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model that best suits your needs.
Step 2: Collect and Prepare the Data
Collect audio samples from a variety of sources and label them according to the emotions they convey. Then, use feature extraction techniques to extract features from the audio samples and create a dataset for training.
Step 3: Train the Model
Train the model on the dataset using a suitable machine learning algorithm.
Step 4: Build the API
Build an API using a framework like Flask or Django to serve the model.
Step 5: Deploy the API
Deploy the API to a cloud platform like AWS or Azure.
Step 6: Test the API
Test the API to ensure that it is functioning correctly.
