Speech Emotion Recognition using Neural Networks
CH. Deepika1, P. Swetha2
1CH. Deepika, Assistant Professor, Vidya Jyothi Institute of Technology Aziz Nagar, Hyderabad (Telangana), India.
2P. Swetha, Assistant Professor, VJIT, Aziz Nagar, Hyderabad (Telangana), India.
Manuscript received on 19 October 2019 | Revised Manuscript received on 25 October 2019 | Manuscript Published on 02 November 2019 | PP: 3519-3522 | Volume-8 Issue-2S11 September 2019 | Retrieval Number: B14320982S1119/2019©BEIESP | DOI: 10.35940/ijrte.B1432.0982S1119
Open Access | Editorial and Publishing Policies | Cite | Mendeley | Indexing and Abstracting
© The Authors. Blue Eyes Intelligence Engineering and Sciences Publication (BEIESP). This is an open access article under the CC-BY-NC-ND license (http://creativecommons.org/licenses/by-nc-nd/4.0/)
Abstract: Emotion recognition is a procedure to identify the human emotion, the identification criteria may be facial expression analysis or may be verbal expression. Emotion plays a vital role in all aspects of cognitive learning processes. Identification of emotion from human expressions is a trending research topic in human computer interaction (HCI). Speech emotion recognition is one the area which can be used to identify the emotions from verbal expression of human. Speech Emotion recognition also become a main research topic in human computer interaction studies. In recent times, the attention of researchers was increased to study the emotional content of speech and verbal expressions. Implementation of Speech Emotion Recognition may involve several learning models, classification methods, feature extraction and pattern recognition. We reviewed many numbers of research articles, major challengesand applications of speech emotion recognition. At present many emotional speech databases and recognition applications are developed for research and development purpose. The results, limitations and performance of current speech emotion recognition system is based on different classifiers are discussed.
Keywords: Speech Emotion Recognition, Emotional Speech Databases, Emotion Classification, Feature Extraction.
Scope of the Article: Pattern Recognition