Antonio Peinado & Jose Segura 
Speech Recognition Over Digital Channels 
Robustness and Standards

Automatic speech recognition (ASR) is a very attractive means for
human-machine interaction. The degree of maturity reached by speech
recognition technologies during recent years allows the development
of applications that use them. In particular, ASR shows an enormous
potential in mobile environments, where devices such as mobile
phones or PDAs are used, and for Internet Protocol (IP)
applications.

Speech Recognition Over Digital Channels is the first
book of its kind to offer a complete system comprehension,
addressing the topics of distributed and network-based speech
recognition issues and standards, the concepts of speech processing
and transmission, and system architectures and robustness.

Describes the different client/server architectures for remote
speech recognition systems, by means of which the client transmits
speech parameters through a digital channel to a remote recognition
server

* Focuses on robustness against both adverse acoustic
environments (in the front-end) and bit errors/packet loss

* Discusses four ETSI standards for distributed speech
recognition; the understanding of the standards and the
technologies behind them

* Provides the necessary background for the comprehension of
remote speech recognition technologies

This book will appeal to a wide-ranging audience: engineers
using speech recognition systems, researchers involved in ASR
systems and those interested in processing and transmitting speech
such as signal processing and communications communities. It will
also be of interest to technical experts requiring an understanding
of recognition over mobile and IP networks, and postgraduate
students working on robust speech processing.

Table of Content

Forward.

Preface.

1 Introduction.

1.1 Introduction.

1.2 RSR over Digital Channels.

1.3 Organization of the Book.

2 Speech Recognition with HMMs.

2.1 Introduction.

2.2 Some General Issues.

2.3 Analysis of Speech Signals.

2.4 Vector Quantization.

2.5 Approaches to ASR.

2.6 Hidden Markov Models.

2.7 Application of HMMs to Speech Recognition.

2.8 Model Adaptation.

2.9 Dealing with Uncertainty.

3 Networks and Degradation.

3.1 Introduction.

3.2 Mobile and Wireless Networks.

3.3 IP Networks.

3.4 The Acoustic Environment.

4 Speech Compression and Architectures for RSR.

4.1 Introduction.

4.2 Speech Coding.

4.3 Recognition from Decoded Speech.

4.4 Recognition from Codec Parameters.

4.5 Distributed Speech Recognition.

4.6 Comparison between NSR and DSR.

5 Robustness Against Transmission Channel Errors.

5.1 Introduction.

5.2 Channel Coding Techniques.

5.3 Error Concealment (EC).

6 Front-end Processing for Robust Feature Extraction.

6.1 Introduction.

6.2 Noise Reduction Techniques.

6.3 Voice Activity Detection.

6.4 Feature Normalization.

7 Standards for Distributed Speech Recognition.

7.1 Introduction.

7.2 Signal Preprocessing.

7.3 Feature Extraction.

7.4 Feature Compression and Encoding.

7.5 Feature Decoding and Postprocessing.

A Alternative Representations of the LPC
Coefficients.

B Basic Digital Modulation Concepts.

C Review of Channel Coding Techniques.

C.1 Media-independent FEC.

C.2 Interleaving.

Bibliography.

List of Acronyms.

Index.

About the author

Antonio Peinado and Jose Segura are the authors of Speech Recognition Over Digital Channels: Robustness and Standards, published by Wiley.