open sourceaudio

Distil-Whisper

Fast and efficient speech transcription model.

Developed by Hugging Face

Official Site
1.5MParams
YesAPI Available
stableStability
1.0Version
Apache 2.0License
PyTorchFramework
NoRuns Locally
Real-World Applications
  • Real-time transcriptionOptimized Capability
  • Voice command recognitionOptimized Capability
  • Automated subtitlingOptimized Capability
  • Speech analyticsOptimized Capability
Implementation Example
Example Prompt
Transcribe the following audio clip: 'Hello, welcome to our meeting.'
Model Output
"Hello, welcome to our meeting."
Advantages
  • ✓ Increased inference speed up to 6x
  • ✓ Uses less than half the parameters of the original Whisper
  • ✓ Maintains a low word error rate in transcription
Limitations
  • ✗ May sacrifice some accuracy compared to the full Whisper model
  • ✗ Limited context understanding due to parameter reduction
  • ✗ Requires high-quality audio input for best results
Model Intelligence & Architecture

Technical Documentation

Distil‑Whisper is an optimized speech transcription model designed for speed and efficiency. It provides real-time transcription capabilities, significantly reducing latency while maintaining high accuracy.

Technical Specification Sheet
Technical Details
Architecture
Causal Decoder-only Transformer
Stability
stable
Framework
PyTorch
Signup Required
No
API Available
Yes
Runs Locally
No
Release Date
2023-11-30

Best For

Users needing fast, real-time transcription for various applications.

Alternatives

OpenAI Whisper, Google Speech-to-Text, IBM Watson Speech to Text

Pricing Summary

Available as open-source with potential freemium features.

Compare With

Distil-Whisper vs OpenAI WhisperDistil-Whisper vs Google Speech-to-TextDistil-Whisper vs DeepSpeechDistil-Whisper vs AssemblyAI

Explore Tags

#asr#speech-recognition

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