ISCA Archive Interspeech 2006
ISCA Archive Interspeech 2006

Single frame selection for phoneme classification

Tingyao Wu, Dirk Van Compernolle, Jacques Duchateau, Hugo Van hamme

Our former study [1] has shown that maximum likelihood (ML) based frame selection, which selects reliable frames from a high resolution along the time axis, helps to improve the discrimination between phonemes. In this paper, we present our recent research on single frame selection for a phoneme classification task. A new single selection, which only selects one frame for one state in an Hidden Markov Model (HMM), is proposed. The new technique takes likelihoods of frames and their positions in a phoneme segment into account at the same time, and selects very few frames to represent the spectral evolution of the phoneme. Furthermore, we also show that for a low model complexity, a phoneme model trained by selected frames is more discriminative than a model using all frames.

doi: 10.21437/Interspeech.2006-229

Cite as: Wu, T., Compernolle, D.V., Duchateau, J., Van hamme, H. (2006) Single frame selection for phoneme classification. Proc. Interspeech 2006, paper 1247-Mon3CaP.2, doi: 10.21437/Interspeech.2006-229

  author={Tingyao Wu and Dirk Van Compernolle and Jacques Duchateau and Hugo {Van hamme}},
  title={{Single frame selection for phoneme classification}},
  booktitle={Proc. Interspeech 2006},
  pages={paper 1247-Mon3CaP.2},