The Archivist's Video Codec/Container FAQ H P://Download.Das-Werksta .Com/Pb/Mthk/Info/Video/FAQ-Digital Vi
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PXC 550 Wireless Headphones
PXC 550 Wireless headphones Instruction Manual 2 | PXC 550 Contents Contents Important safety instructions ...................................................................................2 The PXC 550 Wireless headphones ...........................................................................4 Package includes ..........................................................................................................6 Product overview .........................................................................................................7 Overview of the headphones .................................................................................... 7 Overview of LED indicators ........................................................................................ 9 Overview of buttons and switches ........................................................................10 Overview of gesture controls ..................................................................................11 Overview of CapTune ................................................................................................12 Getting started ......................................................................................................... 14 Charging basics ..........................................................................................................14 Installing CapTune .....................................................................................................16 Pairing the headphones ...........................................................................................17 -
Audio Coding for Digital Broadcasting
Recommendation ITU-R BS.1196-7 (01/2019) Audio coding for digital broadcasting BS Series Broadcasting service (sound) ii Rec. ITU-R BS.1196-7 Foreword The role of the Radiocommunication Sector is to ensure the rational, equitable, efficient and economical use of the radio- frequency spectrum by all radiocommunication services, including satellite services, and carry out studies without limit of frequency range on the basis of which Recommendations are adopted. The regulatory and policy functions of the Radiocommunication Sector are performed by World and Regional Radiocommunication Conferences and Radiocommunication Assemblies supported by Study Groups. Policy on Intellectual Property Right (IPR) ITU-R policy on IPR is described in the Common Patent Policy for ITU-T/ITU-R/ISO/IEC referenced in Resolution ITU-R 1. Forms to be used for the submission of patent statements and licensing declarations by patent holders are available from http://www.itu.int/ITU-R/go/patents/en where the Guidelines for Implementation of the Common Patent Policy for ITU-T/ITU-R/ISO/IEC and the ITU-R patent information database can also be found. Series of ITU-R Recommendations (Also available online at http://www.itu.int/publ/R-REC/en) Series Title BO Satellite delivery BR Recording for production, archival and play-out; film for television BS Broadcasting service (sound) BT Broadcasting service (television) F Fixed service M Mobile, radiodetermination, amateur and related satellite services P Radiowave propagation RA Radio astronomy RS Remote sensing systems S Fixed-satellite service SA Space applications and meteorology SF Frequency sharing and coordination between fixed-satellite and fixed service systems SM Spectrum management SNG Satellite news gathering TF Time signals and frequency standards emissions V Vocabulary and related subjects Note: This ITU-R Recommendation was approved in English under the procedure detailed in Resolution ITU-R 1. -
© 2019 Jimi Jones
© 2019 Jimi Jones SO MANY STANDARDS, SO LITTLE TIME: A HISTORY AND ANALYSIS OF FOUR DIGITAL VIDEO STANDARDS BY JIMI JONES DISSERTATION Submitted in partial fulfillment of the requirements for the degree of Doctor of Philosophy in Library and Information Science in the Graduate College of the University of Illinois at Urbana-Champaign, 2019 Urbana, Illinois Doctoral Committee: Associate Professor Jerome McDonough, Chair Associate Professor Lori Kendall Assistant Professor Peter Darch Professor Howard Besser, New York University ABSTRACT This dissertation focuses on standards for digital video - the social aspects of their design and the sociotechnical forces that drive their development and adoption. This work is a history and analysis of how the MXF, JPEG 2000, FFV1 and Matroska standards have been adopted and/or adapted by libraries and archives of different sizes. Well-funded institutions often have the resources to develop tailor-made specifications for the digitization of their analog video objects. Digital video standards and specifications of this kind are often derived from the needs of the cinema production and television broadcast realms in the United States and may be unsuitable for smaller memory institutions that are resource-poor and/or lack staff with the knowledge to implement these technologies. This research seeks to provide insight into how moving image preservation professionals work with - and sometimes against - broadcast and film production industries in order to produce and/or implement standards governing video formats and encodings. This dissertation describes the transition of four digital video standards from niches to widespread use in libraries and archives. It also examines the effects these standards produce on cultural heritage video preservation by interviewing people who implement the standards as well as people who develop them. -
(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. -
A Multi-Frame PCA-Based Stereo Audio Coding Method
applied sciences Article A Multi-Frame PCA-Based Stereo Audio Coding Method Jing Wang *, Xiaohan Zhao, Xiang Xie and Jingming Kuang School of Information and Electronics, Beijing Institute of Technology, 100081 Beijing, China; [email protected] (X.Z.); [email protected] (X.X.); [email protected] (J.K.) * Correspondence: [email protected]; Tel.: +86-138-1015-0086 Received: 18 April 2018; Accepted: 9 June 2018; Published: 12 June 2018 Abstract: With the increasing demand for high quality audio, stereo audio coding has become more and more important. In this paper, a multi-frame coding method based on Principal Component Analysis (PCA) is proposed for the compression of audio signals, including both mono and stereo signals. The PCA-based method makes the input audio spectral coefficients into eigenvectors of covariance matrices and reduces coding bitrate by grouping such eigenvectors into fewer number of vectors. The multi-frame joint technique makes the PCA-based method more efficient and feasible. This paper also proposes a quantization method that utilizes Pyramid Vector Quantization (PVQ) to quantize the PCA matrices proposed in this paper with few bits. Parametric coding algorithms are also employed with PCA to ensure the high efficiency of the proposed audio codec. Subjective listening tests with Multiple Stimuli with Hidden Reference and Anchor (MUSHRA) have shown that the proposed PCA-based coding method is efficient at processing stereo audio. Keywords: stereo audio coding; Principal Component Analysis (PCA); multi-frame; Pyramid Vector Quantization (PVQ) 1. Introduction The goal of audio coding is to represent audio in digital form with as few bits as possible while maintaining the intelligibility and quality required for particular applications [1]. -
Lossless Compression of Audio Data
CHAPTER 12 Lossless Compression of Audio Data ROBERT C. MAHER OVERVIEW Lossless data compression of digital audio signals is useful when it is necessary to minimize the storage space or transmission bandwidth of audio data while still maintaining archival quality. Available techniques for lossless audio compression, or lossless audio packing, generally employ an adaptive waveform predictor with a variable-rate entropy coding of the residual, such as Huffman or Golomb-Rice coding. The amount of data compression can vary considerably from one audio waveform to another, but ratios of less than 3 are typical. Several freeware, shareware, and proprietary commercial lossless audio packing programs are available. 12.1 INTRODUCTION The Internet is increasingly being used as a means to deliver audio content to end-users for en tertainment, education, and commerce. It is clearly advantageous to minimize the time required to download an audio data file and the storage capacity required to hold it. Moreover, the expec tations of end-users with regard to signal quality, number of audio channels, meta-data such as song lyrics, and similar additional features provide incentives to compress the audio data. 12.1.1 Background In the past decade there have been significant breakthroughs in audio data compression using lossy perceptual coding [1]. These techniques lower the bit rate required to represent the signal by establishing perceptual error criteria, meaning that a model of human hearing perception is Copyright 2003. Elsevier Science (USA). 255 AU rights reserved. 256 PART III / APPLICATIONS used to guide the elimination of excess bits that can be either reconstructed (redundancy in the signal) orignored (inaudible components in the signal). -
Improving Opus Low Bit Rate Quality with Neural Speech Synthesis
Improving Opus Low Bit Rate Quality with Neural Speech Synthesis Jan Skoglund1, Jean-Marc Valin2∗ 1Google, San Francisco, CA, USA 2Amazon, Palo Alto, CA, USA [email protected], [email protected] Abstract learned representation set [11]. A typical WaveNet configura- The voice mode of the Opus audio coder can compress wide- tion requires a very high algorithmic complexity, in the order band speech at bit rates ranging from 6 kb/s to 40 kb/s. How- of hundreds of GFLOPS, along with a high memory usage to ever, Opus is at its core a waveform matching coder, and as the hold the millions of model parameters. Combined with the high rate drops below 10 kb/s, quality degrades quickly. As the rate latency, in the hundreds of milliseconds, this renders WaveNet reduces even further, parametric coders tend to perform better impractical for a real-time implementation. Replacing the di- than waveform coders. In this paper we propose a backward- lated convolutional networks with recurrent networks improved compatible way of improving low bit rate Opus quality by re- memory efficiency in SampleRNN [12], which was shown to be synthesizing speech from the decoded parameters. We compare useful for speech coding in [13]. WaveRNN [14] also demon- two different neural generative models, WaveNet and LPCNet. strated possibilities for synthesizing at lower complexities com- WaveNet is a powerful, high-complexity, and high-latency ar- pared to WaveNet. Even lower complexity and real-time opera- chitecture that is not feasible for a practical system, yet pro- tion was recently reported using LPCNet [15]. vides a best known achievable quality with generative models. -
Cognitive Speech Coding Milos Cernak, Senior Member, IEEE, Afsaneh Asaei, Senior Member, IEEE, Alexandre Hyafil
1 Cognitive Speech Coding Milos Cernak, Senior Member, IEEE, Afsaneh Asaei, Senior Member, IEEE, Alexandre Hyafil Abstract—Speech coding is a field where compression ear and undergoes a highly complex transformation paradigms have not changed in the last 30 years. The before it is encoded efficiently by spikes at the auditory speech signals are most commonly encoded with com- nerve. This great efficiency in information representation pression methods that have roots in Linear Predictive has inspired speech engineers to incorporate aspects of theory dating back to the early 1940s. This paper tries to cognitive processing in when developing efficient speech bridge this influential theory with recent cognitive studies applicable in speech communication engineering. technologies. This tutorial article reviews the mechanisms of speech Speech coding is a field where research has slowed perception that lead to perceptual speech coding. Then considerably in recent years. This has occurred not it focuses on human speech communication and machine because it has achieved the ultimate in minimizing bit learning, and application of cognitive speech processing in rate for transparent speech quality, but because recent speech compression that presents a paradigm shift from improvements have been small and commercial applica- perceptual (auditory) speech processing towards cognitive tions (e.g., cell phones) have been mostly satisfactory for (auditory plus cortical) speech processing. The objective the general public, and the growth of available bandwidth of this tutorial is to provide an overview of the impact has reduced requirements to compress speech even fur- of cognitive speech processing on speech compression and discuss challenges faced in this interdisciplinary speech ther. -
Codec Is a Portmanteau of Either
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. -
Recommended File Formats for Long-Term Archiving and for Web Dissemination in Phaidra
Recommended file formats for long-term archiving and for web dissemination in Phaidra Edited by Gianluca Drago May 2019 License: https://creativecommons.org/licenses/by-nc-sa/4.0/ Premise This document is intended to provide an overview of the file formats to be used depending on two possible destinations of the digital document: long-term archiving uploading to Phaidra and subsequent web dissemination When the document uploaded to Phaidra is also the only saved file, the two destinations end up coinciding, but in general one will probably want to produce two different files, in two different formats, so as to meet the differences in requirements and use in the final destinations. In the following tables, the recommendations for long-term archiving are distinct from those for dissemination in Phaidra. There are no absolute criteria for choosing the file format. The choice is always dependent on different evaluations that the person who is carrying out the archiving will have to make on a case by case basis and will often result in a compromise between the best achievable quality and the limits imposed by the costs of production, processing and storage of files, as well as, for the preceding, by the opportunity of a conversion to a new format. 1 This choice is particularly significant from the perspective of long-term archiving, for which a quality that respects the authenticity and integrity of the original document and a format that guarantees long-term access to data are desirable. This document should be seen more as an aid to the reasoned choice of the person carrying out the archiving than as a list of guidelines to be followed to the letter. -
FFV1 Video Codec Specification
FFV1 Video Codec Specification by Michael Niedermayer [email protected] Contents 1 Introduction 2 2 Terms and Definitions 2 2.1 Terms ................................................. 2 2.2 Definitions ............................................... 2 3 Conventions 3 3.1 Arithmetic operators ......................................... 3 3.2 Assignment operators ........................................ 3 3.3 Comparison operators ........................................ 3 3.4 Order of operation precedence .................................... 4 3.5 Range ................................................. 4 3.6 Bitstream functions .......................................... 4 4 General Description 5 4.1 Border ................................................. 5 4.2 Median predictor ........................................... 5 4.3 Context ................................................ 5 4.4 Quantization ............................................. 5 4.5 Colorspace ............................................... 6 4.5.1 JPEG2000-RCT ....................................... 6 4.6 Coding of the sample difference ................................... 6 4.6.1 Range coding mode ..................................... 6 4.6.2 Huffman coding mode .................................... 9 5 Bitstream 10 5.1 Configuration Record ......................................... 10 5.1.1 In AVI File Format ...................................... 11 5.1.2 In ISO/IEC 14496-12 (MP4 File Format) ......................... 11 5.1.3 In NUT File Format .................................... -
Pragmatic Audiovisual Preservation
http://doi.org/10.7207/twr20-10 Pragmatic Audiovisual Preservation Ashley Blewer DPC Technology Watch Report October 2020 © Digital Preservation Coalition 2020 and Ashley Blewer 2020 ISSN: 2048-7916 DOI: http://doi.org/10.7207/twr20-10 All rights reserved. No part of this publication may be reproduced, stored in a retrieval system, or transmitted, in any form or by any means, without prior permission in writing from the publisher. The moral rights of the author have been asserted. First published in Great Britain in 2020 by the Digital Preservation Coalition. Pragmatic Audiovisual Preservation Foreword The Digital Preservation Coalition (DPC) is an advocate and catalyst for digital preservation, ensuring our members can deliver resilient long-term access to digital content and services. It is a not-for- profit membership organization whose primary objective is to raise awareness of the importance of the preservation of digital material and the attendant strategic, cultural and technological issues. It supports its members through knowledge exchange, capacity building, assurance, advocacy and partnership. The DPC’s vision is to make our digital memory accessible tomorrow. The DPC Technology Watch Reports identify, delineate, monitor and address topics that have a major bearing on ensuring our collected digital memory will be for the future. They provide an advanced introduction in order to support those charged with ensuring a robust digital memory, and they are of general interest to a wide and international audience with interests in computing, information management, collections management and technology. The reports are commissioned after consultation among DPC members about shared priorities and challenges; they are commissioned from experts; and they are thoroughly scrutinized by peers before being released.