EP1212750A1 - Vocodeur de type vselp - Google Patents

Vocodeur de type vselp

Info

Publication number
EP1212750A1
EP1212750A1 EP00960391A EP00960391A EP1212750A1 EP 1212750 A1 EP1212750 A1 EP 1212750A1 EP 00960391 A EP00960391 A EP 00960391A EP 00960391 A EP00960391 A EP 00960391A EP 1212750 A1 EP1212750 A1 EP 1212750A1
Authority
EP
European Patent Office
Prior art keywords
speech
basis vectors
generating
speech coder
codebook
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.)
Withdrawn
Application number
EP00960391A
Other languages
German (de)
English (en)
Inventor
Jonathan Alastair Gibbs
Dominic Chan
Mark A. 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 UK Ltd
Original Assignee
Motorola Ltd
Priority date (The priority date 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 date listed.)
Filing date
Publication date
Application filed by Motorola Ltd filed Critical Motorola Ltd
Publication of EP1212750A1 publication Critical patent/EP1212750A1/fr
Withdrawn legal-status Critical Current

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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
    • G10L19/08—Determination or coding of the excitation function; Determination or coding of the long-term prediction parameters
    • G10L19/12—Determination or coding of the excitation function; Determination or coding of the long-term prediction parameters the excitation function being a code excitation, e.g. in code excited linear prediction [CELP] vocoders
    • G10L19/125—Pitch excitation, e.g. pitch synchronous innovation CELP [PSI-CELP]

Definitions

  • This invention relates to speech coding techniques.
  • the invention is applicable to, but not limited to, speech codecs and, in particular, to methods of utilising speech codecs in radio communications systems.
  • voice communications systems such as the TErrestrial Trunked RAdio (TETRA) system for private mobile radio users, use speech processing units to encode and decode speech patterns.
  • TETRA TErrestrial Trunked RAdio
  • the speech encoder converts the analogue speech pattern into a suitable digital format for transmission and the speech decoder converts a received digital speech signal into an appropriate analog speech pattern.
  • the primary objective in the use of speech coding techniques is to reduce the occupied capacity of the speech patterns as much as possible, by use of compression techniques, without losing fidelity of speech signals.
  • Speech coding typically uses speech production modelling techniques to compress pulse code modulation (PCM) speech signals into bit-rates that are suitable for different kinds of bandwidth-limited applications such as speech communication systems or voice storage systems.
  • PCM pulse code modulation
  • the basic speech production model that is commonly used in speech coding algorithms, uses linear predictive coding (LPC).
  • LPC linear predictive coding
  • the LPC filter models the combined effect of the glottal pulse model, the vocal tract and the lip radiation.
  • voiced speech the voiced excitation, which consists of a pulse train separated by the pitch duration T, is used as an input signal to the LPC filter.
  • a Gaussian noise source is used as the LPC filter input excitation.
  • Advances in speech coding development led to the introduction of Analysis by Synthesis technique used in CELP (Code Excited Linear Prediction) such as (Algebraic Code Excited Linear Prediction).
  • the present invention generally relates to digital speech coding at low data (bit) rates, and more particularly, is directed to an improved method for coding excitation information for such code-excited linear predictive (CELP) speech coders.
  • CELP code-excited linear predictive
  • CELP is a speech coding technique that has the potential of producing high quality synthesised speech at low bit rates, i.e. 4 to 16 kilobits-per-second (kbps). This class of speech coding is used in numerous speech communications and speech synthesis applications.
  • code-excited or "vector-excited” is derived from the fact that an excitation sequence for the speech coder is vector quantised, i.e. a single codeword is used to represent a sequence, or vector, of excitation samples. In this way, it is possible to achieve data rates of less than one bit per sample for coding an excitation sequence.
  • Stored excitation code vectors generally consist of independent random white Gaussian sequences.
  • One code vector from a codebook of stored excitation code vectors is used to represent a block of, say N excitation samples.
  • Each stored code vector is represented by a particular codeword, i.e. an address of the code vector memory location.
  • CELP Code-Excited Linear Prediction
  • an excitation signal for the filters is chosen from a codebook of stored innovation sequences, or code vectors.
  • the speech coder applies each individual code vector to the filters to generate a reconstructed speech signal, and compares the original input speech signal to the reconstructed signal to create an error signal.
  • the error signal is then weighted by passing it through a weighting filter having a response based on human auditory perception.
  • the optimum excitation signal is determined by selecting the code vector that produces the weighted error signal with the minimum energy of error for the current frame.
  • the difficulty of the CELP speech coding technique lies in the very high computational complexity required to perform an exhaustive search of all the excitation code vectors in a typical codebook, for example at a sampling rate of 8 kilohertz (KHz), a 5 millisecond (msec) frame of speech would consist of 40 samples. If the excitation information were coded at a rate of 0.25 bits per sample (corresponding to 2 kbps), then 10 bits of information are used to code each 5 msec, frame. Hence, the random codebook would then contain 2 10 , or 1024, random code vectors.
  • a vector search procedure in such a coder requires approximately 15 multiply-accumulate computations (MACs) (assuming a third order long-term predictor and a tenth order short-term predictor) for each of the 40 samples in each code vector. This corresponds to 600 MACs per code vector per 5 msec speech frame, or approximately 120,000,000 MACs per second (600 MACs/5 msec frame x 1024 code vectors).
  • MACs multiply-accumulate computations
  • the memory allocation requirement to store the codebook of independent random vectors is also exorbitant.
  • a 640 kilobit read-only- memory (ROM) would be required to store all 1024 code vectors, each having 40 samples , each sample represented by a 16-bit word.
  • This ROM size requirement is inconsistent with the size and cost goals of many speech coding applications.
  • Such onerous technical requirements of standard, prior art, code-excited linear prevent the technique from being a practical approach to speech coding.
  • the transform approach requires at least twice the amount of memory, since the transform of each code vector must also be stored. In the above example, a 1.3 Megabit ROM would be required for implementing CELP using transforms.
  • a second approach for reducing the computational complexity is to structure the excitation codebook such that the code vectors are no longer independent of each other. In this manner, the filtered version of a code vector can be computed from the filtered version of the previous code vector, again using only a single filter computation MAC per sample.
  • a third approach for reducing the computational and storage complexity is to structure the excitation codebook such that the code vectors consist of a small number of unit impulses (typically up to 10 per 5 msec, frame). These unit impulses are allowed to have complementary sign (+/-1). Efficient sub-optimal searching of these codebooks is possible when the codebooks are further structured to position the pulses on a series of regularly spaced time-tracks throughout the excitation vector. These are known as Algebraic Codebooks. Such codebooks are described in articles titled "A toll quality 8kb/s speech codec for the personal communications system (PCS)", IEEE Transactions on Vehicular Technology, Vol. 43, pp. 808-816, August 1994 by R. Salami, C.
  • PCS personal communications system
  • VSELP Vector Sum Excited Linear Prediction
  • FIG. 1 there is shown a general block diagram of code excited linear predictive speech coder 100 utilising the excitation signal generation technique according to the present invention.
  • An acoustic input signal to be analysed is applied to speech coder 100 at microphone 102.
  • the input signal typically a speech signal, is then applied to filter 104.
  • Filter 104 generally will exhibit band-pass filter characteristics.
  • the analog speech signal from filter 104 is then converted into a sequence of N pulse samples, and the amplitude of each pulse sample is then represented by a digital code in an analog-to-digital (A/D) converter 108, as generally known in the art.
  • the sampling rate is determined by sample clock SC, which represents an 8.0 KHz rate in the prior art embodiment described in FIG. 1.
  • the sample clock SC is generated along with the frame clock FC via clock 112.
  • A/D 108 which may be represented as input speech vector s(n) is then applied to coefficient analyser 110.
  • This input speech vector s (n) is repetitively obtained in separate frames, i.e. blocks of time, the length of which is determined by the frame clock FC.
  • LPC linear predictive coding
  • the short term predictor parameters (STP), long term predictor parameters LTP, weighting filter parameters (WFP), and excitation gain factor ⁇ are applied to multiplexer 150 and sent over the channel for use by the receiving speech synthesiser.
  • STP short term predictor parameters
  • LTP long term predictor parameters
  • WFP weighting filter parameters
  • excitation gain factor ⁇ (along with the best excitation codeword I, as described later) are applied to multiplexer 150 and sent over the channel for use by the receiving speech synthesiser.
  • the input speech vector s(n) is also applied to subtractor 130, the function of which will be described later.
  • Gain block 122 scales the excitation gain factor ( ⁇ ) may be pre-computed by coefficient analyser 110 and used to analyse all excitation vectors as shown in FIG. 1, or may be optimised jointly with the search for the best excitation codeword I and generated by codebook search controller 140.
  • the scaled excitation signal vu, (n) is then filtered by long term predictor filter 124 and short term predictor filter 126 to generate the reconstructed speech vector s' , (n).
  • Filter 124 utilises the long term predictor parameters LTP to introduce voice periodicity
  • filter 126 utilises the short term predictor parameters STP to introduce the spectral envelope. Note that blocks 124 and 126 are actually recursive filters that contain the long term predictor and short term predictor in their respective feedback paths.
  • the reconstructed speech vector s' , (n) for the i-th excitation code vector is compared to the same block of the input speech vector s(n) by subtracting these two signals in subtractor 130.
  • the difference vector e, (n) represents the difference between the original and the reconstructed blocks of speech.
  • the difference vector is perceptually weighted by weighting filter 132, utilising the weighting filter parameters WTP that are generated by coefficient analyser 110.
  • the preceding reference details a representative weighting filter transfer function. Perceptual weighting is a technique which accentuates those frequencies where the error is perceptually more important to the human ear, and attenuates other frequencies.
  • Energy calculator 134 computes the energy of the weighted difference vector e', (n) , and applies this error signal E, to the codebook search controller 140.
  • the codebook search controller 140 compares the i-th error signal for the present excitation vector u, (n) against previous error signals to determine the excitation vector producing the minimum error.
  • the code of the i-th excitation vector having a minimum error is then output over the channel as the best excitation code I.
  • the codebook search controller 140 may determine a particular codeword that provides an error signal having some predetermined criteria, such as meeting a predefined error threshold.
  • VSELP speech codec attempts to match the ideal excitation of an all-pole model of the vocal tract by summing a small number of basis vectors (or their negatives) on a sample-by-sample basis to the most appropriate part of the excitation from the previous sub-frame. Scaling of both components is calculated to minimise the weighted mean squared error (MSE) between the synthesised speech and the input speech signals.
  • MSE weighted mean squared error
  • the VSELP vectors are all of a length equal to that of one speech sub-frame.
  • VSELP basis vectors must be constructed to minimise the weighted MSE.
  • NTT has produced speech codecs, including the JDC/PDC Half-Rate and a submission to the ITU-T SGI 6 G.4kb/s codec selection, which make use of a Pitch Synchronised CELP codebook.
  • This is described in the paper titled "Design of a Toll-Quality 4 kbit/s Speech Coder Based on Phase- Adaptive PSI-CELP", Proc. ICASSP, pp. 755-758, April 1997, by K. Mano.
  • this codebook apart from being pitch synchronised there is no structure to this codebook and it follows the original CELP codec paradigm.
  • a speech coder for a speech communications unit.
  • the speech coder includes analysis means for analysing an incoming speech signal to determine a particular characteristic of the speech signal and basis vector generating means, operably coupled to the analysis means, for generating a series of basis vectors based on the determined characteristic.
  • the series of basis vectors in the speech coder are optimally generated in accordance with a received speech signal.
  • the speech signal is a voiced speech signal - voiced speech being characterised as those portions of the received signal waveform that are highly periodic with period equal to the pitch as compared to an unvoiced speech signal that can be construed as a a random waveform.
  • the determined characteristic is the pitch of the incoming speech signal, such that the series of basis vectors are generated according to a series of said pitch determinations, such that at least one set of basis vectors is used to model speech of different pitch period.
  • the speech coder further includes selecting means, operably coupled to the analysis means for selecting a portion of the series of basis vectors according to the phase of the incoming speech signal.
  • the conventional VSELP basis vector set are generated using a phase synchroniser operably coupled to the analysis means and the basis vector generator means for synchronising the basis vector phase.
  • the speech coder in the preferred embodiment of the invention further includes a long- term predictor operably coupled to the phase synchroniser, for matching an energy profile of the present speech signal with a speech characteristic in the long term predictor, to generate the series of basis vectors based on the determined phase characteristic.
  • the speech coder includes use of a number of codebooks, such that a first codebook having a first length is used to model unvoiced speech.
  • a second codebook of a second length is used to model voiced speech of pitch periods upto a predefined threshold.
  • a third codebook of a third length can then be used to model voiced speech of pitch periods above a predefined threshold.
  • a radio communications unit including the speech codec, as hereinbefore described, is provided.
  • a method of generating basis vectors in a speech coder includes the step of examining an energy profile of an excitation sequence of a first portion of a speech signal prior to analysing a second portion of the speech signal.
  • the method further includes the step of determining a particular characteristic of the speech signal, and generating a series of basis vectors based on the determined characteristic, for example where the determined characteristic is a pitch of the incoming speech signal, such that the series of basis vectors are generated according to a series of said pitch determinations.
  • the determined characteristic is a pitch of the incoming speech signal
  • the series of basis vectors are generated according to a series of said pitch determinations.
  • portions of the incoming speech signal are selected, and the series of basis vectors are generated according to the determined characteristic of said selected portion.
  • the step of matching an energy profile of the present speech signal with a speech characteristic is performed in a long term predictor to generate the series of basis vectors based on the determined phase characteristic, where at least one set of basis vectors can be used to model speech of different pitch periods.
  • FIG. 1 shows a prior art block diagram of a VSELP codec arrangement.
  • FIG. 2 shows a block diagram of a VSELP codec excitation generation arrangement in accordance with a preferred embodiment of the invention.
  • FIG. 3 shows a block diagram of a pitch-synchronous VSELP codec arrangement for a Primary Excitation Source according to a preferred embodiment of the invention.
  • a speech codec arrangement is shown, based on vector addition/subtraction to simulate the speech signal, in accordance with a preferred embodiment of the invention.
  • An acoustic input signal to be analysed is applied to speech coder 200 at microphone 202.
  • the input signal typically a speech signal, is then applied to filter 204.
  • Filter 204 will generally exhibit band-pass filter characteristics. However, if the speech bandwidth is adequate, filter 204 may be a direct wire connection.
  • the analog speech signal from filter 204 is then converted into a sequence of N pulse samples, and the amplitude of each pulse sample is then represented by a digital code in analog-to-digital (A/D) converter 208, as is known in the art.
  • the sampling rate is determined by sample clock SC, which represents an 8.0 KHz rate in the preferred embodiment.
  • the sample clock SC is generated along with the frame clock FC via clock 212.
  • Each set of super basis vectors is used to model speech of different pitch period which can be derived from the LTP parameters, as compared to prior art basis vectors which are arranged to be of a length equal to a speech sub-frame.
  • One codebook of length N samples is used to model unvoiced speech
  • is used to model voiced speech of pitch periods upto Nj and codebooks N 2 N 3 ... etc. are used to model speech of pitch periods from Ni to N 2 and so on. Therefore the value of n' will differ depending upon the pitch range of the VSELP super basis vector set.
  • a conventional VSELP basis vector set each of length N samples, is derived. If the speech to be synthesised is voiced, as determined by the voiced/unvoiced block 223, then the basis vectors are synchronised with the energy profile of the component of the LTP memory that is applicable to the current speech frame under consideration. This is achieved by Phase Synchronizer 228 and stored in temporary basis vector storage 221. These temporary basis vectors are used by codebook generator 220 to generate a set of 2 M -1 possible sequences as in the VSELP technique.
  • a reconstructed speech vector s' , (n) is generated for comparison to the input speech vector s (n).
  • Gain block 222 scales the excitation gain factor ⁇ which may be pre-computed by coefficient analyser 210 and used to analyse all excitation vectors as shown in FIG. 2, or may be optimised jointly with the search for the best excitation codeword I and generated by codebook search controller 240.
  • the scaled excitation signal vu, (n) is then filtered by long term predictor filter 224 and short term predictor filter 226 to generate the reconstructed speech vector s' , (n).
  • Filter 224 utilises the long-term predictor parameters LTP to introduce voice periodicity, and filter 226 utilises the short-term predictor parameters STP to introduce the spectral envelope. Note that blocks 224 and 226 are actually recursive filters that contain the long term predictor and short term predictor in their respective feedback paths.
  • the reconstructed speech vector s' , (n) for the i-th excitation code vector is compared to the same block of the input speech vector s(n) by subtracting these two signals in subtractor 230.
  • the difference vector e, (n) represents the difference between the original and the reconstructed blocks of speech.
  • the difference vector is perceptually weighted by weighting filter 232, utilising the weighting filter parameters WFP generated by coefficient analyser 210.
  • WFP weighting filter parameters
  • Energy calculator 234 computes the energy of the weighted difference vector e', (n) , and applies this error signal E, to codebook search controller 240.
  • the search controller compares the i-th error signal for the present excitation vector u, (n) against previous error signals to determine the excitation vector producing the minimum error.
  • the code of the i-th excitation vector having a minimum error is then output over the channel as the best excitation code I.
  • codebook search controller 240 may determine a particular codeword that provides an error signal having some predetermined criteria, such as meeting a predefined error threshold.
  • a VSELP speech codec attempts to match the ideal excitation of an all-pole model of the vocal tract by summing a small number of basis vectors (or their negatives) on a sample-by-sample basis to the most appropriate part of the excitation from the previous sub-frame. Scaling of both components is calculated to minimise the weighted mean squared error (MSE) between the synthesised speech and the input speech signals.
  • MSE mean squared error
  • a pitch-synchronous VSELP codebook is synchronised by examining the energy profile of the combined excitation sequence comprising the long-term predictor component for the current sub-frame and the previously stored combined codebook and long-term predictor excitation.
  • Super basis vectors 314, 316, 318 represent an optimised set of excitation parameters for pitches commensurate with that for the current speech being processed. From this set of super basis vectors a set of conventional VSELP basis vectors 324, 326 and 328 are derived by phase adjustment and repetition, if necessary, by function 320.
  • the phase adjustment is performed by analysis of a combination of the stored previous combined excitation 350 and the scaled long-term predictor component 346.
  • the scaled long term predictor component is derived by repeating the stored previous combined excitation 350 with a delay equal to the pitch period for the speech currently being analysed to derive the LTP excitation vector 352. This is scaled in multiplier 354 by the gain Y LTP in order to minimise the weighted squared synthesis error from the input speech segment.
  • the phase adjustment is made by analysing the most recent samples over one pitch period of the combined excitations 346, 350, labelled as segment 348, in function 356 to locate the position of the maximum energy peak.
  • the conventional VSELP basis vectors are multiplied by all possible combinations of "+/-1" in multipliers 330, 332 and 334. They are then summed in summer 336 in order to find the best combination of "+l”s & "-l”s which minimises the weighted squared synthesis error to derive the VSELP excitation vector for the current speech sub-frame 338.
  • the VSELP excitation vector is multiplied in multiplier 340 by the gain Y VSELP and summed in adder 342 with the scaled long term predictor excitation vector to derive the combined excitation vector 344.
  • the phase for the conventional VSELP basis vectors is obtained by analysis of the previous combined excitation 350 without the long-term predictor component.
  • This embodiment is useful when for some reason the long-term predictor component is not available or unreliable.
  • the derivation of a set of conventional VSELP basis vectors from the super basis vectors is conducted in the same manner as previously described.
  • the benefits provided by the present invention in particular with regard to providing a pitch-synchronised VSELP codebook, lie in the better modelling of the stochastic excitation necessary to update the long-term predictor state for voiced speech.
  • the VSELP basis vectors may be optimised to derive updates to the long-term predictor state or adaptive codebook.
  • Pitch synchronised VSELP codebooks may also be optimised, but since different pitch periods and pitch phases are distinguished, the codebook may be optimised to provide better overall performance. This optimisation may be used to reduce the necessary bit-rate of the speech codec, reduce the codebook complexity, or improve synthesised speech quality.
  • the current invention provides higher quality speech, for a given bit rate, than the conventional VSELP codebook paradigm. Furthermore, the present invention provides a more representative speech signal, by determining a characteristic of the speech signal, say pitch of the incoming signal, to generate an improved 'super' set of basis vectors.
  • the codebooks are of a similar size to conventional VSELP codebooks, and the selection of the codebook is performed by simple processes, the additional complexity is relatively small.

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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)

Abstract

L'invention concerne un vocodeur multiple de type PSI-VSELP. Des vecteurs d'excitation sont générés à partir d'un ensemble de vecteurs de base. Le stockage desdits vecteurs est structuré en trois listes de codage. Une première liste de codage est utilisée pour coder des signaux non voisés. Une seconde liste de codage est utilisée pour coder des signaux voisés possédant une hauteur tonale inférieure à une valeur prédéterminée, et une troisième liste de codage est utilisée pour coder les valeurs de hauteur tonale restantes. Les vecteurs de base sont synchronisés à l'aide du profil d'énergie de signal.
EP00960391A 1999-08-02 2000-08-02 Vocodeur de type vselp Withdrawn EP1212750A1 (fr)

Applications Claiming Priority (3)

Application Number Priority Date Filing Date Title
GB9917916A GB2352949A (en) 1999-08-02 1999-08-02 Speech coder for communications unit
GB9917916 1999-08-02
PCT/EP2000/007566 WO2001009880A1 (fr) 1999-08-02 2000-08-02 Vocodeur de type vselp

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EP1212750A1 true EP1212750A1 (fr) 2002-06-12

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EP00960391A Withdrawn EP1212750A1 (fr) 1999-08-02 2000-08-02 Vocodeur de type vselp

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EP (1) EP1212750A1 (fr)
AU (1) AU7272100A (fr)
GB (1) GB2352949A (fr)
WO (1) WO2001009880A1 (fr)

Cited By (1)

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Publication number Priority date Publication date Assignee Title
CN103929222A (zh) * 2005-01-13 2014-07-16 英特尔公司 码书生成系统及相关方法

Families Citing this family (1)

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Publication number Priority date Publication date Assignee Title
FR3011408A1 (fr) * 2013-09-30 2015-04-03 Orange Re-echantillonnage d'un signal audio pour un codage/decodage a bas retard

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US5434947A (en) * 1993-02-23 1995-07-18 Motorola Method for generating a spectral noise weighting filter for use in a speech coder
CA2135629C (fr) * 1993-03-26 2000-02-08 Ira A. Gerson Quantificateur vectoriel a segments multiples pour un codeur de la parole utilisable dans un radiotelephone
US5526464A (en) * 1993-04-29 1996-06-11 Northern Telecom Limited Reducing search complexity for code-excited linear prediction (CELP) coding
JPH08179796A (ja) * 1994-12-21 1996-07-12 Sony Corp 音声符号化方法
JPH09258769A (ja) * 1996-03-18 1997-10-03 Seiko Epson Corp 話者適応化方法および話者適応化装置
GB2312360B (en) * 1996-04-12 2001-01-24 Olympus Optical Co Voice signal coding apparatus

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Cited By (1)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
CN103929222A (zh) * 2005-01-13 2014-07-16 英特尔公司 码书生成系统及相关方法

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WO2001009880A1 (fr) 2001-02-08
GB9917916D0 (en) 1999-09-29
GB2352949A (en) 2001-02-07
AU7272100A (en) 2001-02-19

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