Improved Noise Weighting in CELP Coding of Speech
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MIGRATING RADIO CALL-IN TALK SHOWS to WIDEBAND AUDIO Radio Is the Original Social Network
Established 1961 2013 WBA Broadcasters Clinic Madison, WI MIGRATING RADIO CALL-IN TALK SHOWS TO WIDEBAND AUDIO Radio is the original Social Network • Serves local or national audience • Allows real-time commentary from the masses • The telephone becomes the medium • Telephone technical factors have limited the appeal of the radio “Social Network” Telephones have changed over the years But Telephone Sound has not changed (and has gotten worse) This is very bad for Radio Why do phones sound bad? • System designed for efficiency not comfort • Sampling rate of 8kHz chosen for all calls • 4 kHz max response • Enough for intelligibility • Loses depth, nuance, personality • Listener fatigue Why do phones sound so bad ? (cont) • Low end of telephone calls have intentional high- pass filtering • Meant to avoid AC power hum pickup in phone lines • Lose 2-1/2 Octaves of speech audio on low end • Not relevant for digital Why Phones Sound bad (cont) Los Angeles Times -- January 10, 2009 Verizon Communications Inc., the second-biggest U.S. telephone company, plans to do away with traditional phone lines within seven years as it moves to carry all calls over the Internet. An Internet-based service can be maintained at a fraction of the cost of a phone network and helps Verizon offer a greater range of services, Stratton said. "We've built our business over the years with circuit-switched voice being our bread and butter...but increasingly, we are in the business of selling, basically, data connectivity," Chief Marketing Officer John Stratton said. VoIP -
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. -
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............................................. -
(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. -
Polycom Voice
Level 1 Technical – Polycom Voice Level 1 Technical Polycom Voice Contents 1 - Glossary .......................................................................................................................... 2 2 - Polycom Voice Networks ................................................................................................. 3 Polycom UC Software ...................................................................................................... 3 Provisioning ..................................................................................................................... 3 3 - Key Features (Desktop and Conference Phones) ............................................................ 5 OpenSIP Integration ........................................................................................................ 5 Microsoft Integration ........................................................................................................ 5 Lync Qualification ............................................................................................................ 5 Better Together over Ethernet ......................................................................................... 5 BroadSoft UC-One Integration ......................................................................................... 5 Conference Link / Conference Link2 ................................................................................ 6 Polycom Desktop Connector .......................................................................................... -
NTT DOCOMO Technical Journal
3GPP EVS Codec for Unrivaled Speech Quality and Future Audio Communication over VoLTE EVS Speech Coding Standardization NTT DOCOMO has been engaged in the standardization of Research Laboratories Kimitaka Tsutsumi the 3GPP EVS codec, which is designed specifically for Kei Kikuiri VoLTE to further enhance speech quality, and has contributed to establishing a far-sighted strategy for making the EVS codec cover a variety of future communication services. Journal NTT DOCOMO has also proposed technical solutions that provide speech quality as high as FM radio broadcasts and that achieve both high coding efficiency and high audio quality not possible with any of the state-of-the-art speech codecs. The EVS codec will drive the emergence of a new style of speech communication entertainment that will combine BGM, sound effects, and voice in novel ways for mobile users. 2 Technical Band (AMR-WB)* [2] that is used in also encode music at high levels of quality 1. Introduction NTT DOCOMO’s VoLTE and that sup- and efficiency for non-real-time services, The launch of Voice over LTE (VoL- port wideband speech with a sampling 3GPP experts agreed to adopt high re- TE) services and flat-rate voice service frequency*3 of 16 kHz. In contrast, EVS quirements in the EVS codec for music has demonstrated the importance of high- has been designed to support super-wide- despite its main target of real-time com- quality telephony service to mobile users. band*4 speech with a sampling frequen- munication. Furthermore, considering In line with this trend, the 3rd Genera- cy of 32 kHz thereby achieving speech that telephony services using AMR-WB tion Partnership Project (3GPP) complet- of FM-radio quality*5. -
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]. -
The Growing Importance of HD Voice in Applications the Growing Importance of HD Voice in Applications White Paper
White Paper The Growing Importance of HD Voice in Applications The Growing Importance of HD Voice in Applications White Paper Executive Summary A new excitement has entered the voice communications industry with the advent of wideband audio, commonly known as High Definition Voice (HD Voice). Although enterprises have gradually been moving to HD VoIP within their own networks, these networks have traditionally remained “islands” of HD because interoperability with other networks that also supported HD Voice has been difficult. With the introduction of HD Voice on mobile networks, which has been launched on numerous commercial mobile networks and many wireline VoIP networks worldwide, consumers can finally experience this new technology firsthand. Verizon, AT&T, T-Mobile, Deutsche Telekom, Orange and other mobile operators now offer HD Voice as a standard feature. Because mobile users tend to adopt new technology rapidly, replacing their mobile devices seemingly as fast as the newest models are released, and because landline VoIP speech is typically done via a headset, the growth of HD Voice continues to be high and in turn, the need for HD- capable applications will further accelerate. This white paper provides an introduction to HD Voice and discusses its current adoption rate and future potential, including use case examples which paint a picture that HD Voice upgrades to network infrastructure and applications will be seen as important, and perhaps as a necessity to many. 2 The Growing Importance of HD Voice in Applications White Paper Table of Contents What Is HD Voice? . 4 Where is HD Voice Being Deployed? . 4 Use Case Examples . -
HD Voice – a Revolution in Voice Communication
HD Voice – a revolution in voice communication Besides data capacity and coverage, which are one of the most important factors related to customers’ satisfaction in mobile telephony nowadays, we must not forget about the intrinsic characteristic of the mobile communication – the Voice. Ever since the nineties and the introduction of GSM there have not been much improvements in the area of voice communication and quality of sound has not seen any major changes. Smart Network going forward! Mobile phones made such a progress in recent years that they have almost replaced PCs, but their basic function, voice calls, is still irreplaceable and vital in mobile communication and it has to be seamless. In order to grow our customer satisfaction and expand our service portfolio, Smart Network engineers of Telenor Serbia have enabled HD Voice by introducing new network features and transitioning voice communication to all IP network. This transition delivers crystal-clear communication between the two parties greatly enhancing customer experience during voice communication over smartphones. Enough with the yelling into smartphones! HD Voice (or High-Definition Voice) represents a significant upgrade to sound quality in mobile communications. Thanks to this feature users experience clarity, smoothly reduced background noise and a feeling that the person they are talking to is standing right next to them or of "being in the same room" with the person on the other end of the phone line. On the more technical side, “HD Voice is essentially wideband audio technology, something that long has been used for conference calling and VoIP apps. Instead of limiting a call frequency to between 300 Hz and 3.4 kHz, a wideband audio call transmits at a range of 50 Hz to 7 kHz, or higher. -
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.