EP0570362A1 - Digital speech decoder having a postfilter with reduced spectral distortion - Google Patents

Digital speech decoder having a postfilter with reduced spectral distortion

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Publication number
EP0570362A1
EP0570362A1 EP90913916A EP90913916A EP0570362A1 EP 0570362 A1 EP0570362 A1 EP 0570362A1 EP 90913916 A EP90913916 A EP 90913916A EP 90913916 A EP90913916 A EP 90913916A EP 0570362 A1 EP0570362 A1 EP 0570362A1
Authority
EP
European Patent Office
Prior art keywords
component
coefficients
postfilter
providing
parameters
Prior art date
Legal status (The legal status is an assumption and is not a legal conclusion. Google has not performed a legal analysis and makes no representation as to the accuracy of the status listed.)
Granted
Application number
EP90913916A
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German (de)
French (fr)
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EP0570362A4 (en
EP0570362B1 (en
Inventor
Ira Alan Gerson
Mark Antoni Jasiuk
Current Assignee (The listed assignees may be inaccurate. Google has not performed a legal analysis and makes no representation or warranty as to the accuracy of the list.)
Motorola Solutions Inc
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Motorola Inc
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Publication of EP0570362A1 publication Critical patent/EP0570362A1/en
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Publication of EP0570362B1 publication Critical patent/EP0570362B1/en
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Classifications

    • G—PHYSICS
    • G10—MUSICAL INSTRUMENTS; ACOUSTICS
    • G10L—SPEECH ANALYSIS TECHNIQUES OR SPEECH SYNTHESIS; SPEECH RECOGNITION; SPEECH OR VOICE PROCESSING TECHNIQUES; SPEECH OR AUDIO CODING OR DECODING
    • G10L19/00—Speech 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
    • G10L19/04—Speech 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
    • G10L19/26—Pre-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. 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.
  • 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:
  • 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 v - 0 results in an all-pass filter, while setting v - 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, v 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. 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.
  • a postfilter which postfilter is characterized by a first and second component.
  • the first component includes a set of coefficients. These coefficients are transformed into an alternate domain set of parameters, and then operated on to provide a modified set of parameters. These are then used to provide a set of coefficients that characterize the second component.
  • Z transform (filter) coefficients that represent the first component are converted to the autocorrelation domain.
  • a spectral smoothing techr ue 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 v) polynomial.
  • Format bandwidth expansion does not change the smoothed spectral envelope.
  • the spectrally smoothed bandwidth expanded version of the A(z/v) 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
  • H(z) 1 - uz "1 , where typically 0.2 ⁇ u ⁇ 0.5.
  • Fig. 1 comprises a block diagrammatic depiction of a radio configured in accordance with the invention.
  • 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 (1 13).
  • 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.
  • 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:
  • 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 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
  • H(z) 1 - uz "1 , where typically 0.2 ⁇ u ⁇ 0.5.

Landscapes

  • 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

DIGITAL SPEECH DECODER HAVING A POSTFILTER WITH REDUCED SPECTRAL DISTORTION
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. 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:
where 0 < η < v < 1 an - — T represents the associated LPC filter. 1 - A(z)
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 v - 0 results in an all-pass filter, while setting v - 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, v 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
These needs and others are substantially met through provision of the postfilters disclosed herein. Pursuant to this invention, a postfilter can be provided, which postfilter is characterized by a first and second component. The first component includes a set of coefficients. These coefficients are transformed into an alternate domain set of parameters, and then operated on to provide a modified set of parameters. These are then used to provide a set of coefficients that characterize the second component. In one embodiment, Z transform (filter) coefficients that represent the first component are converted to the autocorrelation domain. A spectral smoothing techr ue 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 v) polynomial. Format bandwidth expansion does not change the smoothed spectral envelope. Thus, the spectrally smoothed bandwidth expanded version of the A(z/v) 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
H(z) = 1 - uz"1 , where typically 0.2 < u < 0.5.
Brief Description of the Drawings
Fig. 1 comprises a block diagrammatic depiction of a radio configured in accordance with the invention.
Best Mode For Parrying Qut 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 (1 13).
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:
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. δ
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
H(z) = 1 - uz"1, where typically 0.2 < u < 0.5.

Claims

Claims
1. A method for providing a filter characterized by a first component and a second component, comprising the steps of:
A) providing a first component having a first set of coefficients; characterized further by the steps of:
B) transforming at least some of the first set of coefficients into an alternate domain set of parameters;
C) operating on the alternate domain set of parameters to provide a modified first set of coefficients; D) using the modified first set of coefficients to provide the second component.
2. A method for substantially minimizing time variant spectral tilt in a speech synthesis postfilter having a first component and a second component, comprising the steps of: A) providing information regarding synthesized speech to be filtered;
B) providing the first component as a function, at least in part, of the information; characterized further by the steps of: C) transforming one of: at least part of the information; and at least part of the first component into an alternate domain set of parameters;
D) operating on the alternate domain set of parameters to provide a set of coefficients;
E) using the set of coefficients to provide the second component.
3. A method for characterizing a speech synthesis postfilter having a first component and a second component, comprising the steps of:
A) providing information regarding synthesized speech to be filtered;
B) providing the first component as a function, at least in part, of the information; characterized further by the steps of:
C) transforming one of: at least part of the information; and at least part of the first component into an alternate domain set of parameters;
D) operating on the alternate domain set of parameters to provide a set of coefficients; E) using the set of coefficients to provide the second component.
4. A method for producing a synthesized speech signal, comprising the steps of:
A) providing an excitation signal to an LPC filter;
B) providing from the LPC 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; characterized further by the steps of:
E) transforming at least some of the first set of coefficients into an alternate domain set of parameters;
F) operating on the alternate 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.
5. The method of claim 4, wherein the LPC filter is at least partially defined by the expression:
1
1 - A(z)
6. The method of claim 5, wherein the first component of the speech synthesis postfilter is of the form
1 - A($) as represented in Z transform notation.
The method of claim 6, wherein v « 0.8.
8. The method of claim 4, and further including the step of: I) filtering the synthesized speech signal in a post emphasis filter substantially defined, in Z transform notation, as:
H(z) = 1 - uz -1 where 0.2 < u < 0.5.
9. A method for producing a synthesized speech signal, comprising the steps of:
A) receiving an RF signal that includes coded speech information; B) recovering from the coded speech information an excitation signal;
C) providing the excitation signal to an LPC filter;
D) providing from the LPC filter a synthesized speech signal; E) providing a speech synthesis postfilter that requires a first component and a second component; F) providing a first component for use by the speech synthesis postfilter that includes a first set of coefficients; characterized further by the steps of: G) transforming at least some of the first set of coefficients into an alternate domain set of parameters; H) operating on the alternate domain set of parameters to provide a modified first set of coefficients; I) using the modified first set of coefficients to provide the second component for use by the speech synthesis postfilter;
J) 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.
10. The method of claim 9, wherein the LPC filter is at least partially defined by the expression:
1
1 - A(z)
11. The method of claim 9, wherein the first component of the speech synthesis postfilter is of the form as represented in Z transform notation.
12. The method of claim 11 , wherein v = 0.8.
13. The method of claim 9, and further including the step of: I) filtering the synthesized speech signal in a post emphasis filter substantially defined, in Z transform notation, as:
H(z) = 1 - uz -1 where 0.2 < u ≤ 0.5.
14. The method of claim 1 , 2, 3, 4, or 9 wherein the step of operating includes the step of multiplying.
15. The method of claim 1 , 2, 3, 4, or 9 wherein the alternate domain set of parameters are auto-correlation domain parameters.
EP90913916A 1989-10-17 1990-09-17 Digital speech decoder having a postfilter with reduced spectral distortion Expired - Lifetime EP0570362B1 (en)

Applications Claiming Priority (3)

Application Number Priority Date Filing Date Title
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

Publications (3)

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

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JP (1) JP3158434B2 (en)
CN (1) CN1078371C (en)
AT (1) ATE177867T1 (en)
AU (1) AU635342B2 (en)
DE (1) DE69033011T2 (en)
ES (1) ES2131498T3 (en)
WO (1) WO1991006093A1 (en)

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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

Citations (1)

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Publication number Priority date Publication date Assignee Title
EP0294020A2 (en) * 1987-04-06 1988-12-07 Voicecraft, Inc. Vector adaptive coding method for speech and audio

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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
US4817157A (en) * 1988-01-07 1989-03-28 Motorola, Inc. Digital speech coder having improved vector excitation source

Patent Citations (1)

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Publication number Priority date Publication date Assignee Title
EP0294020A2 (en) * 1987-04-06 1988-12-07 Voicecraft, Inc. Vector adaptive coding method for speech and audio

Non-Patent Citations (2)

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Title
ADVANCES IN SPEECH CODING-IEEE WORKSHOP ON SPEECH CODING FOR TELECOMMUNICATIONS 1991, DORDRECHT NL-VANCOUVER CANADA pages 69 - 79 GERSON, JASIUK 'Vector sum excited linear prediction' *
See also references of WO9106093A1 *

Also Published As

Publication number Publication date
EP0570362A4 (en) 1993-07-01
DE69033011D1 (en) 1999-04-22
AU635342B2 (en) 1993-03-18
WO1991006093A1 (en) 1991-05-02
JPH05500573A (en) 1993-02-04
DE69033011T2 (en) 2001-10-04
ES2131498T3 (en) 1999-08-01
AU6411490A (en) 1991-05-16
ATE177867T1 (en) 1999-04-15
EP0570362B1 (en) 1999-03-17
CN1051101A (en) 1991-05-01
CN1078371C (en) 2002-01-23
JP3158434B2 (en) 2001-04-23

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