whisper-timestamped
Multilingual Automatic Speech Recognition with word-level timestamps and confidence
GraphCanon updated Sep 20, 2026 · GitHub synced Sep 20, 2026
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Decision brief
whisper-timestamped is a Python library that extends OpenAI's Whisper model with word-level timestamps and confidence scoring.
Good fit when
- When you need precise timestamping for each spoken word in speech recognition output.
- For multilingual speech processing where accurate time alignment between audio and transcriptions is essential.
Avoid when
- Avoid if your project requires minimal dependencies or a smaller footprint, as it includes several external libraries like matplotlib and transformers.
- Not suitable for real-time applications where low latency is crucial due to the additional overhead of timestamp generation and confidence scoring.
Observed Jul 17, 2026 · Source: enrich:decision_facts
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Maintenance and security
Full trust report- Maintenance
- Steady (34d since push)
- As of Sep 20, 2026
- Provenance
- Not a fork · Organization account
- As of Sep 20, 2026
- Security (OSV)
- No criticals
- As of Jul 11, 2026
Public GitHub metadata and optional OSV scans. Signals, not a guarantee. Trust methodology.
Install
pip install whisper-timestampedSimilar tools
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Evidence and technical details
Sourced facts, taxonomy, compatibility claims, README excerpt, and machine-readable endpoints.
Overview
A library for speech recognition that adds fine-grained timestamping and confidence to the output of OpenAI's Whisper model.
Capability facts
- Deploy
- Self-host
Source: dockerfile:Dockerfile · Sep 20, 2026
- Docker
- Dockerfile present
Source: dockerfile:Dockerfile · Sep 20, 2026
- Languages
- python
Source: github.language · Sep 20, 2026
Categories
Compatibility
Sourced claims from the README excerpt - not unsourced marketing copy.
Source: README excerpt (regex_v1, Sep 20, 2026)
* `python3` (version higher or equal to 3.7, at least 3.9 is recommended)Source link
Tags
README
First installation Requirements: (version higher or equal to 3.7, at least 3.9 is recommended) (see instructions for installation on the whisper repository) You can install either by using pip: or by cloning this repository and running installation: Additional packages that might...
For agents
This page has a .md twin and JSON over the API.