The automatic recognition and classification of speech under stress has applications in behavioural and mental health sciences, human to machine ...

These studies use information such as changes in pitch, frequency, and energy of speech to determine whether the subject is stressed [40], [41]. He et al. [42] ...

The speech was classified into two classes: neutral and stressed and the best overall performance was observed for the features extracted using TEO analysis ...

The automatic recognition and classification of speech under stress has applications in behavioural and mental health sciences, human to machine ...

TL;DR: It is observed that wavelets concentrate speech energy into bands which differentiate between voiced or unvoiced speech, and it is shown that the Battle- ...

The automatic recognition and classification of speech under stress has applications in behavioural and mental health sciences, human to machine ...

Bibliographic details on Recognition of stress in speech using wavelet analysis and Teager energy operator.

Oct 11, 2023 · A stressed speech emotion recognition (SSER) system is developed using TEO-Auto-Env and spectral feature combination for detecting the emotions.

We propose a wavelet packet coefficient model in speech emotion recognition. The wavelet packet coefficients at five decomposition levels are analyzed and used ...

Oct 11, 2023 · A stressed speech emotion recognition (SSER) system is developed using TEO-Auto-Env and spectral feature combination for detecting the emotions.