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---
title: Fillersark
emoji: 📉
colorFrom: pink
colorTo: blue
sdk: gradio
sdk_version: 5.28.0
app_file: app.py
pinned: false
license: other
short_description: filler
---
Check out the configuration reference at https://huggingface.co/docs/hub/spaces-config-reference
# 🎙️ CrisperWhisper Speech-to-Text
This Hugging Face Space provides a speech-to-text transcription service powered by the [nyrahealth/CrisperWhisper](https://huggingface.co/nyrahealth/CrisperWhisper) model. Upload audio files and get transcribed text with word-level timestamps.
## Features
- Transcribe audio files to text with word-level timestamps
- Support for multiple audio formats (MP3, WAV, M4A, OGG, FLAC)
- Up to 30MB file size support
- Simple web interface using Gradio
- REST API endpoint for programmatic access
## How to Use
1. Upload an audio file using the interface
2. Click "Transcribe"
3. View both the plain text transcription and detailed JSON output with timestamps
## API Usage
You can also use this Space programmatically via the REST API:
```python
import requests
url = "https://your-space-name.hf.space/api/predict"
files = {'audio_input': open('/path/to/your-audio-file.mp3', 'rb')}
response = requests.post(url, files=files)
print(response.json())
```
## Model Details
This app uses the [nyrahealth/CrisperWhisper](https://huggingface.co/nyrahealth/CrisperWhisper) model, which is optimized for high-quality speech transcription with timestamp information.
## System Requirements
For optimal performance, this Space should be run with:
- GPU acceleration
- At least 8GB RAM
---
tags:
- speech-to-text
- transcription
- whisper
- gradio
- audio-processing
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