ORCID
- Howard, Ian: 0000-0002-6041-9669
Abstract
This paper describes a neural-net based isolated word recogniser that has a better performance on a standard multi-speaker database than our reference Hidden Markov Model recogniser. The complete neural net recogniser is formed from two parts: a front-end which transforms the complex acoustic specification of the speech into a simplified phonetic feature specification, and a whole-word discriminator net. Each level was trained separately, thus considerably reducing the time necessary to train the overall system.
Publication Date
1989-12-01
Publication Title
IEE Conference Publication
Issue
313
First Page
90
Last Page
94
ISSN
0537-9989
Organisational Unit
School of Engineering, Computing and Mathematics
Recommended Citation
Howard, I., & Huckvale, M. (1989) 'Two-level recognition of isolated word using neural nets', IEE Conference Publication, (313), pp. 90-94. Retrieved from https://pearl.plymouth.ac.uk/secam-research/712
