Speech Coding: Fundamentals and Applications
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Omtp Codecs 1 0, Release 1
OMTP CODECS DEFINITION AND REQUIREMENTS This document contains information that is confidential and proprietary to OMTP Limited. The information may not be used, disclosed or reproduced without the prior written authorisation of OMTP Limited, and those so authorised may only use this information for the purpose consistent with the authorisation. VERSION: OMTP CODECS 1_0, RELEASE 1 STATUS: SUBJECT TO BE - APPROVED BY BOARD 21 JULY 2005 DATE OF LAST EDIT: 6 JULY 2005 OWNER: P4: HARDWARE REQUIREMENTS AND DE- FRAGMENTATION OMTP CODECS CONTENTS 1 INTRODUCTION ............................................................................4 1.1 DOCUMENT PURPOSE ..........................................................................4 1.2 INTENDED AUDIENCE ............................................................................5 2 DEFINITION OF TERMS .................................................................7 2.1 CONVENTIONS .....................................................................................7 3 OMTP CODEC PROFILES ............................................................8 3.1 AUDIO DECODE....................................................................................8 3.2 AUDIO ENCODE....................................................................................9 3.3 VIDEO DECODE....................................................................................9 3.4 VIDEO ENCODE....................................................................................9 3.5 IMAGE DECODE..................................................................................10 -
Speech Coding and Compression
Introduction to voice coding/compression PCM coding Speech vocoders based on speech production LPC based vocoders Speech over packet networks Speech coding and compression Corso di Networked Multimedia Systems Master Universitario di Primo Livello in Progettazione e Gestione di Sistemi di Rete Carlo Drioli Università degli Studi di Verona Facoltà di Scienze Matematiche, Dipartimento di Informatica Fisiche e Naturali Speech coding and compression Introduction to voice coding/compression PCM coding Speech vocoders based on speech production LPC based vocoders Speech over packet networks Speech coding and compression: OUTLINE Introduction to voice coding/compression PCM coding Speech vocoders based on speech production LPC based vocoders Speech over packet networks Speech coding and compression Introduction to voice coding/compression PCM coding Speech vocoders based on speech production LPC based vocoders Speech over packet networks Introduction Approaches to voice coding/compression I Waveform coders (PCM) I Voice coders (vocoders) Quality assessment I Intelligibility I Naturalness (involves speaker identity preservation, emotion) I Subjective assessment: Listening test, Mean Opinion Score (MOS), Diagnostic acceptability measure (DAM), Diagnostic Rhyme Test (DRT) I Objective assessment: Signal to Noise Ratio (SNR), spectral distance measures, acoustic cues comparison Speech coding and compression Introduction to voice coding/compression PCM coding Speech vocoders based on speech production LPC based vocoders Speech over packet networks -
Packetcable™ 2.0 Codec and Media Specification PKT-SP-CODEC
PacketCable™ 2.0 Codec and Media Specification PKT-SP-CODEC-MEDIA-I10-120412 ISSUED Notice This PacketCable specification is the result of a cooperative effort undertaken at the direction of Cable Television Laboratories, Inc. for the benefit of the cable industry and its customers. This document may contain references to other documents not owned or controlled by CableLabs. Use and understanding of this document may require access to such other documents. Designing, manufacturing, distributing, using, selling, or servicing products, or providing services, based on this document may require intellectual property licenses from third parties for technology referenced in this document. Neither CableLabs nor any member company is responsible to any party for any liability of any nature whatsoever resulting from or arising out of use or reliance upon this document, or any document referenced herein. This document is furnished on an "AS IS" basis and neither CableLabs nor its members provides any representation or warranty, express or implied, regarding the accuracy, completeness, noninfringement, or fitness for a particular purpose of this document, or any document referenced herein. 2006-2012 Cable Television Laboratories, Inc. All rights reserved. PKT-SP-CODEC-MEDIA-I10-120412 PacketCable™ 2.0 Document Status Sheet Document Control Number: PKT-SP-CODEC-MEDIA-I10-120412 Document Title: Codec and Media Specification Revision History: I01 - Released 04/05/06 I02 - Released 10/13/06 I03 - Released 09/25/07 I04 - Released 04/25/08 I05 - Released 07/10/08 I06 - Released 05/28/09 I07 - Released 07/02/09 I08 - Released 01/20/10 I09 - Released 05/27/10 I10 – Released 04/12/12 Date: April 12, 2012 Status: Work in Draft Issued Closed Progress Distribution Restrictions: Authors CL/Member CL/ Member/ Public Only Vendor Key to Document Status Codes: Work in Progress An incomplete document, designed to guide discussion and generate feedback, that may include several alternative requirements for consideration. -
Space Application Development Board
Space Application Development Board The Space Application Development Board (SADB-C6727B) enables developers to implement systems using standard and custom algorithms on processor hardware similar to what would be deployed for space in a fully radiation hardened (rad-hard) design. The SADB-C6727B is devised to be similar to a space qualified rad-hardened system design using the TI SMV320C6727B-SP DSP and high-rel memories (SRAM, SDRAM, NOR FLASH) from Cobham. The VOCAL SADB- C6727B development board does not use these high reliability space qualified components but rather implements various common bus widths and memory types/speeds for algorithm development and performance evaluation. VOCAL Technologies, Ltd. www.vocal.com 520 Lee Entrance, Suite 202 Tel: (716) 688-4675 Buffalo, New York 14228 Fax: (716) 639-0713 Audio inputs are handled by a TI ADS1278 high speed multichannel analog-to-digital converter (ADC) which has a variant qualified for space operation. Audio outputs may be generated from digital signal Pulse Density Modulation (PDM) or Pulse Width Modulation (PWM) signals to avoid the need for a space qualified digital-to-analog converter (DAC) hardware or a traditional audio codec circuit. A commercial grade AIC3106 audio codec is provided for algorithm development and for comparison of audio performance to PDM/PWM generated audio signals. Digital microphones (PDM or I2S formats) can be sampled by the processor directly or by the AIC3106 audio codec (PDM format only). Digital audio inputs/outputs can also be connected to other processors (using the McASP signals directly). Both SRAM and SDRAM memories are supported via configuration resistors to allow for developing and benchmarking algorithms using either 16-bit wide or 32-bit wide busses (also via configuration resistors). -
Concatenation of Compression Codecs – the Need for Objective Evaluations
Concatenation of compression codecs – The need for objective evaluations C.J. Dalton (UKIB) In this article the Author considers, firstly, a hypothetical broadcast network in which compression equipments have replaced several existing functions – resulting in multiple-cascading. Secondly, he describes a similar network that has been optimized for compression technology. Picture-quality assessment methods – both conventional and new, fied for still-picture applications in the printing in- subjective and objective – are dustry and was adapted to motion video applica- discussed with the aim of providing tions, by encoding on a picture-by-picture basis. background information. Some Various proprietary versions of JPEG, with higher proposals are put forward for compression ratios, were introduced to reduce the objective evaluation together with storage requirements, and alternative systems based on Wavelets and Fractals have been imple- initial observations when concaten- mented. Due to the availability of integrated hard- ating (cascading) codecs of similar ware, motion JPEG is now widely used for off- and different types. and on-line editing, disc servers, slow-motion sys- tems, etc., but there is little standardization and few interfaces at the compressed level. The MPEG-1 compression standard was aimed at 1. Introduction progressively-scanned moving images and has been widely adopted for CD-ROM and similar ap- Bit-rate reduction (BRR) techniques – commonly plications; it has also found limited application for referred to as compression – are now firmly estab- broadcast video. The MPEG-2 system is specifi- lished in the latest generation of broadcast televi- cally targeted at the complete gamut of video sys- sion equipments. tems; for standard-definition television, the MP@ML codec – with compression ratios of 20:1 Original language: English Manuscript received 15/1/97. -
Digital Speech Processing— Lecture 17
Digital Speech Processing— Lecture 17 Speech Coding Methods Based on Speech Models 1 Waveform Coding versus Block Processing • Waveform coding – sample-by-sample matching of waveforms – coding quality measured using SNR • Source modeling (block processing) – block processing of signal => vector of outputs every block – overlapped blocks Block 1 Block 2 Block 3 2 Model-Based Speech Coding • we’ve carried waveform coding based on optimizing and maximizing SNR about as far as possible – achieved bit rate reductions on the order of 4:1 (i.e., from 128 Kbps PCM to 32 Kbps ADPCM) at the same time achieving toll quality SNR for telephone-bandwidth speech • to lower bit rate further without reducing speech quality, we need to exploit features of the speech production model, including: – source modeling – spectrum modeling – use of codebook methods for coding efficiency • we also need a new way of comparing performance of different waveform and model-based coding methods – an objective measure, like SNR, isn’t an appropriate measure for model- based coders since they operate on blocks of speech and don’t follow the waveform on a sample-by-sample basis – new subjective measures need to be used that measure user-perceived quality, intelligibility, and robustness to multiple factors 3 Topics Covered in this Lecture • Enhancements for ADPCM Coders – pitch prediction – noise shaping • Analysis-by-Synthesis Speech Coders – multipulse linear prediction coder (MPLPC) – code-excited linear prediction (CELP) • Open-Loop Speech Coders – two-state excitation -
Ffmpeg Documentation Table of Contents
ffmpeg Documentation Table of Contents 1 Synopsis 2 Description 3 Detailed description 3.1 Filtering 3.1.1 Simple filtergraphs 3.1.2 Complex filtergraphs 3.2 Stream copy 4 Stream selection 5 Options 5.1 Stream specifiers 5.2 Generic options 5.3 AVOptions 5.4 Main options 5.5 Video Options 5.6 Advanced Video options 5.7 Audio Options 5.8 Advanced Audio options 5.9 Subtitle options 5.10 Advanced Subtitle options 5.11 Advanced options 5.12 Preset files 6 Tips 7 Examples 7.1 Preset files 7.2 Video and Audio grabbing 7.3 X11 grabbing 7.4 Video and Audio file format conversion 8 Syntax 8.1 Quoting and escaping 8.1.1 Examples 8.2 Date 8.3 Time duration 8.3.1 Examples 8.4 Video size 8.5 Video rate 8.6 Ratio 8.7 Color 8.8 Channel Layout 9 Expression Evaluation 10 OpenCL Options 11 Codec Options 12 Decoders 13 Video Decoders 13.1 rawvideo 13.1.1 Options 14 Audio Decoders 14.1 ac3 14.1.1 AC-3 Decoder Options 14.2 ffwavesynth 14.3 libcelt 14.4 libgsm 14.5 libilbc 14.5.1 Options 14.6 libopencore-amrnb 14.7 libopencore-amrwb 14.8 libopus 15 Subtitles Decoders 15.1 dvdsub 15.1.1 Options 15.2 libzvbi-teletext 15.2.1 Options 16 Encoders 17 Audio Encoders 17.1 aac 17.1.1 Options 17.2 ac3 and ac3_fixed 17.2.1 AC-3 Metadata 17.2.1.1 Metadata Control Options 17.2.1.2 Downmix Levels 17.2.1.3 Audio Production Information 17.2.1.4 Other Metadata Options 17.2.2 Extended Bitstream Information 17.2.2.1 Extended Bitstream Information - Part 1 17.2.2.2 Extended Bitstream Information - Part 2 17.2.3 Other AC-3 Encoding Options 17.2.4 Floating-Point-Only AC-3 Encoding -
Relating Optical Speech to Speech Acoustics and Visual Speech Perception
UNIVERSITY OF CALIFORNIA Los Angeles Relating Optical Speech to Speech Acoustics and Visual Speech Perception A dissertation submitted in partial satisfaction of the requirements for the degree Doctor of Philosophy in Electrical Engineering by Jintao Jiang 2003 i © Copyright by Jintao Jiang 2003 ii The dissertation of Jintao Jiang is approved. Kung Yao Lieven Vandenberghe Patricia A. Keating Lynne E. Bernstein Abeer Alwan, Committee Chair University of California, Los Angeles 2003 ii Table of Contents Chapter 1. Introduction ............................................................................................... 1 1.1. Audio-Visual Speech Processing ............................................................................ 1 1.2. How to Examine the Relationship between Data Sets ............................................ 4 1.3. The Relationship between Articulatory Movements and Speech Acoustics........... 5 1.4. The Relationship between Visual Speech Perception and Physical Measures ....... 9 1.5. Outline of This Dissertation .................................................................................. 15 Chapter 2. Data Collection and Pre-Processing ...................................................... 17 2.1. Introduction ........................................................................................................... 17 2.2. Background ........................................................................................................... 18 2.3. Recording a Database for the Correlation Analysis............................................. -
Speech Compression Using Discrete Wavelet Transform and Discrete Cosine Transform
International Journal of Engineering Research & Technology (IJERT) ISSN: 2278-0181 Vol. 1 Issue 5, July - 2012 Speech Compression Using Discrete Wavelet Transform and Discrete Cosine Transform Smita Vatsa, Dr. O. P. Sahu M. Tech (ECE Student ) Professor Department of Electronicsand Department of Electronics and Communication Engineering Communication Engineering NIT Kurukshetra, India NIT Kurukshetra, India Abstract reproduced with desired level of quality. Main approaches of speech compression used today are Aim of this paper is to explain and implement waveform coding, transform coding and parametric transform based speech compression techniques. coding. Waveform coding attempts to reproduce Transform coding is based on compressing signal input signal waveform at the output. In transform by removing redundancies present in it. Speech coding at the beginning of procedure signal is compression (coding) is a technique to transform transformed into frequency domain, afterwards speech signal into compact format such that speech only dominant spectral features of signal are signal can be transmitted and stored with reduced maintained. In parametric coding signals are bandwidth and storage space respectively represented through a small set of parameters that .Objective of speech compression is to enhance can describe it accurately. Parametric coders transmission and storage capacity. In this paper attempts to produce a signal that sounds like Discrete wavelet transform and Discrete cosine original speechwhether or not time waveform transform -
Speech Coding Using Code Excited Linear Prediction
ISSN : 0976-8491 (Online) | ISSN : 2229-4333 (Print) IJCST VOL . 5, Iss UE SPL - 2, JAN - MAR C H 2014 Speech Coding Using Code Excited Linear Prediction 1Hemanta Kumar Palo, 2Kailash Rout 1ITER, Siksha ‘O’ Anusandhan University, Bhubaneswar, Odisha, India 2Gandhi Institute For Technology, Bhubaneswar, Odisha, India Abstract The main problem with the speech coding system is the optimum utilization of channel bandwidth. Due to this the speech signal is coded by using as few bits as possible to get low bit-rate speech coders. As the bit rate of the coder goes low, the intelligibility, SNR and overall quality of the speech signal decreases. Hence a comparative analysis is done of two different types of speech coders in this paper for understanding the utility of these coders in various applications so as to reduce the bandwidth and by different speech coding techniques and by reducing the number of bits without any appreciable compromise on the quality of speech. Hindi language has different number of stops than English , hence the performance of the coders must be checked on different languages. The main objective of this paper is to develop speech coders capable of producing high quality speech at low data rates. The focus of this paper is the development and testing of voice coding systems which cater for the above needs. Keywords PCM, DPCM, ADPCM, LPC, CELP Fig. 1: Speech Production Process I. Introduction Speech coding or speech compression is the compact digital The two types of speech sounds are voiced and unvoiced [1]. representations of voice signals [1-3] for the purpose of efficient They produce different sounds and spectra due to their differences storage and transmission. -
Influence of Speech Codecs Selection on Transcoding Steganography
Influence of Speech Codecs Selection on Transcoding Steganography Artur Janicki, Wojciech Mazurczyk, Krzysztof Szczypiorski Warsaw University of Technology, Institute of Telecommunications Warsaw, Poland, 00-665, Nowowiejska 15/19 Abstract. The typical approach to steganography is to compress the covert data in order to limit its size, which is reasonable in the context of a limited steganographic bandwidth. TranSteg (Trancoding Steganography) is a new IP telephony steganographic method that was recently proposed that offers high steganographic bandwidth while retaining good voice quality. In TranSteg, compression of the overt data is used to make space for the steganogram. In this paper we focus on analyzing the influence of the selection of speech codecs on hidden transmission performance, that is, which codecs would be the most advantageous ones for TranSteg. Therefore, by considering the codecs which are currently most popular for IP telephony we aim to find out which codecs should be chosen for transcoding to minimize the negative influence on voice quality while maximizing the obtained steganographic bandwidth. Key words: IP telephony, network steganography, TranSteg, information hiding, speech coding 1. Introduction Steganography is an ancient art that encompasses various information hiding techniques, whose aim is to embed a secret message (steganogram) into a carrier of this message. Steganographic methods are aimed at hiding the very existence of the communication, and therefore any third-party observers should remain unaware of the presence of the steganographic exchange. Steganographic carriers have evolved throughout the ages and are related to the evolution of the methods of communication between people. Thus, it is not surprising that currently telecommunication networks are a natural target for steganography. -
CT8021 H.32X G.723.1/G.728 Truespeech Co-Processor
CT8021 H.32x G.723.1/G.728 TrueSpeech Co-Processor Introduction Features The CT8021 is a speech co-processor which · TrueSpeechâ G.723.1 at 6.3, 5.3, 4.8 and performs full duplex speech compression and de- 4.1 kbps at 8KHz sampling rate (including compression functions. It provides speech G.723.1 Annex A VAD/CNG) compression for H.320, H.323 and H.324 · G.728 16 Kbps LD-CELP Multimedia Visual Telephony / Video · Download of additional speech compression Conferencing products and DSVD Modems. The software modules into external sram for CT8021 has built-in TrueSpeechâ G.723.1 (for TrueSpeechâ 8.5, G.722 & G.729-A/B H.323 and H.324) as well as G.728 LD-CELP · Real-time Full duplex or Half duplex speech speech compression (for H.320). This combination compression and decompression of ITU speech compression standards within a · Acoustic Echo Cancellation concurrent with single device enables the creation of a single full-duplex speech compression multimedia terminal which can operate in all · Full Duplex standalone Speakerphone types of Video Conferencing systems including · Host-to-Host (codec-less) and Host-CODEC H.320 ISDN-based, H.324 POTS-based, and modes of operation H.323 LAN/Internet-based. TrueSpeechâ G.723.1 · Parallel 8-bit host interface provides simple provides compressed data rates of 6.3 and 5.3 memory-mapped I/O host connection. Kbps and includes G.723.1 Annex A VAD/CNG · 1 or 2-channel DMA support (Single Cycle “silence” compression which can supply an even and Burst Modes) lower average bit rate.