Name
Title | ||
|---|---|---|
The Representation Of Speech In A Nonlinear Auditory Model: Time-Domain Analysis Of Simulated Auditory-Nerve Firing Patterns |
Abstract | ||
|---|---|---|
A nonlinear auditory model is appraised in terms of its ability to encode speech formant frequencies in the fine time structure of its output. It is demonstrated that groups of model auditory nerve (AN) fibres with similar interpeak intervals accurately encode the resonances of synthetic three-formant syllables, in close agreement with physiological data. Acoustic features are derived from the interpeak intervals and used as the input to a hidden Markov model-based automatic speech recognition system. In a digits-in-noise recognition task, interval-based features gave a better performance than features based on AN firing rate at every signal-to-noise ratio tested. |
Year | Venue | Keywords |
|---|---|---|
2011 | 12TH ANNUAL CONFERENCE OF THE INTERNATIONAL SPEECH COMMUNICATION ASSOCIATION 2011 (INTERSPEECH 2011), VOLS 1-5 | auditory model, time interval, automatic speech recognition |
Field | DocType | Citations |
Time domain,ENCODE,Nonlinear system,Pattern recognition,Computer science,Speech recognition,Artificial intelligence,Formant,Hidden Markov model | Conference | 0 |
PageRank | References | Authors |
0.34 | 2 | 5 |
Name | Order | Citations | PageRank |
|---|---|---|---|
| Guy J. Brown | 1 | 760 | 97.54 |
| Tim Jürgens | 2 | 0 | 0.34 |
| Ray Meddis | 3 | 53 | 6.98 |
| Matthew Robertson | 4 | 0 | 0.34 |
| Nicholas R. Clark | 5 | 14 | 1.55 |