Open AccessPhone based acoustic modeling for automatic speech recognition for Punjabi language
Author(s) -
Wiqas Ghai,
Navdeep Singh
Publication year - 2021
Publication title -
journal of speech sciences
Language(s) - English
Resource type - Journals
ISSN - 2236-9740
DOI - 10.20396/joss.v3i1.15040
Subject(s) - computer science , speech recognition , word (group theory) , acoustic model , phone , natural language processing , speech corpus , language model , word recognition , speech processing , artificial intelligence , speech synthesis , linguistics , philosophy , reading (process)
Punjabi language is a tonal language belonging to an Indo-Aryan language family and has a number of speakers all around the world. Punjabi language has gained acceptability in the media & communication and therefore deserves to have a place in the growing field of automatic speech recognition which has been explored already for a number of other Indian and foreign languages successfully. Some work has been done in the field of isolated word speech recognition for Punjabi language, but only using whole word based acoustic models. A phone based approach has yet to be applied for Punjabi language speech recognition. This paper describes an automatic speech recognizer that recognizes isolated word speech and connected word speech using a triphone based acoustic model on the HTK 3.4.1 speech Engine and compares the performance with acoustic whole word model based ASR system. Word recognition accuracy of isolated word speech was 92.05% for acoustic whole word model based system and 97.14% for acoustic triphone model based system whereas word recognition accuracy of connected word speech was 87.75% for acoustic whole word model based system and 91.62% for acoustic triphone model based system.