This project is a powerful application that combines the capabilities of OpenAI's Whisper model and spaCy's NLP functionalities. It allows you to upload a 30-second audio file, transcribe the speech to text, and generate various natural language processing insights. The project leverages Gradio to create an interactive web interface for easy use.

• Audio Transcription: Upload an audio file, and the application transcribes the speech to text using the Whisper model.
• Named Entity Recognition (NER): Identifies and visualizes named entities (such as people, organizations, locations, etc.) in the transcribed text.
• Part-of-Speech (POS) Tagging: Tags each word in the transcribed text with its corresponding part of speech (e.g., noun, verb, adjective).
• Dependency Parsing: Analyzes the grammatical structure of the transcribed text by establishing relationships between words.
• Sentence Segmentation: Splits the transcribed text into individual sentences.

1. Transcription:

   • The uploaded audio file is processed and padded/trimmed to fit a 30-second duration.
   • The audio is converted into a log-Mel spectrogram and passed through the Whisper model to generate a transcription.

2. NLP Analysis:

   • The transcribed text is analyzed using spaCy.
   • Various NLP insights are generated, including named entity recognition, part-of-speech tagging, dependency parsing, and sentence segmentation.

3. Display:

   • The transcribed text and NLP insights are displayed on the web interface using Gradio.

To use this application, follow these steps:

1. Upload an Audio File: Select an audio file (up to 30 seconds in duration) from your local machine.
2. View Transcription and Insights: The application will display the transcribed text along with the following insights:
   • Named Entities Visualization
   • Part-of-Speech Tagging
   • Dependency Parsing
   • Sentence Segmentation

To run this project locally, you need to install the required dependencies. Here is the requirements.txt file for easy setup:

gradio==3.9
openai-whisper
spacy==3.4.0
pydub==0.25.1
torch==1.12.1

1. Create a virtual environment (optional but recommended):

   python -m venv venv
   source venv/bin/activate  # On Windows, use `venv\Scripts\activate`

2. Install the requirements:

   pip install -r requirements.txt

To run the application, execute the following command:

python main.py

This will launch the Gradio interface, and you can interact with the application through your web browser.

This project demonstrates the seamless integration of speech recognition and natural language processing, providing valuable insights from audio inputs in an interactive and user-friendly manner.

Feel free to explore and enhance the capabilities of this application according to your needs. Happy coding!