| Paper: | SP-L5.1 | ||
| Session: | Pitch and Tone Based Speech Analysis | ||
| Time: | Thursday, May 20, 09:30 - 09:50 | ||
| Presentation: | Lecture | ||
| Topic: | Speech Processing: Speech Analysis | ||
| Title: | PITCH PREDICTION FROM MFCC VECTORS FOR SPEECH RECONSTRUCTION | ||
| Authors: | Xu Shao; University of East Anglia | ||
| Ben Milner; University of East Anglia | |||
| Abstract: | This work proposes a technique for reconstructing an acoustic speech signal solely from a stream of mel-frequency cepstral coefficients (MFCCs). Previous speech reconstruction methods have required an additional pitch element, but this work proposes two maximum a posteriori (MAP) methods for predicting pitch from the MFCC vectors themselves. The first method is based on a Gaussian mixture model (GMM) while the second scheme utilises the temporal correlation available from a hidden Markov model (HMM) framework. A formal measurement of both frame classification accuracy and RMS pitch error shows that an HMM-based scheme with 5 clusters per state is able to correctly classify over 94% of frames and has an RMS pitch error of 3.1Hz in comparison to a reference pitch. Informal listening tests and analysis of spectrograms reveals that speech reconstructed solely from the MFCC vectors is almost indistinguishable from that using the reference pitch. | ||
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