Speech enhancement models suited for speech recognition using composite source and wavelet decomposition model
P.S. Rajakumar, Shambhavi Bangalore Ravi, R. M. Suresh
Abstract
P.S. Rajakumar, Shambhavi Bangalore Ravi, R. M. Suresh
Abstract
To compare the performance of two speech coders, it is necessary to have some indicator of the intelligibility and quality of the speech produced by each coder. The term intelligibility usually refers to whether the output speech is easily understandable, while the term quality is an indicator of how natural the speech sounds. It is possible for a coder to produce highly intelligible speech from low quality, in that the speech may sound very machine-like and the speaker is not identifiable. On the other hand, it is unlikely that unintelligible speech would be called high quality, but there are situations in which perceptually pleasing speech does not have high intelligibility. In this paper the most common measures of speech enhancement models suited for speech recognition with specific emphasis on wavelet based approach are presented.
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To compare the performance of two speech coders, it is necessary to have some indicator of the intelligibility and quality of the speech produced by each coder. The term intelligibility usually refers to whether the output speech is easily understandable, while the term quality is an indicator of how natural the speech sounds. It is possible for a coder to produce highly intelligible speech from low quality, in that the speech may sound very machine-like and the speaker is not identifiable. On the other hand, it is unlikely that unintelligible speech would be called high quality, but there are situations in which perceptually pleasing speech does not have high intelligibility. In this paper the most common measures of speech enhancement models suited for speech recognition with specific emphasis on wavelet based approach are presented.
Key concepts: Intelligibility (philosophy), Speech recognition, Computer science, Speech enhancement, Speech processing, Voice activity detection, Speech coding, Linear predictive coding