain parameters derived from the spectrum before and after preemphasis addition; and c) nominally setting the LPC gain parameter to a logarithmic average of the two scaled values; and,

wherein the conversion unit converts MELP gain parameters to LPC gain parameters by further performing the step of preserving plosive sounds by an adaptive combining process comprising: a) determining if there is more than a predetermined amount of increase between first and second half-frame scaled MELP gain values and current and last transcoded frames are unvoiced; and b) if so, setting the LPC gain parameter to be equal to the second half-frame scaled MELP gain value.

9. The transcoder of claim 8, wherein the LPC gain parameter is quantized and encoded according to quantization tables for the LPC standard algorithm.

10. The transcoder of claim 8, wherein the encoder is to encode the LPC spectrum parameters, pitch parameters, voicing parameters, and gain parameters according to an LPC quantization standard algorithm.