Tag Archives: MFCC

Information Retrieval Publications Speech Processing Speech Recognition

PNCC features for ASR robustness enhancement

The acoustic features traditionally used in Speech and Audio Processing are MFCC and PLP. However, one important thing in designing an acoustic signal fingerprint is to use a robust feature. Consequently, several techniques aim to enhance MFCC and PLP by using for example, mean and variance normalization, variance normalization or RASTA filtering and variance normalization in the particular case of PLP.  Here, we present a new type of acoustic feature which directly implements a noise reduction algorithm: Power Normalised Cepstral Coefficients (PNCC) introduced by Chanwoo Kim [1]. This feature is more robust against background noise than the traditional features PLP and MFCC.

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Information Retrieval Machine Learning Publications Speech Recognition

Automatic Speech Recognition (ASR)

ASR aims to transcribe an unknown speech signal into text. This textual information can later be processed by a text mining system in order to spot essential keywords amongst the information provided by the input speech signal.

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