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• W2020438552 abstract "This paper introduces a new representation of speech that is invariant to noise. The idea is to filter the temporal trajectories of short-time one-sided autocorrelation sequences of speech such that the noise effect is removed. The filtered sequences are denoted by the relative autocorrelation sequences (RASs), and the mel-scale frequency cepstral coefficients (MFCC) are extracted from RAS instead of the original speech. This new speech feature set is denoted as RAS-MFCC. Experiments were conducted on a task of multispeaker isolated Mandarin digit recognition to demonstrate the effectiveness of RAS-MFCC features in the presence of white noise and colored noise. The proposed features are also shown to be superior to other robust representations and compensation techniques." @default.
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• W2020438552 date "1999-05-01" @default.
• W2020438552 modified "2023-10-17" @default.
• W2020438552 title "Robust features for noisy speech recognition based on temporal trajectory filtering of short-time autocorrelation sequences" @default.
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• W2020438552 doi "https://doi.org/10.1016/s0167-6393(99)00004-7" @default.
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