Cited by 338Speech Recognition and SynthesisSpeech and Audio ProcessingMusic and Audio Processing

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WhisperX: Time-Accurate Speech Transcription of Long-Form Audio

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Bain, Max, Huh, Jaesung, Han, Tengda, Zisserman, Andrew·2023·INTERSPEECH 2023

DOI 10.21437/interspeech.2023-78

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Abstract

Large-scale, weakly-supervised speech recognition models, such as Whisper, have demonstrated impressive results on speech recognition across domains and languages. However, their application to long audio transcription via buffered or sliding window approaches is prone to drifting, hallucination & repetition; and prohibits batched transcription due to their sequential nature. Further, timestamps corresponding each utterance are prone to inaccuracies and word-level timestamps are not available out-of-the-box. To overcome these challenges, we present WhisperX, a time-accurate speech recognition system with word-level timestamps utilising voice activity detection and forced phoneme alignment. In doing so, we demonstrate state-of-the-art performance on long-form transcription and word segmentation benchmarks. Additionally, we show that pre-segmenting audio with our proposed VAD Cut & Merge strategy improves transcription quality and enables a twelve-fold transcription speedup via batched inference.

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Authors: Bain, M., Huh, J., Han, T., & Zisserman, A.
Affiliations: University of Oxford (GB)
ORCID: Bain, Max
Huh, Jaesung
Han, Tengda
Zisserman, Andrew
Venue: INTERSPEECH 2023
Publisher: ISCA
Published: 2023-08-20
Pages: 4489-4493
ISSN: 2308-457X (ISSN-L)
DOI: 10.21437/interspeech.2023-78
OpenAlex: W4385822293
Cited by: 337
References: 29
Citations by year: 2026: 134 · 2025: 123 · 2024: 65 · 2023: 15
FWCI: 59.71
Type: conference paper
Language: en
Open access: green
arxiv.org
Licence: cc-by
Locations: Interspeech (USB) (publishedVersion)
arXiv (Cornell University) (submittedVersion, cc-by)
arXiv (Cornell University) (cc-by)
Funders: Engineering and Physical Sciences Research Council (EP/T028572/1)
Topics: Physical Sciences › Computer Science › Artificial Intelligence › Speech Recognition and Synthesis
Physical Sciences › Computer Science › Signal Processing › Speech and Audio Processing
Physical Sciences › Computer Science › Signal Processing › Music and Audio Processing
Keywords: speech transcription, voice activity detection, forced alignment, phone recognition, timestamping

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WhisperX: Time-Accurate Speech Transcription of Long-Form Audio

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