POWSM: A Phonetic Open Whisper-Style Speech Foundation Model
Recent advances in spoken language processing have led to substantial
progress in phonetic tasks such as automatic speech recognition (ASR), phone
recognition (PR), grapheme-to-phoneme conversion (G2P), and phoneme-to-grapheme
conversion (P2G). Despite their conceptual similarity, these tasks have largely
been studied in isolation, each relying on task-specific architectures and
datasets. In this paper, we introduce POWSM (Phonetic Open Whisper-style Speech
Model), the first unified framework capable of jointly performing multiple
phone-related tasks. POWSM enables seamless conversion between audio, text
(graphemes), and phones, opening up new possibilities for universal and
low-resource speech processing. Our model outperforms or matches specialized PR
models of similar size (Wav2Vec2Phoneme and ZIPA) while jointly supporting G2P,
P2G, and ASR. Our training data, code and models are released to foster open
science.
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Chin-Jou Li
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2026-01-22T08:48:17.636Z
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Chin-Jou Li
cjli
user
cjli
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Kalvin Chang
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2025-12-12T09:18:30.997Z
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Kalvin Chang
kalbin
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kalbin
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Shikhar Bharadwaj
claimed_verified
2025-11-03T20:57:16.726Z
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Shikhar Bharadwaj
shikhar7ssu
user
shikhar7ssu
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Eunjung Yeo
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2026-01-21T09:25:56.768Z
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Eunjung Yeo
speech31
user
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Kwanghee Choi
claimed_verified
2026-01-21T09:25:59.239Z
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Kwanghee Choi
juice500
user
juice500
6902c05e72739622ee92a670
Jian Zhu
6902c05e72739622ee92a671
David Mortensen
6902c05e72739622ee92a672
Shinji Watanabe
POWSM: A Phonetic Open Whisper-Style Speech Foundation Model
Recent advances in spoken language processing have led to substantial
progress in phonetic tasks such as automatic speech recognition (ASR), phone
recognition (PR), grapheme-to-phoneme conversion (G2P), and phoneme-to-grapheme
conversion (P2G). Despite their conceptual similarity, these tasks have largely
been studied in isolation, each relying on task-specific architectures and
datasets. In this paper, we introduce POWSM (Phonetic Open Whisper-style Speech
Model), the first unified framework capable of jointly performing multiple
phone-related tasks. POWSM enables seamless conversion between audio, text
(graphemes), and phones, opening up new possibilities for universal and
low-resource speech processing. Our model outperforms or matches specialized PR
models of similar size (Wav2Vec2Phoneme and ZIPA) while jointly supporting G2P,
P2G, and ASR. Our training data, code and models are released to foster open
science.
A unified framework, POWSM, performs multiple phonetic tasks including ASR, PR, G2P, and P2G, outperforming specialized models while using a single architecture.
automatic speech recognition phone recognition grapheme-to-phoneme conversion phoneme-to-grapheme conversion Wav2Vec2Phoneme ZIPA