Multilingual Automatic Speech Recognition with word-level timestamps and confidence. Whisper is a set of multi-lingual, robust speech recognition models trained by OpenAI that achieve state-of-the-art results in many languages. Whisper models were trained to predict approximate timestamps on speech segments (most of the time with 1-second accuracy), but they cannot originally predict word timestamps. This repository proposes an implementation to predict word timestamps and provide a more accurate estimation of speech segments when transcribing with Whisper models. Besides, a confidence score is assigned to each word and each segment.

Features

  • The start/end estimation is more accurate
  • Documentation available
  • Confidence scores are assigned to each word
  • If possible (without beam search...), no additional inference steps are required to predict word timestamps (word alignment is done on the fly after each speech segment is decoded)
  • Special care has been taken regarding memory usage
  • Light installation for CPU
  • Plot of word alignment

Project Samples

Project Activity

See All Activity >

License

Affero GNU Public License

Follow whisper-timestamped

whisper-timestamped Web Site

Other Useful Business Software
Network Management Software and Tools for Businesses and Organizations | Auvik Networks Icon
Network Management Software and Tools for Businesses and Organizations | Auvik Networks

Mapping, inventory, config backup, and more.

Reduce IT headaches and save time with a proven solution for automated network discovery, documentation, and performance monitoring. Choose Auvik because you'll see value in minutes, and stay with us to improve your IT for years to come.
Learn More
Rate This Project
Login To Rate This Project

User Reviews

Be the first to post a review of whisper-timestamped!

Additional Project Details

Operating Systems

Linux, Mac, Windows

Programming Language

Python

Related Categories

Python Machine Learning Software, Python LLM Inference Tool

Registered

2024-08-14