Farhad Ashoftedel

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In recognition of emotional speech, the performance of automatic speech recognition (ASR) systems is degraded significantly. To improve the recognition rate of ASR systems, we can neutralize the Mel-frequency cepstral coefficients (MFCCs) of emotional speech as the most frequently used features in ASR. In this way, the neutralized MFCCs are used in a hidden(More)
In recent four decades, enormous efforts have been focused on developing automatic speech recognition systems to extract linguistic information, but much research is needed to decode the paralinguistic information such as speaking styles and emotion. The effect of using first three normalized formant frequencies and pitch frequency as supplementary features(More)
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