Speech Emotion Recognition under Noisy Environments with SNR Down to −6 dB Using Multi-Decoder Wave-U-Net
Hyun-Joon Nam,
Hong-June Park
Abstract:A speech emotion recognition (SER) model for noisy environments is proposed, by using four band-pass filtered speech waveforms as the model input instead of the simplified input features such as MFCC (Mel Frequency Cepstral Coefficients). The four waveforms retain the entire information of the original noisy speech while the simplified features keep only partial information of the noisy speech. The information reduction at the model input may cause the accuracy degradation under noisy environments. A normalize… Show more
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