JOINT SEGMENTING AND AUTOMATIC SPEECH RECOGNITION

Abstract

A joint segmenting and ASR model (200) includes an encoder (220) and decoder (260). The encoder configured to: receive acoustic frames (110) characterizing one or more utterances (106); and generate, at each output step, a higher order feature representation (224) for a corresponding acoustic frame. The decoder configured to: receive the higher order feature representation (224) and generate, at each output step: a probability distribution (242) over possible speech recognition hypotheses, and an indication (212) of whether the corresponding output step corresponds to an end of speech segment. The joint segmenting and ASR model trained on a set of training samples each including: audio data characterizing a spoken utterance; and a corresponding transcription of the spoken utterance, the corresponding transcription having an end of speech segment ground truth token inserted into the corresponding transcription automatically based on a set of heuristic-based rules and exceptions applied to the training sample.

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