Titlebook: Robustness in Automatic Speech Recognition; Fundamentals and App Jean-Claude Junqua,Jean-Paul Haton Book 1996 Springer Science+Business Med

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描繪

0893-3405 e excitement in the late seventies when Texas Instruments came up with a toy named "Speak-and-Spell" which was based on a VLSI chip containing the state-of-the-art linear prediction synthesizer. This caused a speech technology fever among the electronics industry. Particularly. applications of autom

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Processes

Nature and Perception of Speech Soundswe also emphasize the influence of noise on speech production and perception. By introducing basic characteristics of speech sounds and how they are produced and perceived, we intend to provide the essential knowledge needed to understand the following chapters.

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碎石頭

Towards Robust Speech Analysis especially successful in noise conditions, are detailed. Together with their description, their application to ASR is also summarized. Finally, the field of robust spectral estimation and ARMA modeling is outlined.

就職

On the Use of a Robust Speech Representationion techniques, and modeling in the autocorrelation domain for robust ASR. We conclude the chapter by summarizing the work done on cepstral liftering and robust distance and similarity measures which have to be tightly integrated with the feature extraction module to yield a robust speech representation.

六邊形

Spontaneous Speechtion of possible interfaces between ASR and natural language processing together with a section on language modeling. We conclude this chapter by presenting current trends in robust parsing and interpretation of speech.

SPASM

On the use of Knowledge in ASResenting several hybrid approaches for ASR, we focus on models developed for the cooperation between knowledge sources. Then, we present deductive and abductive reasoning techniques currently used in knowledge-based approaches. We conclude this chapter by presenting an illustration of the application of hypothetical reasoning to ASR.