Toward Robust Speech Recognition and Understanding

Abstract

AbstractThis paper overviews robust architecture and modeling techniques for automatic recognition and understanding. The topics include robust acoustic and language modeling for spontaneous speech recognition, unsupervised adaptation of acoustic and language models, robust architecture for spoken dialogue systems, multi-modal speech recognition, and speech understanding. This paper also discusses the most important research problems to be solved in order to achieve ultimate robust speech recognition and understanding systems.KeywordsSpeech RecognitionLanguage ModelAutomatic Speech RecognitionSpontaneous SpeechMaximum Likelihood Linear RegressionThese keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.