More than a decade has passed since research on automatic recognition of emotion from
speech has become a new field of research in line with its 'big brothers' speech and speaker …

Speaker emotion recognition is achieved through processing methods that include isolation
of the speech signal and extraction of selected features for the final classification. In terms of …

Purpose: Prosody perception is an essential component of speech communication and
social interaction through which both linguistic and emotional information are conveyed …

In this paper, a novel two-branch neural network model structure is proposed for multimodal
emotion recognition, which consists of a time synchronous branch (TSB) and a time …

The search of a small acoustic feature set for emotion recognition faces three main
challenges. Such a feature set must be robust to large diversity of contexts in real-life …

Pattern recognition tasks often face the situation that training data are not fully representative
of test data. This problem is well-recognized in speech recognition, where methods like …

We propose a new methodology, based on proper scoring rules, for the evaluation of the
goodness of pattern recognizers with probabilistic outputs. The recognizers of interest take …

The present study elaborates on the exploitation of both linguistic and acoustic feature
modeling for anger classification. In terms of acoustic modeling we generate statistics from …

Automatic emotion recognition from speech signals without linguistic cues has been an
important emerging research area. Integrating emotions in human–computer interaction is of …

In this paper, we propose novel spectrally weighted mel-frequency cepstral coefficient
(WMFCC) features for emotion recognition from speech. The idea is based on the fact that …