Speech recognition of Malayalam numbers

Author

Kurian, Cini ; Balakrishnan, Kannan

Author_Institution

Dept. of Comput. Applic., Cochin Univ. of Sci. & Technol., Cochin, India

fYear

2009

fDate

9-11 Dec. 2009

Firstpage

1475

Lastpage

1479

Abstract

Digit speech recognition is important in many applications such as automatic data entry, PIN entry, voice dialing telephone, automated banking system, etc. This paper presents speaker independent speech recognition system for Malayalam digits. The system employs Mel frequency cepstrum coefficient (MFCC) as feature for signal processing and hidden Markov model (HMM) for recognition. The system is trained with 21 male and female voices in the age group of 20 to 40 years and there was 98.5% word recognition accuracy (94.8% sentence recognition accuracy) on a test set of continuous digit recognition task.

Keywords

hidden Markov models; speaker recognition; Malayalam numbers; Mel frequency cepstrum coefficient; PIN entry; automated banking system; automatic data entry; digit speech recognition; hidden Markov model; signal processing; speaker independent speech recognition system; voice dialing telephone; Artificial neural networks; Automatic speech recognition; Databases; Hidden Markov models; Management training; Natural languages; Speech recognition; Support vector machine classification; Support vector machines; Telephony;

fLanguage

English

Publisher

ieee

Conference_Titel

Nature & Biologically Inspired Computing, 2009. NaBIC 2009. World Congress on

Conference_Location

Coimbatore

Print_ISBN

978-1-4244-5053-4

Type

conf

DOI

10.1109/NABIC.2009.5393692

Filename

5393692