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POLOK, A.; KLEMENT, D.; WIESNER, M.; KHUDANPUR, S.; ČERNOCKÝ, J.; BURGET, L.
Original Title
Target Speaker ASR with Whisper
English Title
Type
Paper in proceedings (conference paper)
Original Abstract
We propose a novel approach to enable the use of large, single-speaker ASR models, such as Whisper, for target speaker ASR. The key claim of this method is that it is much easier to model relative differences among speakers by learning to condition on frame-level diarization outputs than to learn the space of all speaker embeddings. We find that adding even a single bias term per diarization output type before the first transformer block can transform single-speaker ASR models into target-speaker ASR models. Our approach also supports speaker-attributed ASR by sequentially generating transcripts for each speaker in a diarization output. This simplified method outperforms baseline speech separation and diarization cascade by 12.9% absolute ORC-WER on the NOTSOFAR-1 dataset.
English abstract
Keywords
target-speaker ASR, diarization conditioning, multi-speaker ASR, Whisper
Key words in English
Authors
Released
06.05.2025
Publisher
IEEE Signal Processing Society
Location
Hyderabad
ISBN
979-8-3503-6874-1
Book
ICASSP, IEEE International Conference on Acoustics, Speech and Signal Processing - Proceedings
Pages from
1
Pages to
5
Pages count
URL
https://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=10887683
BibTex
@inproceedings{BUT198049, author="Alexander {Polok} and Dominik {Klement} and Matthew {Wiesner} and Sanjeev {Khudanpur} and Jan {Černocký} and Lukáš {Burget}", title="Target Speaker ASR with Whisper", booktitle="ICASSP, IEEE International Conference on Acoustics, Speech and Signal Processing - Proceedings", year="2025", pages="1--5", publisher="IEEE Signal Processing Society", address="Hyderabad", doi="10.1109/ICASSP49660.2025.10887683", isbn="979-8-3503-6874-1", url="https://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=10887683" }
Documents
Target_Speaker_ASR_with_Whisper