{"categories":[{"label":"Linguistic","url":"https://skillfed.io/packages/category/text-processing-linguistic/2"}],"enrichment":{"capability":"Adds word-level timestamps and confidence scores to OpenAI's Whisper speech recognition model using Dynamic Time Warping on cross-attention weights, supporting multilingual ASR with optional voice activity detection.","skillfed_tags":["speech-recognition","timestamps","multilingual"],"use_cases":["Generate subtitle files with accurate word-level timing for video synchronization and accessibility.","Extract precise timestamps for each word to enable interactive transcript playback or speaker diarization.","Detect and filter out hallucinated speech on silence using VAD before transcription to improve accuracy.","Build searchable transcripts where users can click a word to jump to its exact position in audio.","Analyze speech patterns by correlating word timing with confidence scores to identify disfluencies or hesitations."],"what_it_does":"whisper-timestamped extends OpenAI's Whisper speech recognition model to predict word-level timestamps and confidence scores for each word in a transcription. Rather than Whisper's native segment-level timestamps (typically 1-second accuracy), this package uses Dynamic Time Warping applied to the model's cross-attention weights to align words precisely with their spoken timing. It processes long audio files with minimal additional memory overhead and works across Whisper's supported languages.\n\nThe package integrates optional Voice Activity Detection (VAD) to reduce hallucinations on silence, provides language detection confidence when the language is unspecified, and aims to do word alignment without extra inference steps when possible. It is designed as a drop-in extension to openai-whisper, maintaining API compatibility while adding these timing and confidence features for applications requiring precise word-level synchronization.","worth_installing":"Yes, if you need word-level timestamps for Whisper transcriptions and accept GPLv3 copyleft constraints. The package has low install friction, active maintenance, and no known vulnerabilities. Suitable for open-source projects, research, and accessibility tools; less suitable for proprietary closed-source products due to license. Aging status (339 days since release) is acceptable given recent repository activity."},"id":"whisper-timestamped","links":{"html":"https://skillfed.io/packages/whisper-timestamped","md":"https://skillfed.io/packages/whisper-timestamped.md","pypi":"https://pypi.org/project/whisper-timestamped/"},"maintenance":{"status":"aging"},"meta":{"latest_release":"2025-09-09","license_spdx":null,"license_treatment":"copyleft","name":"whisper-timestamped","python_support":"supports_current","summary":"Multi-lingual Automatic Speech Recognition (ASR) based on Whisper models, with accurate word timestamps, access to language detection confidence, several options for Voice Activity Detection (VAD), and more."},"popularity":{"monthly_downloads":98887,"position":13052,"tier":"top_15000"},"security":{"n_vulnerabilities":0},"version":"1.15.9"}