Multilingual Phone Recognition in Indian Languages
The book presents current research and developments in multilingual speech recognition. The author presents a Multilingual Phone Recognition System (Multi-PRS), developed using a common multilingual phone-set derived from the International Phonetic Alphabets (IPA) based transcription of six Indian languages - Kannada, Telugu, Bengali, Odia, Urdu, and Assamese. The author shows how the performance of Multi-PRS can be improved using tandem features. The book compares Monolingual Phone Recognition Systems (Mono-PRS) versus Multi-PRS and baseline versus tandem system. Methods are proposed to predict Articulatory Features (AFs) from spectral features using Deep Neural Networks (DNN). Multitask learning is explored to improve the prediction accuracy of AFs. Then, the AFs are explored to improve the performance of Multi-PRS using lattice rescoring method of combination and tandem method of combination. The author goes on to develop and evaluate the Language Identification followed by Monolingual phone recognition (LID-Mono) and common multilingual phone-set based multilingual phone recognition systems.

"1140288869"
Multilingual Phone Recognition in Indian Languages
The book presents current research and developments in multilingual speech recognition. The author presents a Multilingual Phone Recognition System (Multi-PRS), developed using a common multilingual phone-set derived from the International Phonetic Alphabets (IPA) based transcription of six Indian languages - Kannada, Telugu, Bengali, Odia, Urdu, and Assamese. The author shows how the performance of Multi-PRS can be improved using tandem features. The book compares Monolingual Phone Recognition Systems (Mono-PRS) versus Multi-PRS and baseline versus tandem system. Methods are proposed to predict Articulatory Features (AFs) from spectral features using Deep Neural Networks (DNN). Multitask learning is explored to improve the prediction accuracy of AFs. Then, the AFs are explored to improve the performance of Multi-PRS using lattice rescoring method of combination and tandem method of combination. The author goes on to develop and evaluate the Language Identification followed by Monolingual phone recognition (LID-Mono) and common multilingual phone-set based multilingual phone recognition systems.

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Multilingual Phone Recognition in Indian Languages

Multilingual Phone Recognition in Indian Languages

by K.E Manjunath
Multilingual Phone Recognition in Indian Languages

Multilingual Phone Recognition in Indian Languages

by K.E Manjunath

eBook1st ed. 2022 (1st ed. 2022)

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Overview

The book presents current research and developments in multilingual speech recognition. The author presents a Multilingual Phone Recognition System (Multi-PRS), developed using a common multilingual phone-set derived from the International Phonetic Alphabets (IPA) based transcription of six Indian languages - Kannada, Telugu, Bengali, Odia, Urdu, and Assamese. The author shows how the performance of Multi-PRS can be improved using tandem features. The book compares Monolingual Phone Recognition Systems (Mono-PRS) versus Multi-PRS and baseline versus tandem system. Methods are proposed to predict Articulatory Features (AFs) from spectral features using Deep Neural Networks (DNN). Multitask learning is explored to improve the prediction accuracy of AFs. Then, the AFs are explored to improve the performance of Multi-PRS using lattice rescoring method of combination and tandem method of combination. The author goes on to develop and evaluate the Language Identification followed by Monolingual phone recognition (LID-Mono) and common multilingual phone-set based multilingual phone recognition systems.


Product Details

ISBN-13: 9783030807412
Publisher: Springer-Verlag New York, LLC
Publication date: 10/05/2021
Series: SpringerBriefs in Speech Technology
Sold by: Barnes & Noble
Format: eBook
File size: 4 MB

About the Author

Dr. Manjunath K E received his PhD in multilingual speech recognition from International Institute of Information Technology, Bangalore, India, and his MS in automatic speech recognition from Indian Institute of Technology, Kharagpur, India. Currently, he works as Scientist at U R Rao Satellite Centre, Indian Space Research Organisation (ISRO). He has published in several international conferences and journals. He has co-authored the book “Speech recognition using Articulatory and Excitation Source Features” (Springer 2017).

Table of Contents

1. Introduction.-  2. Literature review.- 3. Development and analysis of Multilingual Phone recognition system.- 4. Prediction of Multilingual Articulatory Features.- 5. Articulatory Features of Multilingual Phone recognition.- 6. Applications of Multilingual Phone recognition in Code-switched and Non-code-switched Scenarios.- 7. Summary and Conclusion.

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