Muharram Mansoorizadeh

Muharram Mansoorizadeh Tarbiat Modarres University

Key research interests: Audiovisual Emotion Recognition

Speech Emotion Recognition: Comparison of Speech Segmentation Approaches

Recognition of emotional states carried in speech, is of a great interest in modern human computer interaction developments. To reliably detect the aroused emotion, a sufficiently long continuous speech segment is required. This research aims to analyze different segmentation approaches of speech signals. Berlin emotional speech database is used for data set generation. Time frame based and voiced segmentation approaches are applied and compared. The experimental results show that accurate emotion recognition is obtained when the speech segments are longer than a second or are composed of 10 to 12 voiced segments. Based on the findings of this research, voiced based segmentation generates more accurate results than the other methods

Audio-Visual Emotion Database in Persian Language

I'm creating an audio-visual emotion database in Persian language. currently, recording phase is complete and audio/speech data is archived as digital streams. Clipping and annotation has just began.

Sample clip from the audio-visual emotion database

The subject acts like a man enjoying the blue sky.

The Database

The Database

Facial Feature Localization(includes demo)

I've developed some MATLAB(R) scripts for facial feature localization. The included clip is a demo of scripts in action. I'm looking for guidelines to pack and publish the scripts so that it can be used by others.

Face and Facial Feature Tracking

Here are some initial results of facial feature tracking.