d_vector

# Audio Analysis with D-Vectors

This is a Streamlit application that compares two audio samples using d-vectors. It utilizes the Pinecone similarity search service for finding the nearest speaker based on the computed d-vectors.

## Prerequisites

- Python 3.7 or higher

## Installation

1. Clone the repository:

```shell
git clone https://github.com/sujanMidatani7/d_vector.git

2. Navigate to the project directory:

cd d_vector

3. Install the required dependencies:

pip install -r requirements.txt

Usage

1. Make sure you have obtained a Pinecone API key. If not, sign up for a Pinecone account and create an API key.

2. Open the dVectorSA.py file and replace 'f9571b23-70be-4556-893a-7342b0bb51d1' in the pinecone.init() function with your Pinecone API key.

3. Run the Streamlit app:

streamlit run dVectorSA.py

4. The application will open in your browser. You can select the first audio file using the file uploader component.

5. After selecting the audio file, the app will compute the d-vector for the audio file and find the nearest speaker using the Pinecone index.

6. The app will display the nearest speaker's ID and score.

Contributing

Contributions are welcome! If you find any issues or have suggestions for improvement, please open an issue or submit a pull request.

License

This project is licensed under the GNU License.