Pitch dependent phone modelling for HMM based speech recognition
H. Singer, Shigeki Sagayama · 1992
The authors propose a novel method of incorporating pitch information into a hidden Markov model (HMM) phoneme recognizer by exploiting the correlation between pitch and spectral parameters, e.g. cepstrum. Pitch patterns are not used explicitly; instead, spectral parameters are normalized framewise according to the pitch value. Evidence is given to show that the use of pitch information consistently improves the recognition performance. Experiments with 24 phoneme labels showed that the phoneme error rate for fast continuous speech could be improved by about 10%.>