Time-based clustering for phonetic segmentation

The paper describes an approach to speech segmentation. Unlike approaches based on spectral measurements, the algorithm iteratively clusters on an LPC representation of time waveform blocks. The algorithm uses a generalized maximum likelihood criterion for deciding when two neighboring pieces of the signal should be joined. The paper describes the algorithm and shows that it yields superior results when compared to metrics based on spectral or cepstral measurements