Robust Time-synchronous Environmenta Speech Recognition
نویسنده
چکیده
In this paper we describe system architectures for robust MLLR based environmental adaptation of continuous speech recognition systems. Inspired by an existing broadcast news transcription system [1] we refined the identification of acoustic scenarios by using a combined GMM/HMM method. Thus environmental adaptation regarding arbitrary acoustic scenarios beyond speaker changes becomes possible. For deploying acoustic adaptation in interactive applications, such as human machine interaction, a time-synchronous adaptation approach is proposed. For different corpora the evaluation of our approaches shows significant improvements in recognition accuracy while satisfying the constraint of timesynchronous processing.
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