WITHDRAWN: Feature vector extraction model for noisy reverberant speech signal
نویسندگان
چکیده
منابع مشابه
Speech recognition in reverberant and noisy environments employing multiple feature extractors and i-vector speaker adaptation
The REVERB challenge provides a common framework for the evaluation of feature extraction techniques in the presence of both reverberation and additive background noise. State-of-the-art speech recognition systems perform well in controlled environments, but their performance degrades in realistic acoustical conditions, especially in real as well as simulated reverberant environments. In this c...
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Cepstral mean subtraction (CMS), which is a simple long-term bias removal, is used to compensate for transmission and linear xed channel e ects. In order to process the non-linear channel, a two-level CMS was proposed where separate channel compensation is performed for segments that are classi ed as speech and for segments classied as background. In this paper, methods for extending the two-le...
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Previous research has found autocorrelation domain as an appropriate domain for signal and noise separation. This paper discusses a simple and effective method for decreasing the effect of noise on the autocorrelation of the clean signal. This could later be used in extracting mel cepstral parameters for speech recognition. Two different methods are proposed to deal with the effect of error int...
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Corresponding Author: Youssef Zouhir Research Unit: Signals and Mechatronic Systems, SMS, UR13ES49, ENICarthage, University of Carthage, Tunisia Email: [email protected] Abstract: The paper presents a feature extraction method, named as Normalized Gammachirp Cepstral Coefficients (NGCC) that incorporates the properties of the peripheral auditory system to improve robustness in noisy speech ...
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ژورنال
عنوان ژورنال: Informatics in Medicine Unlocked
سال: 2020
ISSN: 2352-9148
DOI: 10.1016/j.imu.2020.100388