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- W2145830023 abstract "In current speech recognition systems mainly Short-Time Fourier Transform based features like MFCC are applied. Dropping the short-time stationarity assumption of the voiced speech, this paper introduces the non-stationary signal analysis into the ASR framework. We present new acoustic features extracted by a pitch-adaptive Gammatone filter bank. The noise robustness was proved on AURORA 2 and 4 tasks, where the proposed features outperform the standard MFCC. Furthermore, successful combination experiments via ROVER indicate the differences between the new features and MFCC." @default.
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- W2145830023 date "2011-05-01" @default.
- W2145830023 modified "2023-10-17" @default.
- W2145830023 title "Non-stationary feature extraction for automatic speech recognition" @default.
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- W2145830023 doi "https://doi.org/10.1109/icassp.2011.5947530" @default.
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