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Titolo:
Automatic recognition and understanding of spoken language - A first step toward natural human-machine communication
Autore:
Juang, BH; Furui, S;
Indirizzi:
Lucent Technol Inc, Murray Hill, NJ 07974 USA Lucent Technol Inc Murray Hill NJ USA 07974 nc, Murray Hill, NJ 07974 USA Tokyo Inst Technol, Tokyo 1528552, Japan Tokyo Inst Technol Tokyo Japan 1528552 nst Technol, Tokyo 1528552, Japan
Titolo Testata:
PROCEEDINGS OF THE IEEE
fascicolo: 8, volume: 88, anno: 2000,
pagine: 1142 - 1165
SICI:
0018-9219(200008)88:8<1142:ARAUOS>2.0.ZU;2-T
Fonte:
ISI
Lingua:
ENG
Soggetto:
HIDDEN MARKOV-MODELS; SPEECH RECOGNITION; WORD RECOGNITION; ALGORITHM;
Keywords:
acoustic modeling; acoustic-phonetics; articulation; automatic recognition and understanding; Bayes risk; cepstral distance; continuous speech recognition; detection-based approach; dialogue systems; discriminative training; dynamic programming; finite state machine; forward-backward algorithm; generalized phone models; grammar; hidden Markov models; human-machine communication; isolated word recognition; language modeling; language structure; linear prediction; maximum a posteriori maximum-likelihood estimation; noise; perplexity; probability distribution of speech; pronunciation modeling; robustness; search algorithms; short-time spectral analysis; signal analysis; speech dictation; speech distortion; speech representations; spoken language processing technology; statistical language processing; statistical pattern recognition;
Tipo documento:
Article
Natura:
Periodico
Settore Disciplinare:
Engineering, Computing & Technology
Citazioni:
53
Recensione:
Indirizzi per estratti:
Indirizzo: Juang, BH Lucent Technol Inc, Murray Hill, NJ 07974 USA Lucent Technol Inc Murray Hill NJ USA 07974 Hill, NJ 07974 USA
Citazione:
B.H. Juang e S. Furui, "Automatic recognition and understanding of spoken language - A first step toward natural human-machine communication", P IEEE, 88(8), 2000, pp. 1142-1165

Abstract

The promise of a powerful computing device to help people in productivity as well as in recreation can only be realized with proper human-machine communication. Automatic recognition and understanding of spoken language is the first and probably the most important step toward natural human-machine interaction. Research in this fascinating field in the past few decades hasproduced remarkable results, leading to many exciting expectations as wellas new challenges. In this paper, we summarize the development of the spoken language technology from both a vertical (the chronology) and a horizontal (the spectrum of technical approaches) perspective. We highlighted the introduction of statistical methods in dealing with language-related problems as it represents a paradigm shift in the research field of spoken language processing. Statistical methods are designed to allow the machine to learn, directly from data, structure regularities in the speech signal for the purpose of automatic speech recognition and understanding. Today, research results in spoken language processing have led to a number of successful applications ranging from dictation software for personal computers and telephone-call processing systems for automatic call routing to automatic subcaptioning for television broadcast. We analyze the technical successes that support these applications. Along with an assessment of the state-of-the-artin this board technical field, we also discuss the limitations of the current technology can be presented as the basis to inspire future advances.

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Documento generato il 21/09/20 alle ore 15:53:50