INTERNATIONAL JOURNAL OF NOVEL RESEARCH AND DEVELOPMENT International Peer Reviewed & Refereed Journals, Open Access Journal ISSN Approved Journal No: 2456-4184 | Impact factor: 8.76 | ESTD Year: 2016
Scholarly open access journals, Peer-reviewed, and Refereed Journals, Impact factor 8.76 (Calculate by google scholar and Semantic Scholar | AI-Powered Research Tool) , Multidisciplinary, Monthly, Indexing in all major database & Metadata, Citation Generator, Digital Object Identifier(DOI)
Communication is an integral part of the human social life. We communicate using the different semantics known to us and we express our thoughts, ideas and opinions via tone and linguistics. It has been observed that humans convey information using various emotions such as anger, fear, sadness, calm, disgust, happiness, etc. Humans have been able to perceive such emotions because of years of social interaction among them, but such gifted abilities are restricted and limited to humans only. Machines, which us humans are dependent on nowadays do not have this luxury. Machines are not as capable as us humans to process such delicate and intricate information on their own and hence, there is a need to train them accordingly resulting in easier and better communication. In the field of human computer inter- action (HCI), emotion recognition from the computer is still a challenging issue, especially when the recog- nition is based solely on voice, which is the basic mean and the most integral part of human communication. In human computer interaction systems, emotion recognition could provide the users with improved personalization services by being adaptive to their emotions. Therefore, emotion detection from speech could have many potential applications in order to make the machine more flexible to the user and thus enriching and bettering user’s needs and experience. In the proposed system we will be using various Deep Learning (ML) techniques to build and train a model which is capable of detecting and recognizing the various emotions known to man. By this project, one of our aims is to enrich customer experiences in call centers by analyzing various call recordings and recognize the emotional aspects of speech irrespective of the semantic contents.
Keywords:
Speech, Emotion, Noise.
Cite Article:
"Speech Emotion Recognition Using Deep Learning", International Journal of Novel Research and Development (www.ijnrd.org), ISSN:2456-4184, Vol.8, Issue 4, page no.f42-f49, April-2023, Available :http://www.ijnrd.org/papers/IJNRD2304507.pdf
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ISSN:
2456-4184 | IMPACT FACTOR: 8.76 Calculated By Google Scholar| ESTD YEAR: 2016
An International Scholarly Open Access Journal, Peer-Reviewed, Refereed Journal Impact Factor 8.76 Calculate by Google Scholar and Semantic Scholar | AI-Powered Research Tool, Multidisciplinary, Monthly, Multilanguage Journal Indexing in All Major Database & Metadata, Citation Generator
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