Speech Emotion Recognition Using Deep Learning LSTM for Tamil Language
importance 2/10
ai assisted
Emotion and Mood Recognition speech recognition stage: research
Problem
Automatically recognizing emotions in Tamil speech, which traditional feedforward networks handle poorly.
Why it matters
Emotion-aware speech analysis can improve automated voice recognition systems for Tamil speakers.
What the AI did
Designed four deep hierarchical LSTM/BiLSTM architectures with dropout layers for emotional speech analysis in Tamil.
Results
not stated in source
Impact
Evidence supports architecture design only; performance figures are not stated.
Record
| Venue | Pertanika journal of science & technology |
|---|---|
| Published | 2021 |
| Work type | article |
| Authors | Bennilo Fernandes, Kasiprasad Mannepalli |
| Citations | 17 (OpenAlex, at import time) |
| References | 36 |
| Model or method | Deep Hierarchical LSTM/BiLSTM variants (DHLL, DHLB, DHBL, DHBB) |
| Organization | not stated in source |
| Primary source | https://doi.org/10.47836/pjst.29.3.33 |
| Open access | hybrid |
| Keywords | speech emotion recognition, LSTM, BiLSTM, Tamil, deep learning |
Importance rating
2
incremental / niche
Emotion recognition for Tamil speech only; niche language-specific improvement to voice recognition; no broader impact or scale stated.
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