Transcribe audio to text with speaker diarization
Transcribe speech into text
Transcribe spoken audio to text
Transcribe audio to text
ML-powered speech recognition directly in your browser
Transcribe voice to text
Generate a 2-speaker podcast from text input or documents!
Transcribe audio to text
ML-powered speech recognition directly in your browser
Transcribe audio to text
西北工业大学ASLP实验室OSUM项目demo展示
Transcribe audio recordings to text
Transcribe spoken words into text
Faster Whisper Webui is a web-based interface designed to transcribe podcast audio into text with speaker diarization. Built on top of the Whisper AI model, it provides a user-friendly and efficient solution for converting audio content into readable text while identifying and labeling speakers. It is optimized for speed and accuracy, making it ideal for podcast transcriptions.
• Real-time Audio Transcription: Transcribes audio files quickly and accurately. • Speaker Diarization: Identifies and labels different speakers in the audio. • Multi-Language Support: Supports transcription in multiple languages. • User-Friendly Interface: Easy-to-use web interface for uploading and managing audio files. • Visualizations: Includes visual representations of the transcription and speaker segments. • Export Options: Allows exporting transcriptions in various formats for flexibility. • Containerized Deployment: Comes as a Docker container for easy setup and deployment.
What audio formats are supported?
Faster Whisper Webui supports WAV, MP3, and M4A audio formats.
Can I customize the transcription settings?
Yes, you can customize settings such as the language of the audio and the output format.
How do I deploy Faster Whisper Webui locally?
Deploy it using Docker by running the command docker run -p 5000:5000 faster-whisper-webui:latest
and accessing it via your web browser.