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Emotion Recognition from Audio using Deep Learning #830
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Thank you for creating this issue! We'll look into it as soon as possible. Your contributions are highly appreciated! 😊 |
abhisheks008
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level2
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Girlscript Summer of Code 2024
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Jul 7, 2024
Assigned @ChethanaPotukanam |
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abhisheks008
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Status: Up for Grabs
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level2
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gssoc
Girlscript Summer of Code 2024
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Deep Learning Simplified Repository (Proposing new issue)
🔴 Project Title :
Emotion Recognition from Audio using Deep Learning
🔴 Aim :
To build a deep learning model that can analyze audio recordings and classify the emotions expressed. This can have applications in areas such as customer service, mental health monitoring, and entertainment.
🔴 Dataset :
Various publicly available datasets for emotion recognition in audio, such as RAVDESS, TESS, CREMA-D, etc.
🔴 Approach : Try to use 3-4 algorithms to implement the models and compare all the algorithms to find out the best fitted algorithm for the model by checking the accuracy scores. Also do not forget to do a exploratory data analysis before creating any model.
📍 Follow the Guidelines to Contribute in the Project :
requirements.txt
- This file will contain the required packages/libraries to run the project in other machines.Model
folder, theREADME.md
file must be filled up properly, with proper visualizations and conclusions.🔴🟡 Points to Note :
✅ To be Mentioned while taking the issue :
Load the Dataset
Exploratory Data Analysis (EDA): Visualise common patterns and features in audio signals.
Feature Extraction: Extract features such as MFCC, Chroma, Mel Spectrogram, etc.
Model Implementation: Convolutional Neural Network (CNN) , Recurrent Neural Network (RNN) , Long Short-Term ,
Memory (LSTM) , Bidirectional LSTM (BiLSTM)
Train and Evaluate Each Model
Compare Performance using accuracy and loss metrics.
Happy Contributing 🚀
All the best. Enjoy your open source journey ahead. 😎
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