Feature extraction and representation has significant impact on the performance of any
machine learning method. Mel Frequency Cepstrum Coefficient (MFCC) is designed to …

User emotional status recognition is becoming a key feature in advanced Human Computer
Interfaces (HCI). A key source of emotional information is the spoken expression, which may …

Cardiovascular disease is the leading cause of death in the world, and its early detection is
a key to improving long-term health outcomes. The auscultation of the heart is still an …

Speech emotion recognition (SER) has recently been receiving increased interest due to the
rapid advancements in affective computing and human computer interaction. English …

Video-to-speech is the process of reconstructing the audio speech from a video of a spoken
utterance. Previous approaches to this task have relied on a two-step process where an …

A tremendous research is being done on Speech Emotion Recognition (SER) in the recent
years with its main motto to improve human machine interaction. In this work, the effect of …

A new architecture of intelligent audio emotion recognition is proposed in this paper. It fully
utilizes both prosodic and spectral features in its design. It has two main paths in parallel …

This article analyses research in speech emotion recognition (“SER”) from 2006 to 2017 in
order to identify the current focus of research, and areas in which research is lacking. The …

Generating 3D dance motions that are synchronized with music is a difficult task, as it
involves modeling the complex interplay between musical rhythms and human body …

In this paper, a novel feature fusion of Teager Energy Operator (TEO) and Mel Frequency
Cepstral Coefficients (MFCC), as Teager-MFCC (T-MFCC) feature extraction technique, is …