ISCA Archive Interspeech 2009
ISCA Archive Interspeech 2009

Reconstructing clean speech from noisy MFCC vectors

Ben Milner, Jonathan Darch, Ibrahim Almajai

The aim of this work is to reconstruct clean speech solely from a stream of noise-contaminated MFCC vectors, as may be encountered in distributed speech recognition systems. Speech reconstruction is performed using the ETSI Aurora back-end speech reconstruction standard which requires MFCC vectors, fundamental frequency and voicing information. In this work, fundamental frequency and voicing are obtained using maximum a posteriori prediction from input MFCC vectors, thereby allowing speech reconstruction solely from a stream of MFCC vectors. Two different methods to improve prediction accuracy in noisy conditions are then developed. Experimental results first establish that improved fundamental frequency and voicing prediction is obtained when noise compensation is applied. A series of human listening tests are then used to analyse the reconstructed speech quality, which determine the effectiveness of noise compensation in terms of mean opinion scores.

doi: 10.21437/Interspeech.2009-572

Cite as: Milner, B., Darch, J., Almajai, I. (2009) Reconstructing clean speech from noisy MFCC vectors. Proc. Interspeech 2009, 1943-1946, doi: 10.21437/Interspeech.2009-572

  author={Ben Milner and Jonathan Darch and Ibrahim Almajai},
  title={{Reconstructing clean speech from noisy MFCC vectors}},
  booktitle={Proc. Interspeech 2009},