International Journal For Multidisciplinary Research

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Real-time Speech Emotion Recognition using Machine Learning

Author(s) P. BHAVANI DURGA, N.V Ratna Kishor Gade, D.JAYA KUMARI
Country India
Abstract This project is centred around examining spoken language emotion, a critical aspect of human-computer interaction and artificial intelligence. Leveraging advanced techniques such as Convolutional Neural Networks (CNN) and Long Short-Term Memory (LSTM) models, we aim to decipher and understand the nuanced expressions of emotions conveyed through speech. The investigation draws from diverse datasets, including RAVDESS, SAVEE, TESS, and CREAM-D, each carefully chosen to encapsulate a broad spectrum of emotions and real-world speech scenarios. The project unfolds by elucidating the methodologies employed in dataset selection, the prepossessing of raw audio data, and the intricacies of utilizing CNN and LSTM techniques for speech emotion analysis. The main objective is to create a robust and reliable outcome model capable of accurately classifying and interpreting emotions in speech across various contexts. Practical applications of this Research extend to fields such as sentiment analysis and potential contributions to mental health monitoring. Through this project, we contribute valuable insights to the evolving landscape of speech emotion analysis, addressing the inherent challenges and exploring opportunities for enhancing human-computer interaction and emotional intelligence in artificial systems.
Keywords Speech, CNN and LSTM, Voice, RAVDESS, SAVEE, TESS, and CREAM-D
Field Computer
Published In Volume 6, Issue 3, May-June 2024
Published On 2024-05-16
Cite This Real-time Speech Emotion Recognition using Machine Learning - P. BHAVANI DURGA, N.V Ratna Kishor Gade, D.JAYA KUMARI - IJFMR Volume 6, Issue 3, May-June 2024. DOI 10.36948/ijfmr.2024.v06i03.19403
DOI https://doi.org/10.36948/ijfmr.2024.v06i03.19403
Short DOI https://doi.org/gtvt36
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