US20010001320A1 - Method and device for speech coding - Google Patents

Method and device for speech coding Download PDF

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Publication number
US20010001320A1
US20010001320A1 US09/725,345 US72534500A US2001001320A1 US 20010001320 A1 US20010001320 A1 US 20010001320A1 US 72534500 A US72534500 A US 72534500A US 2001001320 A1 US2001001320 A1 US 2001001320A1
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speech
zero
differ
vector elements
encoding
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Stefan Heinen
Wen Xu
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    • H—ELECTRICITY
    • H04—ELECTRIC COMMUNICATION TECHNIQUE
    • H04L—TRANSMISSION OF DIGITAL INFORMATION, e.g. TELEGRAPHIC COMMUNICATION
    • H04L1/00—Arrangements for detecting or preventing errors in the information received
    • H04L1/004—Arrangements for detecting or preventing errors in the information received by using forward error control
    • H04L1/0056—Systems characterized by the type of code used
    • H04L1/0057—Block codes
    • 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
    • G10L19/005—Correction of errors induced by the transmission channel, if related to the coding algorithm
    • 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
    • G10L19/08—Determination or coding of the excitation function; Determination or coding of the long-term prediction parameters
    • G10L19/10—Determination or coding of the excitation function; Determination or coding of the long-term prediction parameters the excitation function being a multipulse excitation
    • 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
    • G10L19/16—Vocoder architecture
    • G10L19/18—Vocoders using multiple modes
    • 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
    • G10L19/002—Dynamic bit allocation
    • 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
    • G10L2019/0001—Codebooks
    • G10L2019/0007—Codebook element generation
    • G10L2019/0008—Algebraic codebooks

Definitions

  • the invention lies in the communications field. More specifically, the invention relates to methods and devices for speech coding in which the speech signal is encoded by a combination of speech parameters and excitation signals, in particular on the CELP (coded excited linear predictive) principle.
  • CELP coded excited linear predictive
  • Source signals or source information such as voice, sound, picture, and video signals almost always contain statistical redundancy, that is redundant information. This redundancy can be greatly reduced by source encoding, so that efficient transmission or storage of the source signal is made possible. This reduction in redundancy eliminates, prior to transmission, redundant signal contents that are based on the prior knowledge of, for example, statistical parameters of the signal variation.
  • the bit rate of the source-encoded information is also referred to as the encoding rate or source bit rate. Following transmission, in the source decoding, these component parts are once more added to the signal, so that objectively and/or subjectively there is no ascertainable loss in quality.
  • a method of encoding and/or corresponding decoding which may also comprise source encoding and/or channel encoding is also referred to as a speech codec.
  • AMR adaptive multirate
  • speech codecs with variable source bit rate or variable encoding rate are to achieve fixed network quality of the speech under different channel conditions and to ensure optimum distribution of the channel capacity with certain network parameters taken into account.
  • the object of the invention is to provide a method and a device for speech coding which overcome the above-noted deficiencies and disadvantages of the prior art devices and methods of this kind, and which make it possible to encode speech signals robustly to resist transmission errors and with relatively little expenditure.
  • a speech coding method which comprises:
  • the speech parameters or the excitation signals are formed from the speech signals on the CELP principle.
  • the positions of the vector elements that differ from zero are encoded together to form an index value.
  • a device for speech coding includes a processor unit receiving speech signals and being configured to:
  • the processor unit is programmed to obtain the speech parameters and excitation signals from the speech signals on the CELP principle.
  • the processor unit is programmed to encode the positions of the vector elements that differ from zero together to form an index value.
  • the invention is premised on the idea of encoding positions of certain predetermined vector elements which differ from zero and the algebraic signs of these vector elements separately from one another for the encoding of vectors for describing speech parameters or excitation signals.
  • the invention relates quite generally to methods for speech coding in which the speech signal is encoded by a combination of speech parameters and excitation signals.
  • the speech parameters include parameters or characteristic variables of a statistical model on which the speech production is based, for example LPC or LTP filter coefficients, and the excitation signals are signals of the exciting processes of this model. These processes may be modeled either statistically or deterministically. Examples of statistical modeling are vocoder methods in which the excitation signals are generated by noise sources. In deterministic modeling, the excitation signals are obtained with the aid of the underlying model from the speech signal and are quantized. Examples of this are RPE/LTP (GSM Full Rate Codec), VSELP (GSM Half Rate Codec) and ACELP (GSM Enhanced Full Rate Codec).
  • FIG. 1 is a block diagram of essential elements in a telecommunications transmission chain
  • FIG. 2 is a block diagram of an AMR encoder based on the CELP principle
  • FIG. 3 is a schematic block diagram of a processor unit.
  • a source Q which generates source signals qs, which are compressed by a source encoder QE, such as the GSM full rate speech coder, to form symbol sequences comprising symbols.
  • a source encoder QE such as the GSM full rate speech coder
  • the source signals qs generated by the source Q are divided into blocks (for example time frames) and these are processed separately.
  • the source encoder QE generates quantized parameters (for example speech parameters or speech coefficients), which are also referred to hereafter as symbols of a symbol sequence, and which reflect the properties of the source in the current block in a certain way (for example spectrum of the speech in the form of filter coefficients, amplitude factors, excitation vectors). After the quantization, these symbols have a certain symbol value.
  • quantized parameters for example speech parameters or speech coefficients
  • symbols of a symbol sequence for example spectrum of the speech in the form of filter coefficients, amplitude factors, excitation vectors.
  • the symbols of the symbol sequence or the corresponding symbol values are mapped by a binary mapping (allocation specification), which is frequently described as part of the source encoding QE, onto a sequence of binary code words, which in each case have a plurality of bit positions. If these binary code words are, for example, further processed one after the other as a sequence of binary code words, a sequence of source-encoded bit positions which may be embedded in a frame structure is produced. After source encoding carried out in this way, source bits or data bits db with a source bit rate (encoding rate) dependent on the type of source encoding are thus obtained in a structured form in the frame.
  • a binary mapping allocation specification
  • codebook is to be understood here as describing a table with all the quantization representatives.
  • the entries of the table may be both scalar and vectorial quantities.
  • Scalar codebooks can be used for example for the quantization of amplitude factors, since these are generally scalar quantities.
  • vectorial codebooks are the quantization of LSF (line spectrum frequencies) and the quantization of the stochastic excitation.
  • FIG. 2 there is shown a basic representation a special variant of a source encoder.
  • the exemplary embodiment is a speech coder, namely an AMR encoder based on a CELP (coded excited linear predictive) principle.
  • CELP coded excited linear predictive
  • the CELP principle concerns a method of analysis by synthesis.
  • a filter structure obtained from the current portion of speech is excited by excitation vectors (code vectors) taken one after the other from a codebook.
  • the output signal of the filter is compared by means of a suitable error criterion with the current portion of speech and the error-minimizing excitation vector is selected.
  • the representation of the filter structure and the position number of the selected excitation vector are transmitted to the receiver.
  • a specific variant of a CELP method uses an algebraic codebook, which is often also referred to as a sparse algebraic code. It is a multipulse codebook which is filled with binary (+/ ⁇ 1) or ternary pulses (0, +/ ⁇ 1). Within the excitation vectors, only a few positions are respectively occupied by pulses. After the selection of the positions, the entire vector is weighted with an amplitude factor.
  • a codebook of this type has several advantages. On the one hand, it does not take up any storage space, since the positions allowed for the pulses are determined by an algebraic computing rule, on the other hand it can be searched through very efficiently for the best pulse positions on account of the way it is structured.
  • a configurational variant of a conventional CELP encoder is first described below with reference to FIG. 2.
  • a target signal to be approximated is reproduced by searching through two codebooks.
  • the adaptive codebook (a 2 ) changes according to the speech signal, while the stochastic codebook (a 4 ) is invariant over time.
  • the search for the best excitation code vectors takes place not by searching jointly, i.e.
  • the codebooks simultaneously, in the codebooks, as would be necessary for an optimum selection of the excitation code vectors, but, for expenditure-related reasons, by initially searching through the adaptive codebook (a 2 ). Once the excitation code vector that is best according to the error criterion has been found, its contribution to the reconstructed target signal is subtracted from the target vector (target signal) and the part of the target signal still to be reconstructed by means of a vector from the stochastic codebook (a 4 ) is obtained.
  • the search in the individual codebooks takes place on the same principle. In both cases, the quotient from the square of the correlation of the filtered excitation code vector with the target vector and the energy of the filtered target vector is computed for all the excitation code vectors.
  • That excitation code vector which maximizes this quotient is regarded as the best excitation code vector, which minimizes the error criterion (a 5 ).
  • the preceding error weighting (a 6 ) weights the error according to the characteristics of human hearing.
  • the position of the found excitation code vector within the excitation codebook is transmitted to the decoder.
  • the computation of the afore-mentioned quotient has the effect of implicitly determining the correct (codebook) amplitude factor (amplification 1 , amplification 2 ) for each excitation code vector.
  • the quality-reducing influence of the sequentially performed codebook search can be reduced by a joint optimization of the amplification. This involves re-specifying the original target vector and computing the best amplifications matching the excitation code vectors now selected. These amplifications usually differ slightly from those which were determined during the codebook search.
  • each candidate vector can be individually filtered (a 3 ) and compared with the target signal for finding the best excitation code vector.
  • filter parameters are converted into binary signals and, embedded in a fixed structure, are transmitted in frames.
  • the filter parameters may be LPC (linear predictive coding) coefficients, LTP (long term prediction) indices, or LTP (long term prediction) amplitude factors.
  • the LPC residual signal or excitation signal is vectorially quantized.
  • an algebraic codebook is used.
  • the group of quantization representatives is not explicitly present in a table, but instead the various representatives can be determined from an index value with the aid of an algebraic computing rule. This additionally has complexity-related advantages in the codebook search.
  • the algebraic computing rule for the determination of the excitation code vectors from an index value uses a division of the vector space into so-called tracks. Within one track (vector), only components (vector elements) which lie on a track-specific grid can assume values which differ from zero.
  • Positions which differ from zero are referred to as pulse positions.
  • the pulses may have either a binary ( ⁇ 1/+1) or ternary ( ⁇ 1/0/+1) value range.
  • the superposing of individual tracks finally supplies the excitation code vector.
  • a track (vector) is consequently described by pulses (vector elements which differ from zero). It is possible for the pulses to be described by their position (vector element index) and their algebraic sign. The total set of possible pulse position combinations is described with the aid of an overall index.
  • the code word length required for encoding the excitation vector found is made up of the number of bits required for encoding the pulse positions and algebraic signs. If only one pulse is set per track, not only the number of bits for the encoding of its position but also a further bit for the encoding of its algebraic sign are required.
  • the sign information of a track must allow itself to be transmitted by deliberate changing of the encoding sequence of the pulse positions. If, for instance, a codebook which provides four pulses per track were drawn up, the permutation of the encoding sequence alone would be sufficient for the sign encoding; an additional sign bit would not be required.
  • the invention describes a significantly more robust sign encoding.
  • the overall set of possible pulse positions is addressed by a suitable algebraic method with the aid of a single index.
  • the algebraic signs of the pulses are respectively encoded with a bit.
  • the improved method may be explained by the example of the algebraic codebook for the rate 9.5 kbits/s.
  • this codebook two pulses are set to 14 possible positions.
  • one bit is required for the first pulse sign and 4 bits are required for each of the two pulse positions, that is a total of 9 bits.
  • the different encoding rates mean that different codec modes generally have different frame sizes, and therefore also different structures in which the bit positions serving for describing the filter parameters, amplitude factors or excitation code vectors are embedded.
  • the changing of the encoding rate may be realized by a corresponding changing of the number of bit positions for describing an excitation code vector taken from a stochastic codebook.
  • Switching over of the codec modes consequently leads, as a result of switching over to a stochastic codebook corresponding to the new codec mode, to the selection of excitation code vectors contained in this codebook, for the description of which a correspondingly changed number of bit positions is required. Consequently, there are different stochastic codebooks available according to the number of different codec modes.
  • a processor unit PE which may be contained in particular in a communication device, such as a base station BS or mobile station MS.
  • the unit PE contains a control device STE, which essentially comprises a program-controlled microcontroller, and a processing device VE, which comprises a processor, in particular a digital signal processor, which can both gain writing and reading access to memory chips SPE.
  • the microcontroller controls and monitors all the major elements and functions of a functional unit which includes the processor unit PE.
  • the digital signal processor, part of the digital signal processor or a specific processor is responsible for carrying out the speech coding or speech decoding.
  • the selection of a speech codec may also be performed by the microcontroller or the digital signal processor itself.
  • An input/output interface I/O serves for the input/output of useful or control data, for example to a man-machine interface MMI, which may include a keyboard and/or a display.
  • MMI man-machine interface
  • the individual elements of the processor unit may be connected to one another by a digital bus system BUS.

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  • Engineering & Computer Science (AREA)
  • Signal Processing (AREA)
  • Physics & Mathematics (AREA)
  • Health & Medical Sciences (AREA)
  • Audiology, Speech & Language Pathology (AREA)
  • Human Computer Interaction (AREA)
  • Computational Linguistics (AREA)
  • Acoustics & Sound (AREA)
  • Multimedia (AREA)
  • Computer Networks & Wireless Communication (AREA)
  • Compression, Expansion, Code Conversion, And Decoders (AREA)
  • Error Detection And Correction (AREA)
  • Transmission Systems Not Characterized By The Medium Used For Transmission (AREA)
US09/725,345 1998-05-29 2000-11-29 Method and device for speech coding Abandoned US20010001320A1 (en)

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EP98109868.4 1998-05-29
EP98109868 1998-05-29
PCT/EP1999/003766 WO1999063522A1 (de) 1998-05-29 1999-05-31 Verfahren und anordnung zur sprachcodierung

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Cited By (10)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
US20050065788A1 (en) * 2000-09-22 2005-03-24 Jacek Stachurski Hybrid speech coding and system
US20050228653A1 (en) * 2002-11-14 2005-10-13 Toshiyuki Morii Method for encoding sound source of probabilistic code book
US20100174534A1 (en) * 2009-01-06 2010-07-08 Koen Bernard Vos Speech coding
US20100174538A1 (en) * 2009-01-06 2010-07-08 Koen Bernard Vos Speech encoding
US20100174547A1 (en) * 2009-01-06 2010-07-08 Skype Limited Speech coding
US20100174541A1 (en) * 2009-01-06 2010-07-08 Skype Limited Quantization
US20100174532A1 (en) * 2009-01-06 2010-07-08 Koen Bernard Vos Speech encoding
US20100174537A1 (en) * 2009-01-06 2010-07-08 Skype Limited Speech coding
US20110077940A1 (en) * 2009-09-29 2011-03-31 Koen Bernard Vos Speech encoding
US9263051B2 (en) 2009-01-06 2016-02-16 Skype Speech coding by quantizing with random-noise signal

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DE19932943A1 (de) * 1999-07-14 2001-01-18 Siemens Ag Verfahren und Vorrichtung zur Decodierung von Quellensignalen
US8219940B2 (en) * 2005-07-06 2012-07-10 Semiconductor Insights Inc. Method and apparatus for removing dummy features from a data structure
US7957701B2 (en) * 2007-05-29 2011-06-07 Alcatel-Lucent Usa Inc. Closed-loop multiple-input-multiple-output scheme for wireless communication based on hierarchical feedback
US8207875B2 (en) * 2009-10-28 2012-06-26 Motorola Mobility, Inc. Encoder that optimizes bit allocation for information sub-parts
US9275644B2 (en) * 2012-01-20 2016-03-01 Qualcomm Incorporated Devices for redundant frame coding and decoding
US9700276B2 (en) * 2012-02-28 2017-07-11 Siemens Healthcare Gmbh Robust multi-object tracking using sparse appearance representation and online sparse appearance dictionary update
EP3111560B1 (en) * 2014-02-27 2021-05-26 Telefonaktiebolaget LM Ericsson (publ) Method and apparatus for pyramid vector quantization indexing and de-indexing of audio/video sample vectors

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US5247579A (en) * 1990-12-05 1993-09-21 Digital Voice Systems, Inc. Methods for speech transmission
FI94810C (fi) * 1993-10-11 1995-10-25 Nokia Mobile Phones Ltd Menetelmä huonon GSM-puhekehyksen tunnistamiseksi
US5970444A (en) * 1997-03-13 1999-10-19 Nippon Telegraph And Telephone Corporation Speech coding method
US6161089A (en) * 1997-03-14 2000-12-12 Digital Voice Systems, Inc. Multi-subframe quantization of spectral parameters

Cited By (22)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
US20050065788A1 (en) * 2000-09-22 2005-03-24 Jacek Stachurski Hybrid speech coding and system
US7363219B2 (en) * 2000-09-22 2008-04-22 Texas Instruments Incorporated Hybrid speech coding and system
US20050228653A1 (en) * 2002-11-14 2005-10-13 Toshiyuki Morii Method for encoding sound source of probabilistic code book
US7577566B2 (en) * 2002-11-14 2009-08-18 Panasonic Corporation Method for encoding sound source of probabilistic code book
US8463604B2 (en) 2009-01-06 2013-06-11 Skype Speech encoding utilizing independent manipulation of signal and noise spectrum
US8433563B2 (en) 2009-01-06 2013-04-30 Skype Predictive speech signal coding
US20100174547A1 (en) * 2009-01-06 2010-07-08 Skype Limited Speech coding
US20100174541A1 (en) * 2009-01-06 2010-07-08 Skype Limited Quantization
US20100174532A1 (en) * 2009-01-06 2010-07-08 Koen Bernard Vos Speech encoding
US20100174537A1 (en) * 2009-01-06 2010-07-08 Skype Limited Speech coding
US10026411B2 (en) 2009-01-06 2018-07-17 Skype Speech encoding utilizing independent manipulation of signal and noise spectrum
US8392178B2 (en) 2009-01-06 2013-03-05 Skype Pitch lag vectors for speech encoding
US8396706B2 (en) * 2009-01-06 2013-03-12 Skype Speech coding
US20100174538A1 (en) * 2009-01-06 2010-07-08 Koen Bernard Vos Speech encoding
US9530423B2 (en) 2009-01-06 2016-12-27 Skype Speech encoding by determining a quantization gain based on inverse of a pitch correlation
US20100174534A1 (en) * 2009-01-06 2010-07-08 Koen Bernard Vos Speech coding
US8639504B2 (en) 2009-01-06 2014-01-28 Skype Speech encoding utilizing independent manipulation of signal and noise spectrum
US8670981B2 (en) 2009-01-06 2014-03-11 Skype Speech encoding and decoding utilizing line spectral frequency interpolation
US8849658B2 (en) 2009-01-06 2014-09-30 Skype Speech encoding utilizing independent manipulation of signal and noise spectrum
US9263051B2 (en) 2009-01-06 2016-02-16 Skype Speech coding by quantizing with random-noise signal
US8452606B2 (en) 2009-09-29 2013-05-28 Skype Speech encoding using multiple bit rates
US20110077940A1 (en) * 2009-09-29 2011-03-31 Koen Bernard Vos Speech encoding

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CN1134764C (zh) 2004-01-14
US20020007473A1 (en) 2002-01-17
EP1080464B1 (de) 2003-01-29
DE59913231D1 (de) 2006-05-11
DE59904164D1 (de) 2003-03-06
US6567949B2 (en) 2003-05-20
CN1143470C (zh) 2004-03-24
EP1093690B1 (de) 2006-03-15
EP1080464A1 (de) 2001-03-07
EP1093690A1 (de) 2001-04-25
CN1312937A (zh) 2001-09-12
WO1999063522A1 (de) 1999-12-09
CN1303508A (zh) 2001-07-11
WO1999063520A1 (de) 1999-12-09
WO1999063523A1 (de) 1999-12-09

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