During the past ten years a new area in speech processing, generally referred to as linear prediction, has evolved. As with all scientific research, results did not always get published in a logical order and terminology was not always con sistent. In mid-1974, we decided to begin an extra hours and weekends project of organizing the literature in linear prediction of speech and developing it into a unified presentation in terms of content and terminology. This effort was completed in November, 1975, with the contents presented herein. If there are two words which describe our goals in this book, they are unifica tion and depth. Considerable effort has been spent on showing the interrelation ships among various linear prediction formulations and solutions, and in develop ing extensions such as acoustic tube models and synthesis filter structures in a unified manner with consistent terminology. Topics are presented in such a manner that derivations and theoretical details are covered, along with Fortran sub routines and practical considerations. Using this approach we hope to have made the material useful for a wide range of backgrounds and interests.

This book provides scientific understanding of the most central techniques used in speech coding both for advanced students as well as professionals with a background in speech audio and or digital signal processing. It provides a clear connection between the Why’s?, How’s?, and What’s, such that the necessity, purpose and solutions provided by tools should be always within sight, as well as their strengths and weaknesses in each respect. Equivalently, this book sheds light on the following perspectives for each technology presented: Objective: What do we want to achieve and especially why is this goal important? Resource / Information: What information is available and how can it be useful? Resource / Platform: What kind of platforms are we working with and what are the capabilities/restrictions of those platforms? This includes properties such as computational, memory, acoustic and transmission capacity of devices used. Solutions: Which solutions have been proposed and how can they be used to reach the stated goals? Strengths and weaknesses: In which ways do the solutions fulfill the objectives and where are they insufficient? Are resources used efficiently? This book concentrates solely on code excited linear prediction and its derivatives since mainstream speech codecs are based on linear prediction It also concentrates exclusively on time domain techniques because frequency domain tools are to a large extent common with audio codecs.

Speech Dereverberation gathers together an overview, a mathematical formulation of the problem and the state-of-the-art solutions for dereverberation. Speech Dereverberation presents current approaches to the problem of reverberation. It provides a review of topics in room acoustics and also describes performance measures for dereverberation. The algorithms are then explained with mathematical analysis and examples that enable the reader to see the strengths and weaknesses of the various techniques, as well as giving an understanding of the questions still to be addressed. Techniques rooted in speech enhancement are included, in addition to a treatment of multichannel blind acoustic system identification and inversion. The TRINICON framework is shown in the context of dereverberation to be a generalization of the signal processing for a range of analysis and enhancement techniques. Speech Dereverberation is suitable for students at masters and doctoral level, as well as established researchers.

Speech coding has been an ongoing area of research for several decades, yet the level of activity and interest in this area has expanded dramatically in the last several years. Important advances in algorithmic techniques for speech coding have recently emerged and excellent progress has been achieved in producing high quality speech at bit rates as low as 4.8 kb/s. Although the complexity of the newer more sophisticated algorithms greatly exceeds that of older methods (such as ADPCM), today's powerful programmable signal processor chips allow rapid technology transfer from research to product development and permit many new cost-effective applications of speech coding. In particular, low bit rate voice technology is converging with the needs of the rapidly evolving digital telecom munication networks. The IEEE Workshop on Speech Coding for Telecommunications was held in Vancouver, British Columbia, Canada, from September 5 to 8, 1989. The objective of the workshop was to provide a forum for discussion of recent developments and future directions in speech coding. The workshop attracted over 130 researchers from several countries and its technical program included 51 papers.

Speech coding is a highly mature branch of signal processing deployed in products such as cellular phones, communication devices, and more recently, voice over internet protocol This book collects many of the techniques used in speech coding and presents them in an accessible fashion Emphasizes the foundation and evolution of standardized speech coders, covering standards from 1984 to the present The theory behind the applications is thoroughly analyzed and proved

It is becoming increasingly apparent that all forms of communication-including voice-will be transmitted through packet-switched networks based on the Internet Protocol (IP). Therefore, the design of modern devices that rely on speech interfaces, such as cell phones and PDAs, requires a complete and up-to-date understanding of the basics of speech

Machine Learning Techniques for Space Weather provides a thorough and accessible presentation of machine learning techniques that can be employed by space weather professionals. Additionally, it presents an overview of real-world applications in space science to the machine learning community, offering a bridge between the fields. As this volume demonstrates, real advances in space weather can be gained using nontraditional approaches that take into account nonlinear and complex dynamics, including information theory, nonlinear auto-regression models, neural networks and clustering algorithms. Offering practical techniques for translating the huge amount of information hidden in data into useful knowledge that allows for better prediction, this book is a unique and important resource for space physicists, space weather professionals and computer scientists in related fields. - Collects many representative non-traditional approaches to space weather into a single volume - Covers, in an accessible way, the mathematical background that is not often explained in detail for space scientists - Includes free software in the form of simple MATLAB® scripts that allow for replication of results in the book, also familiarizing readers with algorithms

When Speech and Audio Signal Processing published in 1999, it stood out from its competition in its breadth of coverage and its accessible, intutiont-based style. This book was aimed at individual students and engineers excited about the broad span of audio processing and curious to understand the available techniques. Since then, with the advent of the iPod in 2001, the field of digital audio and music has exploded, leading to a much greater interest in the technical aspects of audio processing. This Second Edition will update and revise the original book to augment it with new material describing both the enabling technologies of digital music distribution (most significantly the MP3) and a range of exciting new research areas in automatic music content processing (such as automatic transcription, music similarity, etc.) that have emerged in the past five years, driven by the digital music revolution. New chapter topics include: Psychoacoustic Audio Coding, describing MP3 and related audio coding schemes based on psychoacoustic masking of quantization noise Music Transcription, including automatically deriving notes, beats, and chords from music signals. Music Information Retrieval, primarily focusing on audio-based genre classification, artist/style identification, and similarity estimation. Audio Source Separation, including multi-microphone beamforming, blind source separation, and the perception-inspired techniques usually referred to as Computational Auditory Scene Analysis (CASA).

Provides the reader with a practical introduction to the wide range of important concepts that comprise the field of digital speech processing. Students of speech research and researchers working in the field can use this as a reference guide.