Audio segmentation for speech recognition using segment features

Audio segmentation is an essential preprocessing step in several audio processing applications with a significant impact e.g. on speech recognition performance. We introduce a novel framework which combines the advantages of different well known segmentation methods. An automatically estimated log-linear segment model is used to determine the segmentation of an audio stream in a holistic way by a maximum a posteriori decoding strategy, instead of classifying change points locally. A comparison to other segmentation techniques in terms of speech recognition performance is presented, showing a promising segmentation quality of our approach.

• Type: Conference
• Year: 2009
• Where: ICASSP
• Authors: David Rybach, Christian Gollan, Ralf Schlüter, Hermann Ney
• Keywords: Audio Segmentation, ICASSP 2009, Segmentation Methods, Signal Processing, Speech Recognition Performance