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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
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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