Identify the emotion of multiple speakers in an Audio Segment
Identify the emotion of multiple speakers in a Audio Segment
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The main aim of the project is to Identify the emotion of multiple speakers in a call audio as a application for customer satisfaction feedback in call centres.
Follow the Below Instructions for setting the project up on your local Machine.
sudo docker pull chinmaynehate/mevon-ai-ser:2.0
sudo docker run -it chinmaynehate/mevon-ai-ser:2.0 bash
python3 speechEmotionRecognition.py
sudo apt install python3-venv
mkdir mevonAI
cd mevonAI
python3 -m venv mevon-env
source mevon-env/bin/activate
git clone https://github.com/SuyashMore/MevonAI-Speech-Emotion-Recognition.git
cd MevonAI-Speech-Emotion-Recognition/
cd src/
sudo chmod +x setup.sh
./setup.sh
Add audio files in .wav format for analysis in src/input/ folder
Run Speech Emotion Recognition using
python3 speechEmotionRecognition.py
By Default , the application will use the Pretrained Model Available in "src/model/"
Diarized files will be stored in "src/output/" folder
Predicted Emotions will be stored in a separate .csv file in src/ folder
model = Sequential()
#Input Layer
model.add(Conv2D(32, 5,strides=2,padding='same',
input_shape=(13,216,1)))
model.add(Activation('relu'))
model.add(BatchNormalization())
#Hidden Layer 1
model.add(Conv2D(64, 5,strides=2,padding='same',))
model.add(Activation('relu'))
model.add(BatchNormalization())
#Hidden Layer 2
model.add(Conv2D(64, 5,strides=2,padding='same',))
model.add(Activation('relu'))
model.add(BatchNormalization())
#Flatten Conv Net
model.add(Flatten())
#Output Layer
model.add(Dense(7))
model.add(Activation('softmax'))
2DConvolution.ipynb file is used to training the model
Contributions are what make the open source community such an amazing place to be learn, inspire, and create. Any contributions you make are greatly appreciated.
git checkout -b feature/AmazingFeature
)git commit -m 'Add some AmazingFeature'
)git push origin feature/AmazingFeature
)Distributed under the MIT License. See LICENSE
for more information.