[2605.03073] The TTS-STT Flywheel: Synthetic Entity-Dense Audio Closes the Indic ASR Gap Where Commercial and Open-Source Systems Fail
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Computer Science > Computation and Language
arXiv:2605.03073 (cs)
[Submitted on 4 May 2026]
Title:The TTS-STT Flywheel: Synthetic Entity-Dense Audio Closes the Indic ASR Gap Where Commercial and Open-Source Systems Fail
Authors:Venkata Pushpak Teja Menta
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Abstract:Niche-domain Indic ASR -- digit strings, currency amounts, addresses, brand names, English/Indic codemix -- is under-served by both open-source SOTA and commercial systems. On a synthesised entity-dense Telugu test set (held-out by synthesis system), vasista22/whisper-telugu-large-v2 (open SOTA) achieves Entity-Hit-Rate (EHR) 0.027 and Deepgram Nova-3 (commercial) 0.16. We close this gap with a self-contained TTSSTT flywheel: an open-source Indic TTS pipeline synthesises ~22,000 entity-dense Indic-English code-mix utterances at = 0.98. Code, holdouts, predictions, EDSA corpus, and entity dictionaries are released open-source.
Comments: 8 pages, 2 figures. Companion to arXiv:2604.25441 (Praxy Voice TTS), arXiv:2604.25476 (PSP), arXiv:2605.00777 (LASE)
Subjects:
Computation and Language (cs.CL); Sound (cs.SD)
Cite as: arXiv:2605.03073 [cs.CL]
(or arXiv:2605.03073v1 [cs.CL] for this version)
https://doi.org/10.48550/arXiv.2605.03073
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arXiv-issued DOI via DataCite (pending registration)
Submission history
From: Venkata Pushpak Teja Menta [view email] [v1] Mon, 4 May 2026 18:43:30 UTC (328 KB)
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