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2017 | Buch

Introduction Kapitel lesen Erstes Kapitel lesen

Speech Recognition Using Articulatory and Excitation Source Features

verfasst von: K. Sreenivasa Rao, Manjunath K E

Verlag: Springer International Publishing

Buchreihe : SpringerBriefs in Electrical and Computer Engineering

Enthalten in: Springer Professional "Wirtschaft+Technik" , Springer Professional "Technik" , Springer Professional "Wirtschaft"

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SUCHEN

Über dieses Buch

This book discusses the contribution of articulatory and excitation source information in discriminating sound units. The authors focus on excitation source component of speech -- and the dynamics of various articulators during speech production -- for enhancement of speech recognition (SR) performance. Speech recognition is analyzed for read, extempore, and conversation modes of speech. Five groups of articulatory features (AFs) are explored for speech recognition, in addition to conventional spectral features. Each chapter provides the motivation for exploring the specific feature for SR task, discusses the methods to extract those features, and finally suggests appropriate models to capture the sound unit specific knowledge from the proposed features. The authors close by discussing various combinations of spectral, articulatory and source features, and the desired models to enhance the performance of SR systems.

Inhaltsverzeichnis

Frontmatter
Chapter 1. Introduction
Abstract
This chapter provides a brief introduction to the speech recognition systems, types of speech recognition systems, and their applications. The articulatory and excitation source features are briefly described. The significance of articulatory and excitation source features in improving the performance of phone recognition systems (PRSs) is highlighted. Eventually, the objective and scope of the present work is presented.
K. Sreenivasa Rao, Manjunath K.E.
Chapter 2. Literature Review
Abstract
This chapter describes the existing works related to speech recognition. The prior works using the articulatory and excitation source features to improve the performance of speech recognition systems are listed.
K. Sreenivasa Rao, Manjunath K.E.
Chapter 3. Articulatory Features for Phone Recognition
Abstract
This chapter discusses the proposed approaches to derive and use articulatory features (AFs) for phone recognition task. The prediction of AFs for five different AF groups is discussed. The development of tandem and hybrid PRSs using AFs is proposed. The adaptive weighted combination approach used in the development of hybrid PRSs is described in detail. The performance of tandem and hybrid PRSs is evaluated, and the results are analyzed.
K. Sreenivasa Rao, Manjunath K.E.
Chapter 4. Excitation Source Features for Phone Recognition
Abstract
This chapter describes the proposed methods to parameterize the excitation source information for phone recognition task. The development of PRSs using combination of spectral and excitation source features is described. The development of robust PRSs using spectral and excitation source features is discussed. The performance of PRSs is evaluated and results are compared.
K. Sreenivasa Rao, Manjunath K.E.
Chapter 5. Articulatory and Excitation Source Features for Phone Recognition in Read, Extempore and Conversation Modes of Speech
Abstract
This chapter describes the development of PRSs using articulatory and excitation source features for read, extempore, and conversation modes of speech. The performance of PRSs developed using read, extempore, and conversation modes of speech is determined. The results are analyzed by comparing the performance across three modes of speech.
K. Sreenivasa Rao, Manjunath K.E.
Chapter 6. Summary and Conclusion
Abstract
This chapter summarizes the overall contents of the book. Major contributions and future scope of work have been highlighted.
K. Sreenivasa Rao, Manjunath K.E.
Backmatter
Metadaten
Titel
Speech Recognition Using Articulatory and Excitation Source Features
verfasst von
K. Sreenivasa Rao
Manjunath K E
Copyright-Jahr
2017
Electronic ISBN
978-3-319-49220-9
Print ISBN
978-3-319-49219-3
DOI
https://doi.org/10.1007/978-3-319-49220-9

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