Next: INTRODUCTION
Tony Robinson, John Holdsworth
,
Roy Patterson
and Frank Fallside
Cambridge University Engineering Department, Trumpington Street, Cambridge, England.
Medical Research Council -- Applied Psychology Unit, 15 Chaucer Road, Cambridge, England.
The paper evaluates FFT, filterbank, auditory model and LPC based techniques in the spectral and cepstral domains and adds some simple features such as estimates of the degree of voicing, formant positions and amplitudes. The paper concludes that the features do not make a significant contribution and that the spectral domain representations, independent of their derivation, are better suited to this task. However, we find that the recogniser was relatively insensitive to preprocessor and changes in the architecture and training of the recogniser are more significant.
The current recognition rate on the TIMIT database of 61 symbols is
correct (
including insertion errors) and on a reduced 39 symbol set
the recognition rate is
correct (
). This compares
favourably with the results of other methods, such as Hidden Markov Models,
on the same task.