Robust automatic time alignment of orthographic transcriptions with unconstrained speech

Abstract
A method for automatic time alignment of orthographically transcribed speech using supervised speaker-independent automatic speech recognition based on the orthographic transcription, an online dictionary, and HMM phone models is presented. This method successfully aligns transcriptions with speech in unconstrained 5 to 10 min conversations collected over long-distance telephone lines. It requires minimal manual processing and generally produces correct alignments despite the challenging nature of the data. The robustness and efficiency of the method make it a practical tool for very large speech corpora.

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