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EP0570362B1 - Digital speech decoder having a postfilter with reduced spectral distortion - Google Patents

Digital speech decoder having a postfilter with reduced spectral distortion Download PDF

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Publication number
EP0570362B1
EP0570362B1 EP90913916A EP90913916A EP0570362B1 EP 0570362 B1 EP0570362 B1 EP 0570362B1 EP 90913916 A EP90913916 A EP 90913916A EP 90913916 A EP90913916 A EP 90913916A EP 0570362 B1 EP0570362 B1 EP 0570362B1
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Prior art keywords
component
postfilter
speech
signal
filter
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EP0570362A1 (en
EP0570362A4 (en
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Ira Alan Gerson
Mark Antoni Jasiuk
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Motorola Solutions Inc
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    • GPHYSICS
    • G10MUSICAL INSTRUMENTS; ACOUSTICS
    • G10LSPEECH ANALYSIS TECHNIQUES OR SPEECH SYNTHESIS; SPEECH RECOGNITION; SPEECH OR VOICE PROCESSING TECHNIQUES; SPEECH OR AUDIO CODING OR DECODING
    • G10L19/00Speech or audio signals analysis-synthesis techniques for redundancy reduction, e.g. in vocoders; Coding or decoding of speech or audio signals, using source filter models or psychoacoustic analysis
    • G10L19/04Speech or audio signals analysis-synthesis techniques for redundancy reduction, e.g. in vocoders; Coding or decoding of speech or audio signals, using source filter models or psychoacoustic analysis using predictive techniques
    • G10L19/26Pre-filtering or post-filtering

Definitions

  • This invention relates generally to speech coders, and more particularly to digital speech coders that use postfilters to enhance the speech quality.
  • Speech coders and decoders are known in the art. Some speech coders convert analog voice samples into digitized representations, and subsequently represent the spectral speech information through use of linear predictive coding (see, for example, document EP-A-0 294 020). Other speech coders improve upon ordinary linear predictive coding (LPC) techniques by providing an excitation signal that is related to the original voice signal.
  • LPC linear predictive coding
  • U.S. Patent No. 4,817,157 describes a digital speech coder and decoder having an improved vector excitation source wherein a codebook of codebook excitation vectors is accessed to select a codebook excitation signal that best fits the available information, and is used to provide a synthesized speech signal from an LPC filter that closely represents the original.
  • various post-LPC filters are often used to further condition the signal.
  • One such filter is an adaptive spectral postfilter (which is typically intended to enhance the perceptual quality of the synthetic speech), and another is a post emphasis filter (which contributes brightness to the synthetic speech result).
  • the numerator term attempts to cancel the general spectral shape introduced by the denominator. In prior art applications, ⁇ is often set to about 0.8, and ⁇ to about 0.5.
  • the numerator polynomial is only partially successful in tracking the spectral shape of the denominator (in effect, the spectral characteristic of the filter tilts with time), and that discrepancy typically manifests itself as a time varying modulation of the postfiltered speech brightness.
  • a method for producing a synthesized speech signal comprising the steps of: providing an excitation signal to a linear predictive coding (LPC) filter; providing from the LPC filter a synthesized speech signal; providing a speech synthesis postfilter that requires a first component and a second component; providing the first component including a first set of coefficients; the method characterised by the steps of: transforming at least some of the first set of coefficients into an autocorrelation domain set of parameters; spectrally smoothing the autocorrelation domain set of parameters to provide a modified first set of coefficients; using the modified first set of coefficients to provide the second component for use by the speech synthesis postfilter; filtering the synthesized speech signal in the speech synthesis postfilter using the first component and the second component to provide a filtered synthesized speech signal, wherein the second component adaptively tracks and cancels out a general spectral shape of the first component; and rendering the filtered synthesized speech signal audible.
  • LPC linear predictive coding
  • Z transform (filter) coefficients that represent the first component are converted to the autocorrelation domain.
  • a spectral smoothing technique that makes use of a bandwidth expansion function is then applied to the autocorrelation sequence, and the second component polynomial coefficients are calculated from the modified autocorrelation sequence via the Levinson recursion.
  • the first component is then used as the denominator, and the second component as the numerator, in the above noted filter characteristic.
  • the numerator polynomial is replaced by a spectrally smoothed version of the A(z/ ⁇ ) polynomial.
  • Formant bandwidth expansion does not change the smoothed spectral envelope.
  • the spectrally smoothed bandwidth expanded version of the A(z/ ⁇ ) polynomial effectively minimizes time varying spectral tilt and allows the numerator to adaptively track the general spectral shape of the denominator and cancel it out.
  • an additional post emphasis filter can be used to afford more control over postfiltered speech brightness.
  • This filter is a first order filter of the form where typically 0.2 ⁇ u ⁇ 0.5.
  • a radio (100) embodying the invention includes an antenna (102) for receiving a speech coded radio frequency (RF) signal (101).
  • An RF unit (103) processes the received signal to recover the speech coded information.
  • This information is provided to a parameter decoder (105) that develops control parameters for various subsequent processes.
  • An excitation source (104) as described above utilizes the parameters provided to it to create an excitation signal.
  • This resultant excitation signal from the excitation source (104) is provided to an LPC filter (106) that yields a synthesized speech signal in accordance with the coded information.
  • the synthesized speech signal is then pitch postfiltered (107) and spectrally postfiltered (108) to enhance the quality of the reconstructed speech.
  • a post emphasis filter (109) can also be included to further enhance the resultant speech signal. (Additional details regarding the spectral postfilter (108) and the post emphasis filter (109) will be provided below.)
  • the speech signal is then processed in an audio processing unit (111) and rendered audible by an audio transducer (112).
  • the excitation source (104), LPC filter (106), pitch postfilter (107), adaptive spectral postfilter (108), and post emphasis filter (109) can all be provided through appropriate programming of a DSP (113).
  • the adaptive spectral postfilter (108) is characterized by a first component (a denominator that is related to the filter characteristics of the LPC filter (106)) and a second component (a numerator that adaptively tracks the general spectral shape of the denominator to thereby cancel it out).
  • a first component a denominator that is related to the filter characteristics of the LPC filter (106)
  • a second component a numerator that adaptively tracks the general spectral shape of the denominator to thereby cancel it out.
  • the general form of such a filter can be found described in an article entitled "Real-Time Vector APC Speech Coding at 4800 bps With Adaptive Postfiltering," by Chen and Gersho, which appeared in the April, 1987 edition of the Proceedings of The International Conference on Acoustics, Speech, and Signal Processing, at pages 2185-2188.
  • the numerator is developed by applying spectral smoothing techniques to the denominator polynomial.
  • spectral smoothing techniques are described in an article entitled "Spectral Smoothing Technique in PARCOR Speech Analysis - Synthesis," by Tohkura, Itakura, and Hashimoto, which appeared in the December, 1978 edition of the I.E.E.E. Transactions on Acoustics, Speech, and Signal Processing.
  • Z transform coefficients that represent the denominator are converted to the autocorrelation domain.
  • Examples of such conversions can be found in Markel, J.D. Gray, A.H., Jr.; Linear Prediction of Speech (Springer-Verlag, Berlin, Heidelberg, New York, 1976.)
  • the spectral smoothing technique bandwidth expansion function is then applied to the autocorrelation sequence, with the numerator polynomial coefficients being calculated from the modified autocorrelation sequence via the Levinson recursion.
  • the autocorrelation coefficients are multiplied by the following factors to provide the resultant numerator coefficients: Autocorrelation Lag Spectral Smoothing Factor 0 1.0000000 1 0.9230769 2 0.7252747 3 0.4835164 4 0.2719780 5 0.1279896 6 4.9773753E-02 7 1.5718028E-02 8 3.9295070E-03 9 7.4847753E-04 10 1.0206513E-04
  • the denominator and numerator are then used to characterize the adaptive spectral postfilter (108).
  • the numerator polynomial is provided by a spectrally smoothed version of the denominator polynomial.
  • the spectrally smoothed bandwidth expanded version of the denominator polynomial effectively minimizes time varying spectral tilt and allows the numerator to adaptively track the general spectral shape of the denominator and cancel it out.
  • a bandwidth expansion factor (which specifies the degree of smoothing that is performed on the denominator) of about 1,200 Hz was used.
  • the adaptive spectral postfilter is characterized by a first component, or denominator, and a second component, or numerator.
  • the first component which can be expressed as: is provided in block 202.
  • the z-transform coefficients are converted to the autocorrelation domain.
  • a spectral smoothing bandwidth expansion function is applied to the autocorrelation sequence, and, in the subsequent block (205), the numerator (second component) polynomial coefficients are calculated from the autocorrelation sequence modified in the previous step (204), through the use of the Levinson recursion.
  • the numerator, or second component can be expressed as: 1-B(z).
  • the first and second components are used to characterize the adaptive spectral postfilter, which can be represented as:
  • the post emphasis filter (109) may be provided to afford more control over postfiltered speech brightness.
  • This filter is a first order filter of the form

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  • Engineering & Computer Science (AREA)
  • Computational Linguistics (AREA)
  • Signal Processing (AREA)
  • Health & Medical Sciences (AREA)
  • Audiology, Speech & Language Pathology (AREA)
  • Human Computer Interaction (AREA)
  • Physics & Mathematics (AREA)
  • Acoustics & Sound (AREA)
  • Multimedia (AREA)
  • Compression, Expansion, Code Conversion, And Decoders (AREA)
  • Filters That Use Time-Delay Elements (AREA)
  • Transmission Systems Not Characterized By The Medium Used For Transmission (AREA)

Abstract

An adaptive spectral postfilter (108) in a synthesized speech platform has a denominator characteristic that corresponds to a preceding LPC filter stage (106) and a numerator characteristic that is developed as a function of the denominator characteristic through application of spectral smoothing techniques. This allows the numerator to track the denominator without the introduction of spectral distortion that would otherwise affect the processing in an adverse way.

Description

    Technical Field
  • This invention relates generally to speech coders, and more particularly to digital speech coders that use postfilters to enhance the speech quality.
  • Background of the Invention
  • Speech coders and decoders are known in the art. Some speech coders convert analog voice samples into digitized representations, and subsequently represent the spectral speech information through use of linear predictive coding (see, for example, document EP-A-0 294 020). Other speech coders improve upon ordinary linear predictive coding (LPC) techniques by providing an excitation signal that is related to the original voice signal.
  • U.S. Patent No. 4,817,157 describes a digital speech coder and decoder having an improved vector excitation source wherein a codebook of codebook excitation vectors is accessed to select a codebook excitation signal that best fits the available information, and is used to provide a synthesized speech signal from an LPC filter that closely represents the original.
  • Once the synthesized speech signal has been developed, various post-LPC filters are often used to further condition the signal. One such filter is an adaptive spectral postfilter (which is typically intended to enhance the perceptual quality of the synthetic speech), and another is a post emphasis filter (which contributes brightness to the synthetic speech result).
  • An adaptive spectral postfilter is typically of the general form: H(z) = 1 - A(zη )1 - A(zν ) ,    where 0 ≤ η ≤ ν < 1
       and 1 / 1 - A(z) represents the associated LPC filter.
  • The denominator term in the above postfilter representation emphasizes the formants in the synthetic signal spectrum, while attenuating the spectral valleys. (In the two extremes, setting ν = results in an all-pass filter, while setting ν = 1 results in a denominator term that is the same as the associated LPC filter.) The numerator term attempts to cancel the general spectral shape introduced by the denominator. In prior art applications, ν is often set to about 0.8, and η to about 0.5.
  • In practice, the numerator polynomial is only partially successful in tracking the spectral shape of the denominator (in effect, the spectral characteristic of the filter tilts with time), and that discrepancy typically manifests itself as a time varying modulation of the postfiltered speech brightness.
  • Accordingly, a need exists for a method of postfiltering synthesized speech that will both enhance the perceptual quality of the synthetic speech, while simultaneously minimizing detrimental impact on speech brightness. Preferably, speech brightness itself will be better controlled as well.
  • Summary of the Invention
  • According to the present invention there is provided a method for producing a synthesized speech signal, comprising the steps of: providing an excitation signal to a linear predictive coding (LPC) filter; providing from the LPC filter a synthesized speech signal; providing a speech synthesis postfilter that requires a first component and a second component; providing the first component including a first set of coefficients; the method characterised by the steps of: transforming at least some of the first set of coefficients into an autocorrelation domain set of parameters; spectrally smoothing the autocorrelation domain set of parameters to provide a modified first set of coefficients; using the modified first set of coefficients to provide the second component for use by the speech synthesis postfilter; filtering the synthesized speech signal in the speech synthesis postfilter using the first component and the second component to provide a filtered synthesized speech signal, wherein the second component adaptively tracks and cancels out a general spectral shape of the first component; and rendering the filtered synthesized speech signal audible.
  • In one embodiment, Z transform (filter) coefficients that represent the first component are converted to the autocorrelation domain. A spectral smoothing technique that makes use of a bandwidth expansion function is then applied to the autocorrelation sequence, and the second component polynomial coefficients are calculated from the modified autocorrelation sequence via the Levinson recursion. The first component is then used as the denominator, and the second component as the numerator, in the above noted filter characteristic.
  • Via this process, the numerator polynomial is replaced by a spectrally smoothed version of the A(z/ν) polynomial. Formant bandwidth expansion does not change the smoothed spectral envelope. Thus, the spectrally smoothed bandwidth expanded version of the A(z/ν) polynomial effectively minimizes time varying spectral tilt and allows the numerator to adaptively track the general spectral shape of the denominator and cancel it out.
  • In another embodiment, an additional post emphasis filter can be used to afford more control over postfiltered speech brightness. This filter is a first order filter of the form
    Figure 00040001
    where typically 0.2 ≤ u ≤ 0.5.
  • An exemplary embodiment of the invention will now be described with reference to the accompanying drawings.
  • Brief Description of the Drawings
  • Fig. 1 comprises a block diagrammatic depiction of a radio configured in accordance with the invention; and
  • Fig. 2. is a flowchart depicting the characterization of an adaptive spectral postfilter in accordance with the present invention.
  • Best Mode For Carrying Out The Invention
  • U.S. Patent No. 4,817,157, entitled "Digital Speech Coder Having Improved Vector Excitation Source," as issued to Ira Gerson on March 28, 1989 describes in significant detail a digital speech coder and decoder. As detailed in the above noted reference, this invention can be embodied in a speech coder (or decoder) that makes use of an appropriate digital signal processor such as a Motorola DSP56000 family device.
  • In Fig. 1, a radio (100) embodying the invention includes an antenna (102) for receiving a speech coded radio frequency (RF) signal (101). An RF unit (103) processes the received signal to recover the speech coded information. This information is provided to a parameter decoder (105) that develops control parameters for various subsequent processes. An excitation source (104) as described above utilizes the parameters provided to it to create an excitation signal. This resultant excitation signal from the excitation source (104) is provided to an LPC filter (106) that yields a synthesized speech signal in accordance with the coded information. The synthesized speech signal is then pitch postfiltered (107) and spectrally postfiltered (108) to enhance the quality of the reconstructed speech. If desired, a post emphasis filter (109) can also be included to further enhance the resultant speech signal. (Additional details regarding the spectral postfilter (108) and the post emphasis filter (109) will be provided below.)
  • The speech signal is then processed in an audio processing unit (111) and rendered audible by an audio transducer (112). The excitation source (104), LPC filter (106), pitch postfilter (107), adaptive spectral postfilter (108), and post emphasis filter (109) can all be provided through appropriate programming of a DSP (113).
  • Pursuant to this invention, the adaptive spectral postfilter (108) is characterized by a first component (a denominator that is related to the filter characteristics of the LPC filter (106)) and a second component (a numerator that adaptively tracks the general spectral shape of the denominator to thereby cancel it out). The general form of such a filter can be found described in an article entitled "Real-Time Vector APC Speech Coding at 4800 bps With Adaptive Postfiltering," by Chen and Gersho, which appeared in the April, 1987 edition of the Proceedings of The International Conference on Acoustics, Speech, and Signal Processing, at pages 2185-2188.
  • Pursuant to this invention, the numerator is developed by applying spectral smoothing techniques to the denominator polynomial. Such techniques are described in an article entitled "Spectral Smoothing Technique in PARCOR Speech Analysis - Synthesis," by Tohkura, Itakura, and Hashimoto, which appeared in the December, 1978 edition of the I.E.E.E. Transactions on Acoustics, Speech, and Signal Processing.
  • In one embodiment, Z transform coefficients that represent the denominator are converted to the autocorrelation domain. (Examples of such conversions can be found in Markel, J.D. Gray, A.H., Jr.; Linear Prediction of Speech (Springer-Verlag, Berlin, Heidelberg, New York, 1976.) The spectral smoothing technique bandwidth expansion function is then applied to the autocorrelation sequence, with the numerator polynomial coefficients being calculated from the modified autocorrelation sequence via the Levinson recursion. In one embodiment, the autocorrelation coefficients are multiplied by the following factors to provide the resultant numerator coefficients:
    Autocorrelation Lag Spectral Smoothing Factor
    0 1.0000000
    1 0.9230769
    2 0.7252747
    3 0.4835164
    4 0.2719780
    5 0.1279896
    6 4.9773753E-02
    7 1.5718028E-02
    8 3.9295070E-03
    9 7.4847753E-04
    10 1.0206513E-04
  • The denominator and numerator are then used to characterize the adaptive spectral postfilter (108).
  • It would of course also be possible to use the LPC filter information directly and to develop the numerator term therefrom through a similar process, since the LPC filter information is used to develop the denominator term as described above.
  • Via this process, the numerator polynomial is provided by a spectrally smoothed version of the denominator polynomial. The spectrally smoothed bandwidth expanded version of the denominator polynomial effectively minimizes time varying spectral tilt and allows the numerator to adaptively track the general spectral shape of the denominator and cancel it out. Based upon listening tests, a bandwidth expansion factor (which specifies the degree of smoothing that is performed on the denominator) of about 1,200 Hz was used.
  • The flowchart of Fig. 2 aids in understanding the postfilter characterization process just described. As discussed previously, the adaptive spectral postfilter is characterized by a first component, or denominator, and a second component, or numerator. The first component, which can be expressed as:
    Figure 00080001
    is provided in block 202. In the subsequent step (203), the z-transform coefficients are converted to the autocorrelation domain. In block 204, a spectral smoothing bandwidth expansion function is applied to the autocorrelation sequence, and, in the subsequent block (205), the numerator (second component) polynomial coefficients are calculated from the autocorrelation sequence modified in the previous step (204), through the use of the Levinson recursion. The numerator, or second component, can be expressed as: 1-B(z). Finally (206), the first and second components (denominator and numerator) are used to characterize the adaptive spectral postfilter, which can be represented as:
    Figure 00080002
  • The post emphasis filter (109) may be provided to afford more control over postfiltered speech brightness. This filter is a first order filter of the form
    Figure 00090001

Claims (6)

  1. A method for producing a synthesized speech signal, comprising the steps of:
    A) providing an excitation signal to a linear predictive coding filter;
    B) providing from the linear predictive coding filter a synthesized speech signal;
    C) providing a speech synthesis postfilter that requires a first component and a second component;
    D) providing the first component including a first set of coefficients;
    E) transforming at least some of the first set of coefficients into an autocorrelation domain set of parameters;
    F) spectrally smoothing the autocorrelation domain set of parameters to provide a modified first set of coefficients;
    G) using the modified first set of coefficients to provide the second component for use by the speech synthesis postfilter;
    H) filtering the synthesized speech signal in the speech synthesis postfilter using the first component and the second component to provide a filtered synthesized speech signal; and
    I) rendering the filtered synthesized speech signal audible.
  2. A method for producing a synthesized speech signal according to claim 1, further comprising the steps of:
    A) receiving a radio frequency (RF) signal that includes coded speech information;
    B) recovering from the coded speech information an excitation signal; and
    C) providing the excitation signal to a linear predictive coding (LPC) filter;
    and whererin a first component is for use by the speech synthesis postfilter.
  3. The method of claim 1 or 2, wherein the LPC filter is at least partially defined by the expression: 11- A(z)
  4. The method of claim 1 or 2, wherein the first component of the speech synthesis postfilter is of the form
    Figure 00110001
    as represented in Z transform notation.
  5. The method of claim 1 or 2, further including the step of:
    A) filtering the synthesized speech signal in a post emphasis filter substantially defined, in Z transform notation, as:
    Figure 00110002
    where 0.2 ≤ u ≤ 0.5.
  6. The method of any preceding claim, wherein the step of operating includes the step of multiplying.
EP90913916A 1989-10-17 1990-09-17 Digital speech decoder having a postfilter with reduced spectral distortion Expired - Lifetime EP0570362B1 (en)

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US42292689A 1989-10-17 1989-10-17
US422926 1989-10-17
PCT/US1990/005190 WO1991006093A1 (en) 1989-10-17 1990-09-17 Digital speech decoder having a postfilter with reduced spectral distortion

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EP0570362A4 EP0570362A4 (en) 1993-07-01
EP0570362A1 EP0570362A1 (en) 1993-11-24
EP0570362B1 true EP0570362B1 (en) 1999-03-17

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Publication number Priority date Publication date Assignee Title
FR2729246A1 (en) * 1995-01-06 1996-07-12 Matra Communication SYNTHETIC ANALYSIS-SPEECH CODING METHOD
FR2729244B1 (en) * 1995-01-06 1997-03-28 Matra Communication SYNTHESIS ANALYSIS SPEECH CODING METHOD
FR2729247A1 (en) * 1995-01-06 1996-07-12 Matra Communication SYNTHETIC ANALYSIS-SPEECH CODING METHOD
JP2993396B2 (en) * 1995-05-12 1999-12-20 三菱電機株式会社 Voice processing filter and voice synthesizer
DE19643900C1 (en) * 1996-10-30 1998-02-12 Ericsson Telefon Ab L M Audio signal post filter, especially for speech signals
US6137844A (en) * 1998-02-02 2000-10-24 Oki Telecom, Inc. Digital filter for noise and error removal in transmitted analog signals

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US4301329A (en) * 1978-01-09 1981-11-17 Nippon Electric Co., Ltd. Speech analysis and synthesis apparatus
US4617676A (en) * 1984-09-04 1986-10-14 At&T Bell Laboratories Predictive communication system filtering arrangement
JP2535833B2 (en) * 1986-07-03 1996-09-18 日本電気株式会社 Integrated circuit
US4852169A (en) * 1986-12-16 1989-07-25 GTE Laboratories, Incorporation Method for enhancing the quality of coded speech
US4969192A (en) * 1987-04-06 1990-11-06 Voicecraft, Inc. Vector adaptive predictive coder for speech and audio
US4817157A (en) * 1988-01-07 1989-03-28 Motorola, Inc. Digital speech coder having improved vector excitation source

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DE69033011D1 (en) 1999-04-22
JP3158434B2 (en) 2001-04-23
AU635342B2 (en) 1993-03-18
DE69033011T2 (en) 2001-10-04
JPH05500573A (en) 1993-02-04
EP0570362A1 (en) 1993-11-24
ES2131498T3 (en) 1999-08-01
ATE177867T1 (en) 1999-04-15
CN1078371C (en) 2002-01-23
EP0570362A4 (en) 1993-07-01
CN1051101A (en) 1991-05-01
WO1991006093A1 (en) 1991-05-02
AU6411490A (en) 1991-05-16

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