Publication date: Available online 10 January 2019Source: Speech CommunicationAuthor(s): Shamima Najnin, Bonny BanerjeeAbstractThough speech recognition has been widely investigated in the past decades, the role of articulation in recognition has received scant attention. Recognition accuracy increases when recognizers are trained with acoustic features in conjunction with articulatory ones. Traditionally, acoustic features are represented by mel-frequency cepstral coefficients (MFCCs) while articulatory features are represented by the locations or trajectories of the articulators. We propose the articulatory cepstral coefficients (ACCs) as features which are the cepstral coefficients of the time-location articulatory signal. We show that ACCs yield state-of-the-art results in phoneme clas...
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