PRiSM: Benchmarking Phone Realization in Speech Models
Phone recognition (PR) serves as the atomic interface for language-agnostic modeling for cross-lingual speech processing and phonetic analysis. Despite prolonged efforts in developing PR systems, current evaluations only measure surface-level transcription accuracy. We introduce PRiSM, the first open-source benchmark designed to expose blind spots in phonetic perception through intrinsic and extrinsic evaluation of PR systems. PRiSM standardizes transcription-based evaluation and assesses downstream utility in clinical, educational, and multilingual settings with transcription and representation probes. We find that diverse language exposure during training is key to PR performance, encoder-CTC models are the most stable, and specialized PR models still outperform Large Audio Language Models. PRiSM releases code, recipes, and datasets to move the field toward multilingual speech models with robust phonetic ability: https://github.com/changelinglab/prism.
69706334a8be625b19c2af8f
Shikhar Bharadwaj
claimed_verified
2026-01-21T09:19:30.067Z
66ccd2fcdba9f642125e3a55
https://cdn-avatars.huggingface.co/v1/production/uploads/66ccd2fcdba9f642125e3a55/hTKwQQahkbpNuGlaRhKp7.jpeg
Shikhar Bharadwaj
shikhar7ssu
user
shikhar7ssu
69706334a8be625b19c2af90
Chin-Jou Li
claimed_verified
2026-01-21T09:19:27.747Z
643e6952f6bb3c31a26d3650
/avatars/70bfa6a28f71e78446ccac5742bc7be8.svg
Chin-Jou Li
cjli
user
cjli
69706334a8be625b19c2af91
Yoonjae Kim
claimed_verified
2026-01-21T09:19:25.403Z
66138e8107b5892cee1fdc84
https://cdn-avatars.huggingface.co/v1/production/uploads/66138e8107b5892cee1fdc84/s9tumjav-9OiWnjQoSnGl.jpeg
Yoonjae Kim
y00njaekim
user
y00njaekim
69706334a8be625b19c2af92
Kwanghee Choi
claimed_verified
2026-01-21T09:19:22.863Z
64ba7c68710f5e5476877218
/avatars/1e5ad96dd0b237db1bfee400aa8ed229.svg
Kwanghee Choi
juice500
user
juice500
69706334a8be625b19c2af93
Eunjung Yeo
claimed_verified
2026-01-21T09:19:20.183Z
618b80845dc6e1c37cc46643
/avatars/60cdf870213f41d63d077cc5cfaf75cb.svg
Eunjung Yeo
speech31
user
speech31
69706334a8be625b19c2af94
Ryan Soh-Eun Shim
69706334a8be625b19c2af95
Hanyu Zhou
69706334a8be625b19c2af96
Brendon Boldt
69706334a8be625b19c2af97
Karen Rosero Jacome
69706334a8be625b19c2af98
Kalvin Chang
claimed_verified
2026-01-21T09:19:17.515Z
62b1fe30b9bc778fe4e68c5d
https://cdn-avatars.huggingface.co/v1/production/uploads/62b1fe30b9bc778fe4e68c5d/3qVYitofCIBloSN0be7pp.jpeg
Kalvin Chang
kalbin
user
kalbin
69706334a8be625b19c2af99
Darsh Agrawal
69706334a8be625b19c2af9a
Keer Xu
69706334a8be625b19c2af9b
Chao-Han Huck Yang
claimed_verified
2026-04-16T20:22:56.551Z
629e1b71bb6419817ed7566c
https://cdn-avatars.huggingface.co/v1/production/uploads/629e1b71bb6419817ed7566c/0ZCt-11eQtRDCOk9AozOp.jpeg
Huck Yang
huckiyang
user
huckiyang
69706334a8be625b19c2af9c
Jian Zhu
69706334a8be625b19c2af9d
Shinji Watanabe
69706334a8be625b19c2af9e
David R. Mortensen
PRiSM: Benchmarking Phone Realization in Speech Models
Phone recognition (PR) serves as the atomic interface for language-agnostic modeling for cross-lingual speech processing and phonetic analysis. Despite prolonged efforts in developing PR systems, current evaluations only measure surface-level transcription accuracy. We introduce PRiSM, the first open-source benchmark designed to expose blind spots in phonetic perception through intrinsic and extrinsic evaluation of PR systems. PRiSM standardizes transcription-based evaluation and assesses downstream utility in clinical, educational, and multilingual settings with transcription and representation probes. We find that diverse language exposure during training is key to PR performance, encoder-CTC models are the most stable, and specialized PR models still outperform Large Audio Language Models. PRiSM releases code, recipes, and datasets to move the field toward multilingual speech models with robust phonetic ability: https://github.com/changelinglab/prism.
PRiSM benchmark evaluates phonetic perception in speech models through standardized transcription-based metrics and downstream applications across clinical, educational, and multilingual domains.
phone recognition cross-lingual speech processing phonetic analysis intrinsic evaluation extrinsic evaluation transcription-based evaluation downstream utility clinical settings educational settings multilingual settings transcription probes representation probes language exposure encoder-CTC models large audio language models