Robust Feature Extraction Using Autocorrelation Domain for Noisy Speech Recognition
نویسندگان
چکیده
منابع مشابه
Robust Feature Extraction Using Autocorrelation Domain for Noisy Speech Recognition
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: Signal & Image Processing : An International Journal
سال: 2017
ISSN: 2229-3922,0976-710X
DOI: 10.5121/sipij.2017.8103