Abstract
In this paper, we focus on the design of an AUTOCFGPROCESSOR procedure to automatically create and tune context free grammars (CFGs) for directed dialog speech applications without the use of any domain specific text corpora. A reranking mechanism is used to post-process the large vocabulary continuous speech recognizer (LVCSR) n-best lists with additional phonetic and higher level linguistic knowledge for transcribing the user utterances with improved word error rate (WER). We also depict the classification of LVCSR transcriptions into semantic categories and the use of a statistical filtering mechanism on the valid LVCSR-transcriptions for the CFG creation and tuning tasks. We also illustrate the importance of the additional improvements gained by using semantic classification strength in a feedback loop to the transcription mechanism.
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