Phoneme segmentation of speech

In most approaches to speech recognition, the speech signals are segmented using constant-time segmentation, for example into 25 ms blocks. Constant segmentation risks losing information about the phonemes. Different sounds may be merged into single blocks and individual phonemes lost completely. A more satisfactory approach is to attempt to segment the phoneme boundaries from the speech signals and use these boundaries to define blocks. The discrete wavelet transform (DWT) is interesting in the analysis of speech since it is easy to extract parameters which take into account the properties of the human hearing system. The analysis of the power in different frequency bands offers potential for distinguishing the start and end of phonemes. For many boundaries, there is no discernible drop in overall power, and at some frequencies, the power is broadly constant over the lifetime of the phoneme. However, many phonemes exhibit rapid changes in particular subbands which can be used to dete...

• Type: Conference
• Year: 2006
• Where: ICPR
• Authors: Bartosz Ziólko, Suresh Manandhar, Richard C. Wilson
• Keywords: Computer Vision, Constant Segmentation Risks, ICPR 2006, Phoneme Boundaries, Speech Signals