Knowledge Based Approach to Speech Recognition
نویسنده
چکیده
This paper presents a knowledge/rule based approach to continuous speech recognition. The proposed recognition system (Samouelian, 1994) uses a data driven methodology, where the knowledge about the structure and characteristics of the speech signal is captured explicitly from the database by the use of inductive inference (C4.5) (Quinlan, 1986). This allows the integration of features from existing signal processing techniques, that are currently used in HMM stochastic modelling, and acoustic-phonetic features, which have been the cornerstone of traditional knowledge based techniques. Phoneme recognition results on the phonetic classes of plosives, semivowels and nasals for a combination of feature sets, for speaker dependent and independent recognition, are presented.
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روشی جدید در بازشناسی مقاوم گفتار مبتنی بر دادگان مفقود با استفاده از شبکه عصبی دوسویه
Performance of speech recognition systems is greatly reduced when speech corrupted by noise. One common method for robust speech recognition systems is missing feature methods. In this way, the components in time - frequency representation of signal (Spectrogram) that present low signal to noise ratio (SNR), are tagged as missing and deleted then replaced by remained components and statistical ...
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