The Audio Language Identifier is a machine learning application designed to classify spoken audio as either English or Hindi.
Instead of traditional audio processing, this project leverages computer vision to solve an audio problem. Raw audio clips are dynamically converted into Mel-Spectrograms (visual representations of sound frequencies). These spectrogram images are then passed through a Convolutional Neural Network (CNN) capable of distinguishing the unique visual patterns of both languages to give an accurate prediction.
- Frontend / Deployment: Streamlit
- Machine Learning: TensorFlow & Keras (CNN Architecture)
- Audio Processing: Librosa
- Data Visualization & Image Processing: Matplotlib, Pillow (PIL), NumPy
- Environment: Python 3.11