Scaling Human and G2P Supervision for Robust Phonetic Transcription
Accepted Paper to Interspeech 2026
We are presenting at Interspeech 2026 about how phonetic transcription systems scale with expert human labels versus G2P-generated supervision. Across native, non-native, and post-stroke speech, we find that G2P helps only when expert annotation is scarce, while diverse human labels and ASR pretraining drive stronger robustness and reduce weighted phone feature error by 2.3x.
Speak Like The Stars: Pronunciation Mastery Through Movies.
Interspeech Conference Science Fair
We presented our work on making speech pathology more accessible, insights and statistics into our latest phonetic model, and a demo of our work-in-progress pronunciation platform.
Speech Technology Built for Everyone, Everywhere.
University of Washington Research Symposium
We presented our work on making speech pathology more accessible, insights and statistics into our latest phonetic model, and a demo of our work-in-progress pronunciation platform.
Research and Collaboration
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