| dc.contributor.author |
Kannan, Balakrishnan |
|
| dc.contributor.author |
Cini, Kurian |
|
| dc.date.accessioned |
2014-07-22T05:03:59Z |
|
| dc.date.available |
2014-07-22T05:03:59Z |
|
| dc.date.issued |
2009-12-09 |
|
| dc.identifier.uri |
http://dyuthi.cusat.ac.in/purl/4190 |
|
| dc.description |
Nature & Biologically Inspired Computing, 2009. NaBIC 2009. World Congress on |
en_US |
| dc.description.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. |
en_US |
| dc.description.sponsorship |
Cochin University of Science & Technology |
en_US |
| dc.language.iso |
en |
en_US |
| dc.publisher |
IEEE |
en_US |
| dc.subject |
Digit speech recognition |
en_US |
| dc.subject |
automatic data entry |
en_US |
| dc.subject |
PIN entry |
en_US |
| dc.subject |
Mel frequency cepstrum coefficient (MFCC) |
en_US |
| dc.subject |
Hidden Markov model (HMM) |
en_US |
| dc.title |
Speech Recognition of Malayalam Numbers |
en_US |
| dc.type |
Article |
en_US |