Initial commit

README.md

@@ -1,13 +1,47 @@
----
-title: Basic ASR
-emoji: 📈
-colorFrom: purple
-colorTo: green
-sdk: gradio
-sdk_version: 5.49.1
-app_file: app.py
-pinned: false
-short_description: Basic ASR application
----
-
-Check out the configuration reference at https://huggingface.co/docs/hub/spaces-config-reference
+# ASR Application
+
+## Overview
+This is an Automatic Speech Recognition (ASR) application.
+
+## Features
+- Speech-to-text conversion
+- Audio file processing
+- Real-time transcription support
+
+## Installation
+```bash
+# Clone the repository
+git clone <repository-url>
+cd "ASR Application"
+
+# Install dependencies
+pip install -r requirements.txt
+```
+
+## Usage
+```bash
+# Run the application
+python app.py
+```
+
+## Requirements
+- Python 3.x
+- Required libraries (see `requirements.txt`)
+
+## Project Structure
+```
+ASR Application/
+├── README.md
+├── requirements.txt
+├── app.py
+└── ...
+```
+
+## License
+[Specify your license]
+
+## Contributing
+Contributions are welcome! Please open an issue or submit a pull request.
+
+## Contact
+[Your contact information]

app.py

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+# -*- coding: utf-8 -*-
+
+
+import gradio as gr
+from transformers import pipeline
+
+asr = pipeline("automatic-speech-recognition", model="facebook/wav2vec2-base-100h")
+
+def transcribe_audio(audio):
+    text = asr(audio)["text"]
+    return text
+
+demo = gr.Interface(
+    fn=transcribe_audio,
+    inputs=gr.Audio(sources=["microphone"], type="filepath"),
+    outputs="text",
+    title="Speech-to-Text Transcription",
+    description="Record your voice and get the transcribed text using a pre-trained Wav2Vec2 model."
+)
+
+demo.launch(share=True)
+

requirements.txt

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+gradio
+transformers
+torch
+torchaudio
+
+