EP0774750A2 - Détermination des fréquences du spectre de raies pour utilisation dans un radiotéléphone - Google Patents

Détermination des fréquences du spectre de raies pour utilisation dans un radiotéléphone Download PDF

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Publication number
EP0774750A2
EP0774750A2 EP96308081A EP96308081A EP0774750A2 EP 0774750 A2 EP0774750 A2 EP 0774750A2 EP 96308081 A EP96308081 A EP 96308081A EP 96308081 A EP96308081 A EP 96308081A EP 0774750 A2 EP0774750 A2 EP 0774750A2
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EP
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Prior art keywords
polynomials
lpc
zero
line spectrum
zeros
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EP96308081A
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German (de)
English (en)
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EP0774750B1 (fr
EP0774750A3 (fr
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Vesa T. Ruoppila
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Nokia Oyj
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Nokia Mobile Phones Ltd
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    • 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
    • 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
    • G10L25/00—Speech or voice analysis techniques not restricted to a single one of groups G10L15/00 - G10L21/00
    • G10L25/03—Speech or voice analysis techniques not restricted to a single one of groups G10L15/00 - G10L21/00 characterised by the type of extracted parameters
    • G10L25/24—Speech or voice analysis techniques not restricted to a single one of groups G10L15/00 - G10L21/00 characterised by the type of extracted parameters the extracted parameters being the cepstrum

Definitions

  • This invention relates generally to speech encoding methods and apparatus and, in particular, to linear predictive coding (LPC) speech and audio coding techniques that employ a line spectrum frequency representation of an LPC filter.
  • LPC linear predictive coding
  • Linear predictive coding is a known technique for analyzing a speech signal and for characterizing the signal in terms of coefficients which are encoded, broadcast, received and decoded to recover an approximation of the original signal.
  • the parameters of a LPC filter are coded and sent as a part of the information stream.
  • the use of line spectrum frequencies is an alternative to the use of, for example, polynomial coefficients or reflection coefficients for representing the LPC filter.
  • the line spectrum frequencies have useful properties for quantization and interpolation which make them a more attractive representation than polynomial or reflection coefficients.
  • a method for determining line spectrum frequencies of a LPC filter is disclosed.
  • the predictor polynominal of the LPC filter is decomposed into symmetric and antisymmetric auxiliary polynomials, the zeros of which determine the line spectrum frequencies of the filter.
  • the line spectrum frequency representation is determined by solving the zeros of the two auxiliary polynomials. Due to the symmetry of the auxiliary polynomials, their zeros are preferably solved from two cosine series. In speech codecs this is usually done by a bisection algorithm, and by employing the definition of Chebyshev polynomials to evaluate the cosine series.
  • a potential aim of this invention is to reduce the complexity of the line spectrum frequency computation. This may be obtained by rewriting the cosine series as polynomials using explicit forms of Chebyshev polynomials. This enables an evaluation of the series by nested multiplications. Moreover, the already-computed zeros are successively eliminated from the polynomial by polynomial deflation. This procedure and the properties of the auxiliary polynomials can enable the initial values to be chosen in the zero finding algorithm such that a zero is found by only a few iterations using the zero of the other polynomial. Thus, the invention may reduce considerably the arithmetic operations required to compute the line spectrum frequencies. The method of this invention thus has the potential to be implemented with relatively low complexity, and furthermore to be accomplished using fixed-point arithmetic.
  • FIG. 1 A simplified block diagram of a speech encoder 10 employing the spectrum frequency representation of the LPC filter is presented in Fig. 1.
  • the speech encoder 10 may form a portion of a radiotelephone, such as a digital cellular user terminal or a personal communicator device.
  • An input audio signal such as a speech signal obtained from a speech transducer or microphone 5, is converted into a digital form by an analog-to-digital (A/D) converter 12.
  • A/D analog-to-digital
  • the digital output of the A/D converter is preprocessed by separating the signal into frames of convenient length, typically of the order of tens of milliseconds. It should be noted that the A/D conversion is not necessary if the signal is already in digital form. After preprocessing, the signal is applied to an LPC analysis block 14.
  • the LPC analysis produces coefficients for an LPC filter, also referred to herein as an LPC-analysis filter 16.
  • the output of the LPC analysis block 14 is transformed into a line spectrum frequency (LSF) representation in block 18.
  • LSF line spectrum frequency
  • the LSF coefficients may be quantized in block 20 and then interpolated in block 22 in order to construct a LPC analysis filter for each speech subframe.
  • four 5 millesecond subframes may be used, wherein the analysis filter is constructed separately for each subframe.
  • the coefficients of a long-term prediction (LTP) filter are searched, and the residual is generated in the block labeled LTP analysis and filtering 24.
  • LTP long-term prediction
  • the residual is encoded in the excitation encoding block 26, and the resulting encoded residual, i.e., an encoded excitation signal, is multiplexed (block 28) with the quantized LSF coefficients into a bit stream transmitted to a speech decoder (not shown) via a communication channel 30.
  • the communication channel 30 is a radio channel linking the mobile terminal to a base station (not shown) by a transmitter 32 and an antenna 34.
  • the "side information" input to the multiplexer 28 determines, for example, the operational mode of the speech coder, particularly for variable rate codecs such as QCELP. For a speech coder operated in a fixed rate mode, this input may not be required.
  • a n+1 (z) A n (z)+k n+1 z -n-1 A n (z -1 ), wherein k 1 , k 2 ,...,k n+1 are reflection coefficients.
  • the recurrence formula (2) is called the Levinson-Durbin solution to the Yule-Walker equations. It expresses the relationship between the (n+1)th and the nth degree predictor polynomials. For the purposes of this description it is assumed that all roots of the predictor polynomial A n (z) are inside the unit circle, i.e., that the predictor polynomial is minimum phase.
  • P n+1 (z) and Q n+1 (z) can be factored as follows: where ⁇ 1 , ⁇ 2 ,..., ⁇ n are the phase angles of the zeros of the polynomials such that (10) 0 ⁇ ⁇ 1 ⁇ ⁇ 2 ⁇ ⁇ n ⁇ ⁇ ⁇ 1 , ⁇ 2 ,..., ⁇ n are the line spectrum frequencies of A n (z).
  • the degree of the polynomial Q(z) is 2m Q , where
  • the symmetric polynomial Q(z) can be rewritten similarly to the form where q 1 , q 2 ,..., q mQ are the coefficients of the polynomial Q(z).
  • Kang and Fransen (“Application of line spectrum pairs to low bit rate speech encoders", Proceedings of IEEE International Conference on Acoustics, Speech, and Signal Processing, Tampa, FL, pp. 7.3.1-7.3.4, March 1984) have proposed autocorrelation based and ratio-filter based methods for finding line spectrum frequencies. However, these two methods also require an evaluation of a large number of trigonometric functions.
  • Saoudi et al. ("A new efficient algorithm to compute the LSP parameters for speech coding", Signal Processing, vol. 28, pp. 201-212, 1992) reformulated the problem. That is, they introduced an algorithm which solves line spectrum frequencies from eigenvalues of tridiagonal symmetric matrices without computing the predictor polynomial. The eigenvalues are computed by the bisection method. Saoudi et al. also compared the complexity of several algorithms introduced for computing the line spectrum frequencies. Unfortunately, the results of the comparison are not comprehensive.
  • the algorithm (22) is known to be used in speech codecs, it has several shortcomings. For example, if some zeros of the polynomials are sufficiently near each other, the algorithm has a tendency to miss zeros, since the sign change is not detected. This shortcoming can be circumvented by making the grid denser. In other words, the intervals are made sufficiently small so that two or more roots do not occur in the same interval. The definitive choice of the grid interval is always a compromise between a reliability and computational burden. That is, as the grid interval is made more dense, the overall processing burden increases as well.
  • the method successively eliminates already-found zeros from the polynomials.
  • the procedure is known as polynomial deflation, or as synthetic division in numerical analysis, see, e.g., Kincaid and Chaney.
  • polynomial deflation allows for the elimination of the sign-change detection procedure from the algorithm.
  • Another advantage is that efficient algorithms (which have better convergence properties than the bisection method) can be exploited together with the property (21) to locate the zeros. For example, when zeros are computed by Newton's method, the algorithm is guaranteed to find all line spectrum frequencies if sufficient numerical accuracy is used.
  • the polynomials (25) and (26) can then be evaluated effectively by the procedure of nested multiplications, known also as Horner's algorithm (see, for example, Kincaid and Cheney, Numerical Analysis: Mathematics of Scientific Computing , Brooks/Cole Publishing Company, 1991).
  • step (d) of algorithm (29) i.e., in the block Solve the last zero in Fig. 2.
  • the initial values can be chosen differently.
  • Figs. 4A-4D illustrate the progress of the technique (algorithm (29)) employing polynomial deflation.
  • the zeros of the polynomials R(x) and S(x) corresponding to A 10 (z) are presented in Fig. 4A by crosses (x) and circles (o), respectively.
  • (x - x 1 ) is divided from the polynomial R(x).
  • the polynomial R(x) after the first deflation is shown in Fig. 4C.
  • the search is continued from S(x) using x 1 as an initial value.
  • Fig. 4D illustrates the polynomial R(x) after two deflations.
  • the is invention teaches in one aspect a method for determining line spectrum frequencies of a linear predictive coder (LPC) filter that is expressed as symmetric and antisymmetric polynomials, the zeros of which determine the line spectrum frequencies of the LPC filter.
  • the method includes the steps of (a) expressing the polynomials using explicit forms of Chebyshev polynomials; (b) interatively solving a zero of a first of the polynomials using a zero of the other one of the polynomials; and (c) successively eliminating zeros from the polynomials by polynomial division so as to determine the line spectrum frequencies.
  • the first polynomial can be either the symmetric or the antisymmetric polynomial, in which case the other polynomial is then the antisymmetric or the symmetric polynomial, respectively.
  • any of the zeros of the first polynomial can be solved using any of the zeros of the other polynomial.
  • the immittance spectrum frequency representation of the LPC filter is based on a similar polynomial decomposition of a predictor polynomial as the line spectrum frequency representation.
  • the symmetric polynomial P n (z) and the antisymmetric polynomial Q n (z) also have similar properties as polynomials (3) and (4).
  • the roots of P n (z) and Q n (z) are on the unit circle, and they are simple and separate from each other.
  • phase angles ⁇ 1 , ⁇ 2 , ..., ⁇ n-1 and the parameter k give an unique parametrization for the LPC filter.
  • the properties of the immittance spectrum frequencies and their relation to line spectrum frequencies have been discussed in more detail by Bistritz and Peller.
  • polynomials (35) and (36) are not identical to the polynomials defined in (3) and (4).
  • the degrees of the symmetric polynomials P(z) and Q(z) defined in (35) and (36) are 2m p and 2m Q , respectively, where and
  • Equations (38) and (39) can be written to the form (25) and (26) by proceeding as described above.
  • the immittance spectrum frequencies ⁇ 1 , ⁇ 2 , ..., ⁇ n-1 can be solved in accordance with this invention by the techniques summarized in the algorithm (29).
  • the audio encoder can be used in a PC or workstation connected to a network.
  • the communication channel 30 may then be a wired network (e.g., Internet).

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  • Engineering & Computer Science (AREA)
  • Physics & Mathematics (AREA)
  • Signal Processing (AREA)
  • Health & Medical Sciences (AREA)
  • Audiology, Speech & Language Pathology (AREA)
  • Human Computer Interaction (AREA)
  • Computational Linguistics (AREA)
  • Acoustics & Sound (AREA)
  • Multimedia (AREA)
  • Compression, Expansion, Code Conversion, And Decoders (AREA)
  • Mobile Radio Communication Systems (AREA)
  • Noise Elimination (AREA)
  • Monitoring And Testing Of Transmission In General (AREA)
EP19960308081 1995-11-15 1996-11-07 Détermination des fréquences du spectre de raies pour utilisation dans un radiotéléphone Expired - Lifetime EP0774750B1 (fr)

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US678795P 1995-11-15 1995-11-15
US6787 1995-11-15
US73582796A 1996-10-23 1996-10-23
US735827 1996-10-23

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EP0774750A2 true EP0774750A2 (fr) 1997-05-21
EP0774750A3 EP0774750A3 (fr) 1998-08-05
EP0774750B1 EP0774750B1 (fr) 2003-02-05

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Cited By (4)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
EP0989544A1 (fr) * 1998-09-22 2000-03-29 Koninklijke Philips Electronics N.V. Dispositif et procédé de filtrage d'un signal de parole, récepteur et système de communications téléphonique
JP2017513048A (ja) * 2014-03-07 2017-05-25 フラウンホーファー−ゲゼルシャフト・ツール・フェルデルング・デル・アンゲヴァンテン・フォルシュング・アインゲトラーゲネル・フェライン 情報符号化のコンセプト
EP3349212A1 (fr) * 2017-01-13 2018-07-18 Nokia Technologies Oy Procede de determination de frequences spectrales lineaires
CN110070894A (zh) * 2019-03-26 2019-07-30 天津大学 一种改进的多个病理单元音识别方法

Citations (2)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
EP0440335A2 (fr) * 1990-02-01 1991-08-07 Psion Plc Codage de la parole
GB2254760A (en) * 1991-01-14 1992-10-14 Ericsson Telefon Ab L M "lpc speech encoding"

Patent Citations (2)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
EP0440335A2 (fr) * 1990-02-01 1991-08-07 Psion Plc Codage de la parole
GB2254760A (en) * 1991-01-14 1992-10-14 Ericsson Telefon Ab L M "lpc speech encoding"

Non-Patent Citations (6)

* Cited by examiner, † Cited by third party
Title
BISTRITZ Y ET AL: "IMMUTTANCE SPECTRAL PAIRS (ISP) FOR SPEECH ENCODING" SPEECH PROCESSING, MINNEAPOLIS, APR. 27 - 30, 1993, vol. VOL. 2, no. -, 27 April 1993, INSTITUTE OF ELECTRICAL AND ELECTRONICS ENGINEERS, pages II-09-12, XP000427712 *
GOALIC A ET AL: "AN INTRINSICALLY RELIABLE AND FAST ALGORITHM TO COMPUTE THE LINE SPECTRUM PAIRS (LSP) IN LOW BIT RATE CELP CODING" PROCEEDINGS OF THE INTERNATIONAL CONFERENCE ON ACOUSTICS, SPEECH, AND SIGNAL PROCESSING (ICASSP), DETROIT, MAY 9 - 12, 1995 SPEECH, vol. VOL. 1, 9 May 1995, INSTITUTE OF ELECTRICAL AND ELECTRONICS ENGINEERS, pages 728-731, XP000658097 *
JAU-HUNG CHEN ET AL: "A two-level method using a decimation-in-degree algorithm for the computation of the LSP frequencies" APCCAS 94. 1994 IEEE ASIA-PACIFIC CONFERENCE ON CIRCUITS AND SYSTEMS (CAT. NO.94TH8029), PROCEEDINGS OF APCCAS 94 - 1994 ASIA PACIFIC CONFERENCE ON CIRCUITS AND SYSTEMS, TAIPEI, TAIWAN, 5-8 DEC. 1994, ISBN 0-7803-2440-4, 1994, NEW YORK, NY, USA, IEEE, USA, pages 400-405, XP002066602 *
KABAL P ET AL: "The computation of line spectral frequencies using Chebyshev polynomials" IEEE TRANSACTIONS ON ACOUSTICS, SPEECH AND SIGNAL PROCESSING, DEC. 1986, USA, vol. ASSP-34, no. 6, ISSN 0096-3518, pages 1419-1426, XP002066603 *
SAOUDI S ET AL: "A NEW EFFICIENT ALGORITHM TO COMPUTE THE LSP PARAMETERS FOR SPEECH CODING" SIGNAL PROCESSING EUROPEAN JOURNAL DEVOTED TO THE METHODS AND APPLICATIONS OF SIGNAL PROCESSING, vol. 28, no. 2, 1 August 1992, pages 201-212, XP000363663 *
SOONG F K ET AL: "LINE SPECTRUM PAIR (LSP) AND SPEECH DATA COMPRESSION" INTERNATIONAL CONFERENCE ON ACOUSTICS, SPEECH & SIGNAL PROCESSING ICASSP, SAN DIEGO, MARCH 19 - 21, 1984, vol. VOL. 1, no. CONF. 9, 19 March 1984, INSTITUTE OF ELECTRICAL AND ELECTRONICS ENGINEERS, pages 1.10.1-1.10.4, XP000560468 *

Cited By (9)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
EP0989544A1 (fr) * 1998-09-22 2000-03-29 Koninklijke Philips Electronics N.V. Dispositif et procédé de filtrage d'un signal de parole, récepteur et système de communications téléphonique
JP2017513048A (ja) * 2014-03-07 2017-05-25 フラウンホーファー−ゲゼルシャフト・ツール・フェルデルング・デル・アンゲヴァンテン・フォルシュング・アインゲトラーゲネル・フェライン 情報符号化のコンセプト
US10403298B2 (en) 2014-03-07 2019-09-03 Fraunhofer-Gesellschaft Zur Foerderung Der Angewandten Forschung E.V. Concept for encoding of information
US11062720B2 (en) 2014-03-07 2021-07-13 Fraunhofer-Gesellschaft Zur Foerderung Der Angewandten Forschung E.V. Concept for encoding of information
US11640827B2 (en) 2014-03-07 2023-05-02 Fraunhofer-Gesellschaft Zur Foerderung Der Angewandten Forschung E.V. Concept for encoding of information
EP3349212A1 (fr) * 2017-01-13 2018-07-18 Nokia Technologies Oy Procede de determination de frequences spectrales lineaires
WO2018130742A1 (fr) * 2017-01-13 2018-07-19 Nokia Technologies Oy Procédé de détermination de fréquences de spectres linéaires
CN110070894A (zh) * 2019-03-26 2019-07-30 天津大学 一种改进的多个病理单元音识别方法
CN110070894B (zh) * 2019-03-26 2021-08-03 天津大学 一种改进的多个病理单元音识别方法

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Publication number Publication date
DE69626088D1 (de) 2003-03-13
EP0774750B1 (fr) 2003-02-05
DE69626088T2 (de) 2003-10-09
EP0774750A3 (fr) 1998-08-05

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