Multilingual Phone Recognition in Indian Languages

1. Auflage 2022
ISBN: 978-3-030-80740-5
Verlag: Springer International Publishing

Buch, Englisch, 103 Seiten, Format (B × H): 155 mm x 235 mm, Gewicht: 195 g

Reihe: SpringerBriefs in Speech Technology

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.

Zielgruppe

Research

Autoren/Hrsg.

Manjunath, K. E

Fachgebiete

• Geisteswissenschaften Sprachwissenschaft Computerlinguistik, Korpuslinguistik
• Technische Wissenschaften Elektronik | Nachrichtentechnik Nachrichten- und Kommunikationstechnik Signalverarbeitung
• Mathematik | Informatik EDV | Informatik Informatik Künstliche Intelligenz Spracherkennung, Sprachverarbeitung

Inhaltsverzeichnis

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.

Über Autor(innen)

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 atU 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).