Study of sub-word acoustical models for Kannada isolated word recognition system

Ananthakrishna, T and Kumara, Shama (2016) Study of sub-word acoustical models for Kannada isolated word recognition system. International Journal of Speech Technology, 19 (4). pp. 817-826. ISSN 13812416

[img] PDF
art%3A10.1007%2Fs10772-016-9374-0.pdf - Published Version
Restricted to Registered users only

Download (1MB) | Request a copy
Official URL: http://www.springer.com/engineering/signals/journa...

Abstract

The speech recognition system basically extracts the textual information present in the speech. In the present work, speaker independent isolated word recognition system for one of the south Indian language—Kannada has been developed. For European languages such as English, large amount of research has been carried out in the context of speech recognition. But, speech recognition in Indian languages such as Kannada reported significantly less amount of work and there are no standard speech corpus readily available. In the present study, speech database has been developed by recording the speech utterances of regional Kannada news corpus of different speakers. The speech recognition system has been implemented using the Hidden Markov Tool Kit. Two separate pronunciation dictionaries namely phone based and syllable based dictionaries are built in-order to design and evaluate the performances of phone-level and syllable-level sub-word acoustical models. Experiments have been carried out and results are analyzed by varying the number of Gaussian mixtures in each state of monophone Hidden Markov Model (HMM). Also, context dependent triphone HMM models have been built for the same Kannada speech corpus and the recognition accuracies are comparatively analyzed. Mel frequency cepstral coefficients along with their first and second derivative coefficients are used as feature vectors and are computed in acoustic front-end processing. The overall word recognition accuracy of 60.2% and 74.35 % respectively for monophone and triphone models have been obtained. The study shows a good improvement in the accuracy of isolated-word Kannada speech recognition system using triphone HMM models compared to that of monophone HMM models.

Item Type: Article
Subjects: Engineering > MIT Manipal > Electronics and Communication
Depositing User: Anantha krishna T
Date Deposited: 13 Dec 2016 15:17
Last Modified: 13 Dec 2016 15:17
URI: http://eprints.manipal.edu/id/eprint/147703

Actions (login required)

View Item View Item