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Multi-resolution modulation-filtered cochleagram feature for LSTM-based dimensional emotion recognition from speech

Neural Networks, 2021
Continuous dimensional emotion recognition from speech helps robots or virtual agents capture the temporal dynamics of a speaker's emotional state in natural human-robot interactions. Temporal modulation cues obtained directly from the time-domain model of auditory perception can better reflect temporal dynamics than the acoustic features usually ...
Zhichao Peng   +2 more
exaly   +3 more sources

Learning Emotion Information for Expressive Speech Synthesis Using Multi-resolution Modulation-filtered Cochleagram

2022 Asia-Pacific Signal and Information Processing Association Annual Summit and Conference (APSIPA ASC), 2022
Masashi Unoki
exaly   +2 more sources

Cochleagram to Recognize Dysphonia: Auditory Perceptual Analysis for Health Informatics [PDF]

open access: yesIEEE Access
The spectral images provide the dynamic characteristics of the voice signal in the time and frequency domains. However, extracting the predominant spectral features from the voice samples is still challenging.
Rumana Islam   +2 more
exaly   +4 more sources

Improved Speech Activity Detection Using Cochleagram Spectral Basis by Nonnegative Matrix Factorization

Lecture Notes in Electrical Engineering, 2022
Sujoy Mondal, Abhirup Das Barman
exaly  

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