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Whisper Timestamped
Whisper Timestamped is an extension for OpenAI Whisper speech recognition models that generates word-level timestamps and confidence scores for transcribed audio.
Whisper Timestamped is an extension to the OpenAI Whisper Python package that enables word-level timestamp generation. It works by applying Dynamic Time Warping to the cross-attention weights of the underlying Whisper model rather than requiring additional neural networks. The tool assigns confidence scores to each word and segment to assist in transcription quality analysis. Users can incorporate Voice Activity Detection to reduce hallucinations on silent segments. It supports fine-tuned models from the Hugging Face Hub and provides output formats including JSON, CSV, and SRT.
Whisper Timestamped at a glance
Key features
- Word-level timestamp generation
- Confidence score assignment for words and segments
- Voice Activity Detection integration
- Support for fine-tuned models from Hugging Face
- Command line interface for batch processing
- Word alignment visualization plots
Use it for
- Generating time-coded subtitles for video
- Aligning text precisely with audio clips
- Cleaning transcripts of non-speech segments
- Analyzing confidence of speech recognition results
Alternatives to Whisper Timestamped
- faster-whisper — Transcribes audio faster with lower memory usage than standard implementations.
- WhisperLive — It provides real-time speech-to-text using multiple backends like Faster Whisper and TensorRT.
- WhisperX — It enables 70x faster, batched transcription with high-accuracy alignment.
- Whisper ASR Webservice — Provides a REST API for multiple ASR engines including WhisperX and Faster Whisper.
- whisper.cpp — It provides high-performance, offline speech recognition on diverse hardware.
- Whisper Diarization — Combines OpenAI Whisper with voice activity detection and speaker embedding.
- browser-whisper — Transcribes audio and video locally with zero servers involved.
- RealtimeSTT — Provides fast local speech recognition with voice activity detection and wake words.
- RealtimeTTS — Provides low-latency speech synthesis with a broad engine matrix and multiple backends.
- WeNet — Achieves state-of-the-art results on public speech datasets.
- Speech-to-Speech — Fully modular, swappable components with local or hosted execution options.
- AssemblyAI — Industry-leading speech models deliver high accuracy and low latency for voice applications.
All Whisper Timestamped alternatives