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date: 09 December 2018

Abstract and Keywords

Speech recognition is concerned with converting the speech waveform, an acoustic signal, into a sequence of words. Today's approaches are based on a statistical modellization of the speech signal. This article provides an overview of the main topics addressed in speech recognition, which are, acoustic-phonetic modelling, lexical representation, language modelling, decoding, and model adaptation. Language models are used in speech recognition to estimate the probability of word sequences. The main components of a generic speech recognition system are, main knowledge sources, feature analysis, and acoustic and language models, which are estimated in a training phase, and the decoder. The focus of this article is on methods used in state-of-the-art speaker-independent, large-vocabulary continuous speech recognition (LVCSR). Primary application areas for such technology are dictation, spoken language dialogue, and transcription for information archival and retrieval systems. Finally, this article discusses issues and directions of future research.

Keywords: speech recognition, statistical modellization, speech signal, language models, dictation, spoken language dialogue, large-vocabulary continuous speech recognition

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