DOCSLIB.ORG

Exploring Use of Non-Negative Matrix Factorization for Lossy Audio Compression Student: Bc

Total Page：16

File Type：pdf, Size：1020Kb

Download full-text PDF Read full-text
Exploring Use of Non-Negative Matrix Factorization for Lossy Audio Compression Student: Bc ASSIGNMENT OF MASTER’S THESIS Title: Exploring use of non-negative matrix factorization for lossy audio compression Student: Bc. Tomáš Drbota Supervisor: doc. Ing. Ivan Šimeček, Ph.D. Study Programme: Informatics Study Branch: System Programming Department: Department of Theoretical Computer Science Validity: Until the end of winter semester 2019/20 Instructions The aim of this work is to research existing methods for lossy audio compression and to apply non-negative matrix factorization (NMF) in order to improve the compression ratio without a noticeable loss in quality. Therefore, the goals are as following: 1) Become familiar with state of the art digital audio encoding and compression methods [1]. 2) Become familiar with non-negative matrix factorization, its properties and applications in digital audio processing [2][3]. 3) Design and implement a proof of concept audio codec utilizing NMF for audio compression, or extend an existing codec with this functionality [4]. 4) Find a suitable method for measuring perceived audio quality. 5) Measure the resulting audio quality and compare the quality and compression ratio to existing solutions. References [1] BOSI, Marina and Richard E. GOLDBERG, 2003. Introduction to digital audio coding and standards. Boston: Kluwer Academic Publishers. [2] Wang, Y., & Zhang, Y. (2013). Nonnegative Matrix Factorization: A Comprehensive Review. IEEE Transactions on Knowledge and Data Engineering, 25(6), 1336-1353. [3] RECOSKIE, Daniel and MANN, Richard, 2014, Constrained Nonnegative Matrix Factorization with Applications to Music Transcription. University of Waterloo Technical Report CS-2014-27 [online]. 23 December 2014. [4] VALIN, Jean-Marc, MAXWELL, Gregory, TERRIBERRY, Timothy B. and VOS, Koen, 2013, High-Quality, Low-Delay Music Coding in the Opus Codec. [online]. October 2013. doc. Ing. Jan Janoušek, Ph.D. doc. RNDr. Ing. Marcel Jiřina, Ph.D. Head of Department Dean Prague June 19, 2018 Master’s thesis Exploring use of non-negative matrix factorization for lossy audio compression Bc. Tom´aˇsDrbota Department of Theoretical Computer Science Supervisor: doc. Ing. Ivan Simeˇcek,Ph.D.ˇ May 8, 2019 Acknowledgements I would like to thank my supervisor for always being quick to consult any arising issues. My thanks also go to my family and friends for supporting me throughout the entire time of my studies. Declaration I hereby declare that the presented thesis is my own work and that I have cited all sources of information in accordance with the Guideline for adhering to ethical principles when elaborating an academic final thesis. I acknowledge that my thesis is subject to the rights and obligations stipu- lated by the Act No. 121/2000 Coll., the Copyright Act, as amended. In accor- dance with Article 46(6) of the Act, I hereby grant a nonexclusive authoriza- tion (license) to utilize this thesis, including any and all computer programs incorporated therein or attached thereto and all corresponding documentation (hereinafter collectively referred to as the “Work”), to any and all persons that wish to utilize the Work. Such persons are entitled to use the Work in any way (including for-profit purposes) that does not detract from its value. This authorization is not limited in terms of time, location and quantity. In Prague on May 8, 2019 . Czech Technical University in Prague Faculty of Information Technology c 2019 Tom´aˇsDrbota. All rights reserved. This thesis is school work as defined by Copyright Act of the Czech Republic. It has been submitted at Czech Technical University in Prague, Faculty of Information Technology. The thesis is protected by the Copyright Act and its usage without author’s permission is prohibited (with exceptions defined by the Copyright Act). Citation of this thesis Drbota, Tom´aˇs. Exploring use of non-negative matrix factorization for lossy audio compression. Master’s thesis. Czech Technical University in Prague, Faculty of Information Technology, 2019. Abstrakt Algoritmus nez´aporn´ehorozkladu matic byl ´uspˇesnˇepouˇzit pro mnoho r˚uzn´ych probl´em˚u,kter´esouvis´ıs anal´yzouvelk´ehomnoˇzstv´ıdat a z nich plynouc´ıch souvislost´ı. Vyuˇz´ıv´ase napˇr. pro rozpozn´av´an´ıobliˇcej˚u,separaci sign´al˚uˇci kompresi obr´azk˚u. C´ılemt´etopr´ace je prozkoumat moˇzn´evyuˇzit´ınez´aporn´ehorozkladu matic pro ztr´atovou kompresi zvuku. Bude naprogramov´anreferenˇcn´ıkod´era dekod´er zvuku vyuˇz´ıvajic´ıNMF, a s n´ımbudou potom provedeny r˚uzn´eexperimenty. V´ysledkybudou zmˇeˇreny a srovn´any v˚uˇciexistuj´ıc´ımn´astroj˚umpro kompresi zvuku. Kl´ıˇcov´a slova ztr´atov´akomprese, zvuk, komprese dat, nmf, k´odov´an´ı Abstract Non-negative matrix factorization has been successfully applied in various scenarios involving analysis of large chunks of data and finding patterns in them for later use. It’s used to perform things such as face recognition, source separation or image compression among others. The purpose of this thesis is to research possible uses of non-negative matrix factorization in the problem of lossy audio compression. A reference vii audio encoder and decoder using NMF will be implemented and various ex- periments using this encoder will be conducted. The results will be measured and compared to existing audio compressing solutions. Keywords lossy compression, audio, data compression, nmf, encoding viii Contents 1 Introduction 1 2 Digital audio 3 2.1 Important terms . 3 2.1.1 Sampling . 3 2.1.2 Nyquist frequency . 4 2.1.3 Quantization . 5 2.1.4 Windowing . 7 2.1.5 Transient . 9 2.1.6 Aliasing . 9 2.1.7 Spectral leakage . 9 2.1.8 Scalloping . 9 2.2 Digital audio representation . 10 2.2.1 Time domain representation . 10 2.2.2 Frequency domain representation . 11 2.3 Psychoacoustics . 15 2.3.1 Pitch . 15 2.3.2 Loudness . 17 2.3.3 Auditory masking . 17 3 Non-negative matrix factorization 19 3.1 Linear dimensionality reduction . 19 3.2 NMF definition . 20 3.3 Classification . 20 3.3.1 Basic NMF . 20 3.3.2 Constrained NMF (CNMF) . 21 3.3.3 Structured NMF (SNMF) . 21 3.3.4 Generalized NMF (GNMF) . 21 3.4 Properties . 22 ix 3.5 Algorithms . 22 3.5.1 Cost function . 22 3.5.2 Update rules . 23 3.5.3 Initialization . 23 3.6 Use in digital audio processing . 24 4 Data compression 25 4.1 Lossy audio compression . 25 4.1.1 State of the art . 25 4.1.2 Compression using NMF . 28 4.2 Lossless data compression . 29 4.2.1 Huffman coding . 29 5 Design 31 5.1 WAVE file . 31 5.2 ANMF File structure . 32 5.3 Encoder . 33 5.3.1 ANMF-RAW . 33 5.3.2 ANMF-MDCT . 34 5.3.3 ANMF-STFT . 35 5.4 Decoder . 39 6 Implementation 41 6.1 Used 3rd party libraries . 41 6.1.1 click . 41 6.1.2 pytest . 42 6.1.3 dahuffman . 42 6.1.4 SciPy . 42 6.2 Command line utility . 43 6.3 Audio library . 43 6.4 Compression library . 44 6.4.1 Utility functions . 44 6.4.2 NMF implementation . 47 6.4.3 ANMF-RAW . 48 6.4.4 ANMF-MDCT . 48 6.4.5 ANMF-STFT . 50 7 Evaluation 53 7.1 Methodology . 53 7.2 GstPEAQ . 54 7.3 Evaluating results . 54 7.3.1 Audio examples . 55 7.3.2 Bitrate . 55 7.3.3 ANMF-RAW . 55 x 7.3.4 ANMF-MDCT . 57 7.3.5 ANMF-STFT . 58 7.3.6 Comparison . 63 8 Conclusion 65 Bibliography 67 A List of Symbols 73 B Abbreviations 75 C Contents of enclosed CD 77 xi List of Figures 2.1 Example audio signal . 4 2.2 Windowing example . 8 2.3 Spectral leakage example . 10 2.4 Example audio spectrogram . 13 2.5 Bark scale . 16 2.6 Auditory masking . 18 3.1 NMF classification . 20 4.1 MP3 encoding scheme . 26 4.2 Comparison of various audio codecs . 28 5.1 Encoder overview . 33 5.2 ANMF-RAW Encoder . 33 5.3 ANMF-MDCT Encoder . 34 5.4 ANMF-STFT Encoder . 36 5.5 ANMF-STFT quantized phase frequencies . 37 5.6 ANMF-STFT quantized magnitude coefficient frequencies . 38 5.7 Decoder overview . 39 7.1 ANMF-RAW cost function . 56 7.2 ANMF-MDCT cost function . 58 7.3 ANMF-STFT cost function . 59 7.4 ANMF-STFT rank versus bitrate . 62 7.5 ANMF-STFT chunk size versus bitrate . 63 xiii List of Tables 2.1 Digital audio notation . 5 5.1 ANMF file structure . 32 5.2 Serialized matrix structure . 32 5.3 Serialized quantized matrix structure . 32 5.4 ANMF-RAW data structure . 34 5.5 ANMF-RAW structure of each data chunk . 34 5.6 ANMF-MDCT data structure . 35 5.7 ANMF-MDCT structure of each data chunk . 35 5.8 ANMF-STFT data structure . 39 5.9 ANMF-STFT structure of each magnitude submatrix . 39 7.1 PEAQ - Objective Difference Grade table . 54 7.2 List of tested audio files . 55 7.3 ANMF-RAW rank experiment results . 56 7.4 ANMF-RAW average runtime in seconds . 56 7.5 ANMF-MDCT rank experiment results . 59 7.6 ANMF-STFT rank experiment results . 61 7.7 ANMF-STFT chunk size experiment results . 62 7.8 ANMF-STFT µW experiment results . 63 7.9 ANMF-STFT µH experiment results . ..
Load more

Recommended publications
  • Download Media Player Codec Pack Version 4.1 Media Player Codec Pack
    download media player codec pack version 4.1 Media Player Codec Pack. Description: In Microsoft Windows 10 it is not possible to set all file associations using an installer. Microsoft chose to block changes of file associations with the introduction of their Zune players. Third party codecs are also blocked in some instances, preventing some files from playing in the Zune players. A simple workaround for this problem is to switch playback of video and music files to Windows Media Player manually. In start menu click on the "Settings". In the "Windows Settings" window click on "System". On the "System" pane click on "Default apps". On the "Choose default applications" pane click on "Films & TV" under "Video Player". On the "Choose an application" pop up menu click on "Windows Media Player" to set Windows Media Player as the default player for video files. Footnote: The same method can be used to apply file associations for music, by simply clicking on "Groove Music" under "Media Player" instead of changing Video Player in step 4. Media Player Codec Pack Plus. Codec's Explained: A codec is a piece of software on either a device or computer capable of encoding and/or decoding video and/or audio data from files, streams and broadcasts. The word Codec is a portmanteau of ' co mpressor- dec ompressor' Compression types that you will be able to play include: x264 | x265 | h.265 | HEVC | 10bit x265 | 10bit x264 | AVCHD | AVC DivX | XviD | MP4 | MPEG4 | MPEG2 and many more. File types you will be able to play include: .bdmv | .evo | .hevc | .mkv | .avi | .flv | .webm | .mp4 | .m4v | .m4a | .ts | .ogm .ac3 | .dts | .alac | .flac | .ape | .aac | .ogg | .ofr | .mpc | .3gp and many more.
    [Show full text]
  • Ardour Export Redesign
    Ardour Export Redesign Thorsten Wilms [email protected] Revision 2 2007-07-17 Table of Contents 1 Introduction 4 4.5 Endianness 8 2 Insights From a Survey 4 4.6 Channel Count 8 2.1 Export When? 4 4.7 Mapping Channels 8 2.2 Channel Count 4 4.8 CD Marker Files 9 2.3 Requested File Types 5 4.9 Trimming 9 2.4 Sample Formats and Rates in Use 5 4.10 Filename Conflicts 9 2.5 Wish List 5 4.11 Peaks 10 2.5.1 More than one format at once 5 4.12 Blocking JACK 10 2.5.2 Files per Track / Bus 5 4.13 Does it have to be a dialog? 10 2.5.3 Optionally store timestamps 5 5 Track Export 11 2.6 General Problems 6 6 MIDI 12 3 Feature Requests 6 7 Steps After Exporting 12 3.1 Multichannel 6 7.1 Normalize 12 3.2 Individual Files 6 7.2 Trim silence 13 3.3 Realtime Export 6 7.3 Encode 13 3.4 Range ad File Export History 7 7.4 Tag 13 3.5 Running a Script 7 7.5 Upload 13 3.6 Export Markers as Text 7 7.6 Burn CD / DVD 13 4 The Current Dialog 7 7.7 Backup / Archiving 14 4.1 Time Span Selection 7 7.8 Authoring 14 4.2 Ranges 7 8 Container Formats 14 4.3 File vs Directory Selection 8 8.1 libsndfile, currently offered for Export 14 4.4 Container Types 8 8.2 libsndfile, also interesting 14 8.3 libsndfile, rather exotic 15 12 Specification 18 8.4 Interesting 15 12.1 Core 18 8.4.1 BWF – Broadcast Wave Format 15 12.2 Layout 18 8.4.2 Matroska 15 12.3 Presets 18 8.5 Problematic 15 12.4 Speed 18 8.6 Not of further interest 15 12.5 Time span 19 8.7 Check (Todo) 15 12.6 CD Marker Files 19 9 Encodings 16 12.7 Mapping 19 9.1 Libsndfile supported 16 12.8 Processing 19 9.2 Interesting 16 12.9 Container and Encodings 19 9.3 Problematic 16 12.10 Target Folder 20 9.4 Not of further interest 16 12.11 Filenames 20 10 Container / Encoding Combinations 17 12.12 Multiplication 20 11 Elements 17 12.13 Left out 21 11.1 Input 17 13 Credits 21 11.2 Output 17 14 Todo 22 1 Introduction 4 1 Introduction 2 Insights From a Survey The basic purpose of Ardour's export functionality is I conducted a quick survey on the Linux Audio Users to create mixdowns of multitrack arrangements.
    [Show full text]
  • A Practical Approach to Spatiotemporal Data Compression
    A Practical Approach to Spatiotemporal Data Compres- sion Niall H. Robinson1, Rachel Prudden1 & Alberto Arribas1 1Informatics Lab, Met Office, Exeter, UK. Datasets representing the world around us are becoming ever more unwieldy as data vol- umes grow. This is largely due to increased measurement and modelling resolution, but the problem is often exacerbated when data are stored at spuriously high precisions. In an effort to facilitate analysis of these datasets, computationally intensive calculations are increasingly being performed on specialised remote servers before the reduced data are transferred to the consumer. Due to bandwidth limitations, this often means data are displayed as simple 2D data visualisations, such as scatter plots or images. We present here a novel way to efficiently encode and transmit 4D data fields on-demand so that they can be locally visualised and interrogated. This nascent “4D video” format allows us to more flexibly move the bound- ary between data server and consumer client. However, it has applications beyond purely scientific visualisation, in the transmission of data to virtual and augmented reality. arXiv:1604.03688v2 [cs.MM] 27 Apr 2016 With the rise of high resolution environmental measurements and simulation, extremely large scientific datasets are becoming increasingly ubiquitous. The scientific community is in the pro- cess of learning how to efficiently make use of these unwieldy datasets. Increasingly, people are interacting with this data via relatively thin clients, with data analysis and storage being managed by a remote server. The web browser is emerging as a useful interface which allows intensive 1 operations to be performed on a remote bespoke analysis server, but with the resultant information visualised and interrogated locally on the client1, 2.
    [Show full text]
  • (A/V Codecs) REDCODE RAW (.R3D) ARRIRAW
    What is a Codec? Codec is a portmanteau of either "Compressor-Decompressor" or "Coder-Decoder," which describes a device or program capable of performing transformations on a data stream or signal. Codecs encode a stream or signal for transmission, storage or encryption and decode it for viewing or editing. Codecs are often used in videoconferencing and streaming media solutions. A video codec converts analog video signals from a video camera into digital signals for transmission. It then converts the digital signals back to analog for display. An audio codec converts analog audio signals from a microphone into digital signals for transmission. It then converts the digital signals back to analog for playing. The raw encoded form of audio and video data is often called essence, to distinguish it from the metadata information that together make up the information content of the stream and any "wrapper" data that is then added to aid access to or improve the robustness of the stream. Most codecs are lossy, in order to get a reasonably small file size. There are lossless codecs as well, but for most purposes the almost imperceptible increase in quality is not worth the considerable increase in data size. The main exception is if the data will undergo more processing in the future, in which case the repeated lossy encoding would damage the eventual quality too much. Many multimedia data streams need to contain both audio and video data, and often some form of metadata that permits synchronization of the audio and video. Each of these three streams may be handled by different programs, processes, or hardware; but for the multimedia data stream to be useful in stored or transmitted form, they must be encapsulated together in a container format.
    [Show full text]
  • Command-Line Sound Editing Wednesday, December 7, 2016
    21m.380 Music and Technology Recording Techniques & Audio Production Workshop: Command-line sound editing Wednesday, December 7, 2016 1 Student presentation (pa1) • 2 Subject evaluation 3 Group picture 4 Why edit sound on the command line? Figure 1. Graphical representation of sound • We are used to editing sound graphically. • But for many operations, we do not actually need to see the waveform! 4.1 Potential applications • • • • • • • • • • • • • • • • 1 of 11 21m.380 · Workshop: Command-line sound editing · Wed, 12/7/2016 4.2 Advantages • No visual belief system (what you hear is what you hear) • Faster (no need to load guis or waveforms) • Efficient batch-processing (applying editing sequence to multiple files) • Self-documenting (simply save an editing sequence to a script) • Imaginative (might give you different ideas of what’s possible) • Way cooler (let’s face it) © 4.3 Software packages On Debian-based gnu/Linux systems (e.g., Ubuntu), install any of the below packages via apt, e.g., sudo apt-get install mplayer. Program .deb package Function mplayer mplayer Play any media file Table 1. Command-line programs for sndfile-info sndfile-programs playing, converting, and editing me- Metadata retrieval dia files sndfile-convert sndfile-programs Bit depth conversion sndfile-resample samplerate-programs Resampling lame lame Mp3 encoder flac flac Flac encoder oggenc vorbis-tools Ogg Vorbis encoder ffmpeg ffmpeg Media conversion tool mencoder mencoder Media conversion tool sox sox Sound editor ecasound ecasound Sound editor 4.4 Real-world
    [Show full text]
  • Multimedia Compression Techniques for Streaming
    International Journal of Innovative Technology and Exploring Engineering (IJITEE) ISSN: 2278-3075, Volume-8 Issue-12, October 2019 Multimedia Compression Techniques for Streaming Preethal Rao, Krishna Prakasha K, Vasundhara Acharya most of the audio codes like MP3, AAC etc., are lossy as Abstract: With the growing popularity of streaming content, audio files are originally small in size and thus need not have streaming platforms have emerged that offer content in more compression. In lossless technique, the file size will be resolutions of 4k, 2k, HD etc. Some regions of the world face a reduced to the maximum possibility and thus quality might be terrible network reception. Delivering content and a pleasant compromised more when compared to lossless technique. viewing experience to the users of such locations becomes a The popular codecs like MPEG-2, H.264, H.265 etc., make challenge. audio/video streaming at available network speeds is just not feasible for people at those locations. The only way is to use of this. FLAC, ALAC are some audio codecs which use reduce the data footprint of the concerned audio/video without lossy technique for compression of large audio files. The goal compromising the quality. For this purpose, there exists of this paper is to identify existing techniques in audio-video algorithms and techniques that attempt to realize the same. compression for transmission and carry out a comparative Fortunately, the field of compression is an active one when it analysis of the techniques based on certain parameters. The comes to content delivering. With a lot of algorithms in the play, side outcome would be a program that would stream the which one actually delivers content while putting less strain on the audio/video file of our choice while the main outcome is users' network bandwidth? This paper carries out an extensive finding out the compression technique that performs the best analysis of present popular algorithms to come to the conclusion of the best algorithm for streaming data.
    [Show full text]
  • CALIFORNIA STATE UNIVERSITY, NORTHRIDGE Optimized AV1 Inter
    CALIFORNIA STATE UNIVERSITY, NORTHRIDGE Optimized AV1 Inter Prediction using Binary classification techniques A graduate project submitted in partial fulfillment of the requirements for the degree of Master of Science in Software Engineering by Alex Kit Romero May 2020 The graduate project of Alex Kit Romero is approved: ____________________________________ ____________ Dr. Katya Mkrtchyan Date ____________________________________ ____________ Dr. Kyle Dewey Date ____________________________________ ____________ Dr. John J. Noga, Chair Date California State University, Northridge ii Dedication This project is dedicated to all of the Computer Science professors that I have come in contact with other the years who have inspired and encouraged me to pursue a career in computer science. The words and wisdom of these professors are what pushed me to try harder and accomplish more than I ever thought possible. I would like to give a big thanks to the open source community and my fellow cohort of computer science co-workers for always being there with answers to my numerous questions and inquiries. Without their guidance and expertise, I could not have been successful. Lastly, I would like to thank my friends and family who have supported and uplifted me throughout the years. Thank you for believing in me and always telling me to never give up. iii Table of Contents Signature Page ................................................................................................................................ ii Dedication .....................................................................................................................................
    [Show full text]
  • Data Compression Using Pre-Generated Dictionaries
    Technical Disclosure Commons Defensive Publications Series January 2020 Data compression using pre-generated dictionaries Simon Cooke Follow this and additional works at: https://www.tdcommons.org/dpubs_series Recommended Citation Cooke, Simon, "Data compression using pre-generated dictionaries", Technical Disclosure Commons, (January 16, 2020) https://www.tdcommons.org/dpubs_series/2876 This work is licensed under a Creative Commons Attribution 4.0 License. This Article is brought to you for free and open access by Technical Disclosure Commons. It has been accepted for inclusion in Defensive Publications Series by an authorized administrator of Technical Disclosure Commons. Cooke: Data compression using pre-generated dictionaries Data compression using pre-generated dictionaries ABSTRACT A file is compressed by replacing its characters by codes that are dependent on the statistics of the characters. The character-to-code table, known as the dictionary, is typically incorporated into the compressed file. Popular compression schemes reach theoretical compression limit only asymptotically. Small files or files without much intra-file redundancy, either compress poorly or not at all. This disclosure describes techniques that achieve superior compression, even for small files or files without much intra-file redundancy, by independently maintaining the dictionary at the transmitting and receiving ends of a file transmission, such that the dictionary does not need to be incorporated into the compressed file. KEYWORDS ● Data compression ● Codec dictionary ● Compression dictionary ● Compression ratio ● Page load speed ● Webpage download ● Shannon limit ● Webpage compression ● JavaScript compression ● Web browser Published by Technical Disclosure Commons, 2020 2 Defensive Publications Series, Art. 2876 [2020] BACKGROUND A file is compressed by replacing its characters by codes that are dependent on the statistics of the characters.
    [Show full text]
  • Lossy Audio Compression Identification
    2018 26th European Signal Processing Conference (EUSIPCO) Lossy Audio Compression Identification Bongjun Kim Zafar Rafii Northwestern University Gracenote Evanston, USA Emeryville, USA [email protected] zafar.rafi[email protected] Abstract—We propose a system which can estimate from an compression parameters from an audio signal, based on AAC, audio recording that has previously undergone lossy compression was presented in [3]. The first implementation of that work, the parameters used for the encoding, and therefore identify the based on MP3, was then proposed in [4]. The idea was to corresponding lossy coding format. The system analyzes the audio signal and searches for the compression parameters and framing search for the compression parameters and framing conditions conditions which match those used for the encoding. In particular, which match those used for the encoding, by measuring traces we propose a new metric for measuring traces of compression of compression in the audio signal, which typically correspond which is robust to variations in the audio content and a new to time-frequency coefficients quantized to zero. method for combining the estimates from multiple audio blocks The first work to investigate alterations, such as deletion, in- which can refine the results. We evaluated this system with audio excerpts from songs and movies, compressed into various coding sertion, or substitution, in audio signals which have undergone formats, using different bit rates, and captured digitally as well lossy compression, namely MP3, was presented in [5]. The as through analog transfer. Results showed that our system can idea was to measure traces of compression in the signal along identify the correct format in almost all cases, even at high bit time and detect discontinuities in the estimated framing.
    [Show full text]
  • What Is Ogg Vorbis?
    Ogg Vorbis Audio Compression Format Norat Rossello Castilla 5/18/2005 Ogg Vorbis 1 What is Ogg Vorbis? z Audio compression format z Comparable to MP3, VQF, AAC, TwinVQ z Free, open and unpatented z Broadcasting, radio station and television by internet ( = Streaming) 5/18/2005 Ogg Vorbis 2 1 About the name… z Ogg = name of Xiph.org container format for audio, video and metadata z Vorbis = name of specific audio compression scheme designed to be contained in Ogg FOR MORE INFO... https://www.xiph.org 5/18/2005 Ogg Vorbis 3 Some comercial characteristics z The official mime type was approved in February 2003 z Posible to encode all music or audio content in Vorbis z Designed to not be proprietary or patented audio format z Patent and licensed-free z Specification in public domain 5/18/2005 Ogg Vorbis 4 2 Audio Compression z Two classes of compression algorithms: - Lossless - Lossy FOR MORE INFO... http://www.firstpr.com.au/audiocomp 5/18/2005 Ogg Vorbis 5 Lossless algorithms z Produce compressed data that can be decoded to output that is identical to the original. z Zip, FLAC for audio 5/18/2005 Ogg Vorbis 6 3 Lossy algorithms z Discard data in order to compress it better than would normally be possible z VORBIS, MP3, JPEG z Throw away parts of the audio waveform that are irrelevant. 5/18/2005 Ogg Vorbis 7 Ogg Vorbis - Compression Factors z Vorbis is an audio codec that generates 16 bit samples at 16KHz to 48KHz, providing variable bit rates from 16 to 128 Kbps per channel FOR MORE INFO..
    [Show full text]
  • Data Compression a Comparison of Methods
    OMPUTER SCIENCE & TECHNOLOGY: Data Compression A Comparison of Methods NBS Special Publication 500-12 U.S. DEPARTMENT OF COMMERCE 00-12 National Bureau of Standards NATIONAL BUREAU OF STANDARDS The National Bureau of Standards^ was established by an act of Congress March 3, 1901. The Bureau's overall goal is to strengthen and advance the Nation's science and technology and facilitate their effective application for public benefit. To this end, the Bureau conducts research and provides: (1) a basis for the Nation's physical measurement system, (2) scientific and technological services for industry and government, (3) a technical basis for equity in trade, and (4) technical services to pro- mote public safety. The Bureau consists of the Institute for Basic Standards, the Institute for Materials Research, the Institute for Applied Technology, the Institute for Computer Sciences and Technology, the Office for Information Programs, and the Office of Experimental Technology Incentives Program. THE INSTITUTE FOR BASIC STANDARDS provides the central basis within the United States of a complete and consist- ent system of physical measurement; coordinates that system with measurement systems of other nations; and furnishes essen- tial services leading to accurate and uniform physical measurements throughout the Nation's scientific community, industry, and commerce. The Institute consists of the Office of Measurement Services, and the following center and divisions: Applied Mathematics — Electricity — Mechanics — Heat — Optical Physics — Center for Radiation Research — Lab- oratory Astrophysics- — Cryogenics^ — Electromagnetics' — Time and Frequency". THE INSTITUTE FOR MATERIALS RESEARCH conducts materials research leading to improved methods of measure- ment, standards, and data on the properties of well-characterized materials needed by industry, commerce, educational insti- tutions, and Government; provides advisory and research services to other Government agencies; and develops, produces, and distributes standard reference materials.
    [Show full text]
  • Methods of Sound Data Compression \226 Comparison of Different Standards
    See discussions, stats, and author profiles for this publication at: https://www.researchgate.net/publication/251996736 Methods of sound data compression — Comparison of different standards Article CITATIONS READS 2 151 2 authors, including: Wojciech Zabierowski Lodz University of Technology 123 PUBLICATIONS 96 CITATIONS SEE PROFILE Some of the authors of this publication are also working on these related projects: How to biuld correct web application View project All content following this page was uploaded by Wojciech Zabierowski on 11 June 2014. The user has requested enhancement of the downloaded file. 1 Methods of sound data compression – comparison of different standards Norbert Nowak, Wojciech Zabierowski Abstract - The following article is about the methods of multimedia devices, DVD movies, digital television, data sound data compression. The technological progress has transmission, the Internet, etc. facilitated the process of recording audio on different media such as CD-Audio. The development of audio Modeling and coding data compression has significantly made our lives One's requirements decide what type of compression he easier. In recent years, much has been achieved in the applies. However, the choice between lossy or lossless field of audio and speech compression. Many standards method also depends on other factors. One of the most have been established. They are characterized by more important is the characteristics of data that will be better sound quality at lower bitrate. It allows to record compressed. For instance, the same algorithm, which the same CD-Audio formats using "lossy" or lossless effectively compresses the text may be completely useless compression algorithms in order to reduce the amount in the case of video and sound compression.
    [Show full text]