Titlebook: Robust Emotion Recognition using Spectral and Prosodic Features; K. Sreenivasa Rao,Shashidhar G. Koolagudi Book 2013 The Author(s) 2013 Sp

GENUS

音乐学者

Robust Emotion Recognition using Pitch Synchronous and Sub-syllabic Spectral Features,cy cepstral coefficients (MFCC) are used as the correlates of vocal tract information. In addition to LPCCs and MFCCs, formant related features are also explored in this work for recognizing emotions from speech. Extraction of the above mentioned spectral features is discussed in brief. Further extr

粗糙

Robust Emotion Recognition using Sentence, Word and Syllable Level Prosodic Features,nize the emotions is illustrated using the gross statistics and time varying patterns of prosodic parameters. Prosodic correlates of speech such as energy, duration and pitch parameters are computed from the emotional utterances. Global prosodic features representing the gross statistics of prosody

anesthesia

仲裁者

discord

Emotion Recognition on Real Life Emotions,ns with reasonable accuracy. From the literature it is observed that combination of different features improves the classification performance. In this chapter score level combination of different features has been studied for recognizing real life emotions. For modelling real life emotions, there i

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cortex

易弯曲

小步舞