Scholarly open access journals, Peer-reviewed, and Refereed Journals, Impact factor 8.14 (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)
Emotion recognition in speech is one of the main challenging components of Human Computer Interaction (HCI). Emotion detection has grown to be one of the maximum vital roles in customers that stumble on cutting-edge emotion of a person's emotion and suggest him the apt product or help him to improve the demand of the company or product. Where that is utilized in apps like Alexa, Cortana, Google Assistant and Siri. It has been changing the way of human beings interacting with the devices, homes, cars, jobs and also includes the huge database used to extract emotions, which contribute to speech emotion recognition and its limitation that relate to express such as happiness, anger, sad moods. We can use this technology in distinct fields consisting of security, medicine, entertainment, schooling.
Keywords:
Deep Learning, Human computer interaction, classification, speech data base, LSTM
Cite Article:
"CLASSIFYING VARIOUS EMOTIONS IN SPEECH USING LSTM ", International Journal for Research Trends and Innovation (www.ijrti.org), ISSN:2455-2631, Vol.7, Issue 6, page no.185 - 189, June-2022, Available :http://www.ijrti.org/papers/IJRTI2206033.pdf
Downloads:
000205201
ISSN:
2456-3315 | IMPACT FACTOR: 8.14 Calculated By Google Scholar| ESTD YEAR: 2016
An International Scholarly Open Access Journal, Peer-Reviewed, Refereed Journal Impact Factor 8.14 Calculate by Google Scholar and Semantic Scholar | AI-Powered Research Tool, Multidisciplinary, Monthly, Multilanguage Journal Indexing in All Major Database & Metadata, Citation Generator