IJRTI
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 : 10

Issue Published : 115

Article Submitted : 19482

Article Published : 8050

Total Authors : 21282

Total Reviewer : 770

Total Countries : 145

Indexing Partner

Licence

This work is licensed under a Creative Commons Attribution-NonCommercial 4.0 International License
Published Paper Details
Paper Title: Speech Emotion Recognition using LSTM
Authors Name: Kopparapu Nihith , Khushi D M , Umashree
Download E-Certificate: Download
Author Reg. ID:
IJRTI_187435
Published Paper Id: IJRTI2307028
Published In: Volume 8 Issue 7, July-2023
DOI:
Abstract: Abstract-Conceptual Finding the specific feeling of a human in light of speech is exceptionally difficult. Discourse feeling acknowledgment is an undertaking that includes recognizing feelings communicated in discourse. Long momentary memory (LSTM) networks are a sort of intermittent brain network that can be utilized for this errand. LSTMs are appropriate for discourse feeling acknowledgment since they can catch long haul conditions in consecutive information like discourse. In a discourse feeling acknowledgment framework utilizing LSTMs, the discourse signal is first handled to remove highlights like Mel-recurrence cepstral coefficients (MFCCs) that catch significant acoustic properties of the discourse. The highlights are then input into the LSTM organization, which has been prepared to anticipate the close to home condition of the speaker in view of the arrangement of elements. The result of the LSTM is a likelihood dissemination over a bunch of feelings, and the feeling with the most elevated likelihood is chosen as the last expectation..
Keywords: LSTM , Cross lingual , DNN
Cite Article: "Speech Emotion Recognition using LSTM", International Journal of Science & Engineering Development Research (www.ijrti.org), ISSN:2455-2631, Vol.8, Issue 7, page no.163 - 167, July-2023, Available :http://www.ijrti.org/papers/IJRTI2307028.pdf
Downloads: 000205203
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: IJRTI2307028
Registration ID:187435
Published In: Volume 8 Issue 7, July-2023
DOI (Digital Object Identifier):
Page No: 163 - 167
Country: Bengaluru, Karnataka, India
Research Area: Information Technology 
Publisher : IJ Publication
Published Paper URL : https://www.ijrti.org/viewpaperforall?paper=IJRTI2307028
Published Paper PDF: https://www.ijrti.org/papers/IJRTI2307028
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

Join RMS/Earn 300

IJRTI

WhatsApp
Click Here

Indexing Partner