Text2Audio_-_Audio2Text_Conversion_Using_HuggingFace

This project demonstrates how to perform text-to-audio and audio-to-text conversions using Hugging Face transformers. It includes examples of generating audio from text, converting audio to text, and downloading audio for further processing.

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Project Overview

1. Text-to-Audio Conversion
   Use the Hugging Face pipeline and the suno/bark-small model to convert text into audio.
2. Audio-to-Text Conversion
   Use the Hugging Face whisper-medium model to transcribe audio files into text.
3. Download and Play Audio
   Download an audio file, play it directly, and process it for transcription.

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Requirements

• Python 3.7+
• Hugging Face transformers library
• Jupyter Notebook (or Google Colab)
• IPython for displaying audio in notebooks

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Installation

1. Clone the repository:

   git clone https://github.com/<your-username>/<your-repo-name>.git
   cd <your-repo-name>
   
   

Text-to-Audio and Audio-to-Text Conversion using Hugging Face

This project demonstrates text-to-audio and audio-to-text conversions using Hugging Face transformers. It includes key models, installation instructions, and code examples for quick implementation.

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Text-to-Audio and Audio-to-Text Conversion using Hugging Face

This project demonstrates text-to-audio and audio-to-text conversions using Hugging Face transformers. It showcases how to generate audio from text, transcribe audio into text, and play audio directly within a Python environment.

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Installation

Install dependencies:

Run the following command to install the required libraries:

pip install transformers ipython

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How to Run

Text-to-Audio Conversion

Convert text into audio using the suno/bark-small model:

from transformers import pipeline
from IPython.display import Audio

# Input text
text = "Subscribe to my channel: Content on Demand"

# Load the text-to-speech pipeline
pipe = pipeline("text-to-speech", model='suno/bark-small')

# Generate audio
output = pipe(text)

# Play the audio
Audio(output["audio"], rate=output["sampling_rate"])

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Audio-to-Text Conversion

Transcribe audio using the openai/whisper-medium model:

from transformers import pipeline

# Load the Whisper model
whisper = pipeline('automatic-speech-recognition', model='openai/whisper-medium')

# Transcribe the audio file
transcription = whisper('audio.mp3')

# Print the transcription
print(transcription)

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Key Models

-suno/bark-small: Used for converting text into audio.

-openai/whisper-medium: Used for transcribing audio into text. from transformers import pipeline

Acknowledgments

-Hugging Face for providing powerful transformer-based models.

-Google Colab for offering an easy-to-use platform for running Python code.