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WO2005106849A1 - Compression/decompression audio numerique a codage/decodage de coefficients de predicteur linaire a complexite reduite - Google Patents

Compression/decompression audio numerique a codage/decodage de coefficients de predicteur linaire a complexite reduite Download PDF

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Publication number
WO2005106849A1
WO2005106849A1 PCT/US2005/012738 US2005012738W WO2005106849A1 WO 2005106849 A1 WO2005106849 A1 WO 2005106849A1 US 2005012738 W US2005012738 W US 2005012738W WO 2005106849 A1 WO2005106849 A1 WO 2005106849A1
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WO
WIPO (PCT)
Prior art keywords
partial correlation
companded
correlation coefficient
quantized
coefficients
Prior art date
Application number
PCT/US2005/012738
Other languages
English (en)
Inventor
Yuriy A. Reznik
Original Assignee
Realnetworks, Inc.
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 Realnetworks, Inc. filed Critical Realnetworks, Inc.
Publication of WO2005106849A1 publication Critical patent/WO2005106849A1/fr

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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
    • G10L19/06—Determination or coding of the spectral characteristics, e.g. of the short-term prediction coefficients

Definitions

  • the present invention relates to the field of signal processing. More specifically, the present invention relates to compression and decompression of audio signal data.
  • PCM audio has a number of advantages over analog audio.
  • pulse code modulation (PCM) audio has a number of advantages over other audio formats.
  • PCM audio offers freedom to interchange audio data without generation loss between media.
  • PCM audio is not only being offered in mediums like compact disc (CD), it is also widely employed in broadcast programming, through air waves or cable, or in streamed content, through private and/or public networks, such as the Internet.
  • CD compact disc
  • bandwidth availability/consumption remains a significant challenge.
  • digital audio data is often compressed.
  • linear prediction filtering is often employed as part of the compression process.
  • Figure 1 illustrates an overview of an encoder for compressing audio signal data, in accordance with some embodiments of the present invention
  • Figure 2 illustrates an overview of a decoder for decompressing audio signal data, in accordance with some embodiments of the present invention
  • Figure 3 illustrates a system, including an encoder and a decoder of Fig. 1-2, respective, in accordance with some embodiments.
  • Illustrative embodiments of the present invention include, but are not limited to, a method to compress digital audio data (in particular, PCM audio data), encoders and/or decoders adapted to practice all or portions of the method, and systems having the encoders/decoders.
  • digital audio data in particular, PCM audio data
  • encoders and/or decoders adapted to practice all or portions of the method
  • systems having the encoders/decoders Various aspects of embodiments of the present invention will be described. However, various embodiments may be practiced with only some or all of the described aspects. For purposes of explanation, specific numbers, materials and configurations are set forth in order to provide a thorough understanding of the embodiments being described. In alternate embodiments, the described aspects may be practiced without explaining the specific details of operation.
  • Examples of general purpose “computing devices/systems” may include, but are not limited to, handheld computing devices (palm sized, tablet sized and so forth), laptop computing devices, desktop computing devices, servers, and so forth.
  • Examples of special purpose “computing device/system” may include, but are not limited to, processor based wireless mobile phones, handheld digital music players, set-top boxes, game boxes/consoles, CD/DVD players, digital cameras, digital CAMCORDERS, and so forth.
  • DVD - Digital Versatile Disk Various operations will be described as multiple discrete operations in turn, in a manner that is most helpful in understanding the various embodiments of the present invention, however, the order of description should not be construed as to imply that these operations are necessarily order dependent.
  • Encoder 100 includes Buffer 102, Linear Predictive Coding (LPC) Coefficient Estimator 104, Predictor 106, Quantization Unit 108, Subtractor 109, Entropy Encoder 110, and Multiplexor 112, coupled with each other as shown.
  • LPC Linear Predictive Coding
  • Encoder 100 includes LPC Coefficient Converter 114, Companding and Quantization Unit 116, and Partial Correlation (ParCor) Encoder 118 coupled with each other and the earlier enumerated elements, as shown.
  • Buffer 102 is adapted to temporally and successively store portions of an incoming audio stream to be encoded.
  • LPC Coefficient Estimator 104 is adapted to provide a number of LPC coefficients, based on the incoming audio stream, for use to apply linear prediction filtering on the incoming audio stream, to generate residuals for the audio stream.
  • Quantization Unit 108 is adapted to quantize the linear prediction coefficients.
  • Predictor 106 and Subtractor 109 are used in conjunction to generate the residuals of the audio data.
  • Entropy Encoder 110 is adapted to encode the residuals, generated encoded residuals and associated code indices.
  • LPC Coefficients Converter 114 is adapted to convert the linear prediction coefficients to partial correlation coefficients.
  • Companding and quantication unit 116 is adapted to compand and quantize the partial correlation coefficients to generate companded and quantized partial correlation coefficients.
  • ParCor Encoder 118 is adapted to encode the companded and quantized partial correlation coefficients.
  • Multiplexor is adapted to multiplex the encoded residuals of the audio data, the associated code indices, and the encoded partial correlation coefficients to form the compressed audio data bitstream. Resultantly, compressed audio data bitstream is typically more compact than prior art compressed audio data bitstream.
  • ParCor Encoder 118 is adapted to encode the companded and quantized partial correlation coefficients as follows: For each companded and quantized partial correlation coefficient, a residual of the companded and quantized partial correlation coefficient is computed by subtracting an offset from the companded and quantized partial correlation coefficient to generate an intermediate value; then multiplying the intermediate value by 2 to obtain the residual, if the intermediate value is positive, or multiplying the intermediate value by -2 to obtain another intermediate value, and adding 1 to the other intermediate value to obtain the residual, if the intermediate value is negative. In turn, the residual of the companded and quantized partial correlation coefficient is encoded. In various embodiments, the encoding may be performed, for example, using Golomb-Rice codes.
  • the encoding may be performed, using Huffman codes, Arithmetic codes, Fixed-rate codes, codes of the like or combination of them (including combination with Golomb-Rice codes).
  • the offsets and Rice parameters for the various coefficients are as follows:
  • Encoder 100 may be implemented in hardware and/or software, in whole or in part. For examples, for software implementations, it may be implemented in C or other system programming languages; for hardware implementations, the logic may be implemented using programmable gate arrays or Application Specific Integrated Circuits (ASIC).
  • ASIC Application Specific Integrated Circuits
  • Decoder 200 includes De- Multiplexor 212, Entropy Decoder 210, Adder 209, De-Quantization Unit 208, Predictor 206, and Buffer 202, coupled with each other as shown. Further, Decoder 200 includes Partial Correlation Decoder 218, De-Quantization and Inverse Companding Unit 216, and LPC Coefficient Recovery Unit 214, coupled with each other and the earlier enumerated elements, as shown.
  • De-Multiplexor 212 is adapted to de-multiplex an audio bitstream to recover the encoded residuals of the audio data, the associated code indices and the encoded partial correlation coefficients.
  • Entropy Decoder 210 is adapted to decode the encoded residuals, to recover unencoded residuals.
  • Predictor 206 and Adder 209 are used in conjunction to recover the audio data.
  • Buffer 202 is adapted to temporally and successively store portions of recovered/decompressed audio data.
  • ParCor Decoder 218 is adapted to decode the encoded companded and quantized partial correlation coefficients.
  • De-Quantication and Inverse Companding Unit 216 is adapted to de-quantize and inverse compand the companded and quantized partial correlation coefficients to recover the original partial correlation coefficients.
  • LPC Coefficients Recovery Unit 214 is adapted to recover the linear prediction coefficients from the partial correlation coefficients.
  • Quantization Unit 208 is adapted to quantize the recovered linear prediction coefficients for earlier described Predictor 206. In various embodiments, the above described elements are performed under the control of a controller (not shown). Still referring to Figure 2, in various embodiments, where the residuals of companded and quantized partial correlation coefficients are encoded (e.g.
  • ParCor Decoder 218 is adapted to decode the encoded residuals as follows: For each residual of a companded and quantized partial correlation coefficient, the companded and quantized partial correlation coefficient is computed by subtracting 1 from the residual to obtain a difference, dividing the difference by -2 to obtain a first quotient, determine whether the first quotient is negative, adding an offset to the first quotient to obtain the companded and quantized partial correlation coefficient, if the first quotient is negative, dividing the residual by 2 to obtain a second quotient, if the first quotient is not negative, and adding an offset to the second quotient to obtain the companded and quantized partial correlation coefficient, if the second quotient is computed.
  • decoder 200 may be implemented in hardware and/or software, in whole or in part. Referring now to Figure 3, wherein a system incorporated with the encoder and decoder of Fig 1-2 respectively, in accordance with various embodiments. As illustrated, for the embodiments, system 300 includes audio source 302 and audio renderer 304 operatively coupled to each other via "connection" 306.
  • Audio source 302 and audio renderer 304 includes audio encoder 100 and audio decoder 200 of Fig. 1 and 2, respectively.
  • audio source 302 and audio renderer 304 may be components of an audio application (e.g. a speech related application).
  • audio source 302 and audio renderer 304 may be components of an audio/video application (e.g. an audio/video streaming application).
  • audio source 302 and audio renderer 304 may be components of the same electronic device, coupled 306 to each other via e.g. an internal system bus of the electronic device.
  • audio source 302 and audio renderer 304 may be disposed on separate electronic devices, coupled 306 to each other via e.g. a cable or a networked connection.
  • Audio source 302 may e.g. be a server, set- top unit, a desktop computer, and so forth.
  • Audio renderer 304 may be a speaker, a media player, a desktop computer, and so forth.
  • the networked connection may be a local area network connection or a wide area network connection, wired or wireless.

Landscapes

  • Engineering & Computer Science (AREA)
  • Physics & Mathematics (AREA)
  • Spectroscopy & Molecular Physics (AREA)
  • Computational Linguistics (AREA)
  • Signal Processing (AREA)
  • Health & Medical Sciences (AREA)
  • Audiology, Speech & Language Pathology (AREA)
  • Human Computer Interaction (AREA)
  • Acoustics & Sound (AREA)
  • Multimedia (AREA)
  • Compression, Expansion, Code Conversion, And Decoders (AREA)

Abstract

Dans une application de filtrage de prédiction linéaire pour la compression d'un ensemble de données audio, des coefficients de prédiction linéaire sont codés par codage de leurs coefficients de corrélation partielle correspondants. Pendant la décompression, ces coefficients de prédiction linéaire sont récupérés à partir des coefficients de corrélation partielle récupérés.
PCT/US2005/012738 2004-04-14 2005-04-14 Compression/decompression audio numerique a codage/decodage de coefficients de predicteur linaire a complexite reduite WO2005106849A1 (fr)

Applications Claiming Priority (2)

Application Number Priority Date Filing Date Title
US56266904P 2004-04-14 2004-04-14
US60/562,669 2004-04-14

Publications (1)

Publication Number Publication Date
WO2005106849A1 true WO2005106849A1 (fr) 2005-11-10

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PCT/US2005/012738 WO2005106849A1 (fr) 2004-04-14 2005-04-14 Compression/decompression audio numerique a codage/decodage de coefficients de predicteur linaire a complexite reduite

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WO (1) WO2005106849A1 (fr)

Cited By (1)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
KR100718416B1 (ko) 2006-06-28 2007-05-14 주식회사 대우일렉트로닉스 예측필터를 이용한 채널간 스테레오 오디오 코딩 방법

Citations (3)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
US4390747A (en) * 1979-09-28 1983-06-28 Hitachi, Ltd. Speech analyzer
US4516259A (en) * 1981-05-11 1985-05-07 Kokusai Denshin Denwa Co., Ltd. Speech analysis-synthesis system
US5822732A (en) * 1995-05-12 1998-10-13 Mitsubishi Denki Kabushiki Kaisha Filter for speech modification or enhancement, and various apparatus, systems and method using same

Patent Citations (3)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
US4390747A (en) * 1979-09-28 1983-06-28 Hitachi, Ltd. Speech analyzer
US4516259A (en) * 1981-05-11 1985-05-07 Kokusai Denshin Denwa Co., Ltd. Speech analysis-synthesis system
US5822732A (en) * 1995-05-12 1998-10-13 Mitsubishi Denki Kabushiki Kaisha Filter for speech modification or enhancement, and various apparatus, systems and method using same

Cited By (1)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
KR100718416B1 (ko) 2006-06-28 2007-05-14 주식회사 대우일렉트로닉스 예측필터를 이용한 채널간 스테레오 오디오 코딩 방법

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