UGC CARE norms ugc approved journal norms IJRTI Research Journal

WhatsApp
Click Here

International Journal for Research Trends and Innovation
International Peer Reviewed & Refereed Journals, Open Access Journal
ISSN Approved Journal No: 2456-3315 | Impact factor: 8.14 | ESTD Year: 2016
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)

Call For Paper

For Authors

Forms / Download

Published Issue Details

Editorial Board

Other IMP Links

Facts & Figure

Impact Factor : 8.14

Issue per Year : 12

Volume Published : 7

Issue Published : 74

Article Submitted : 3603

Article Published : 2063

Total Authors : 5474

Total Reviewer : 528

Total Countries : 39

Indexing Partner

Licence

This work is licensed under a Creative Commons Attribution-NonCommercial 4.0 International License
Published Paper Details
Paper Title: CLASSIFYING VARIOUS EMOTIONS IN SPEECH USING LSTM
Authors Name: Mrs K.Sadhana , Siripuram Ramya , Vemali Likitha , Yalla Lahari , Chintalapati Shekar Varma
Download E-Certificate: Download
Author Reg. ID:
IJRTI_182164
Published Paper Id: IJRTI2206033
Published In: Volume 7 Issue 6, June-2022
DOI:
Abstract: 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 of Science & Engineering Development Research (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: 00084153
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
Publication Details: Published Paper ID: IJRTI2206033
Registration ID:182164
Published In: Volume 7 Issue 6, June-2022
DOI (Digital Object Identifier):
Page No: 185 - 189
Country: Vizianagaram , Andhra Pradesh, India
Research Area: Engineering
Publisher : IJ Publication
Published Paper URL : https://www.ijrti.org/viewpaperforall?paper=IJRTI2206033
Published Paper PDF: https://www.ijrti.org/papers/IJRTI2206033
Share Article:

Click Here to Download This Article

Article Preview
Click Here to Download This Article

Major Indexing from www.ijrti.org
Google Scholar ResearcherID Thomson Reuters Mendeley : reference manager Academia.edu
arXiv.org : cornell university library Research Gate CiteSeerX DOAJ : Directory of Open Access Journals
DRJI Index Copernicus International Scribd DocStoc

ISSN Details

ISSN: 2456-3315
Impact Factor: 8.14 and ISSN APPROVED
Journal Starting Year (ESTD) : 2016

DOI (A digital object identifier)


Providing A digital object identifier by DOI.ONE
How to Get DOI?

Conference

Open Access License Policy

This work is licensed under a Creative Commons Attribution-NonCommercial 4.0 International License

Creative Commons License This material is Open Knowledge This material is Open Data This material is Open Content

Important Details

Social Media

Join RMS/Earn 300

IJRTI

Indexing Partner