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This paper introduces Tha, an open-source toolkit utilizing weighted finite-state transducers to solve text normalization and inverse text normalization challenges specific to the Khmer language. By addressing unique linguistic constraints like non-segmented words and embedded numerals, it significantly improves compatibility for Khmer speech recognition and text-to-speech systems. This work represents a concrete advancement in machine learning infrastructure for low-resource languages, enabling more robust deployment of AI models in Southeast Asia.
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THA: Weighted Finite-State Text Normalization and Inverse Text Normalization for Khmer

arXiv2 min read

arXiv:2609.30984v1 Announce Type: new Abstract: Text-to-speech needs written text in spoken form, and speech recognition output needs the reverse. For Khmer, neither direction has a maintained open-source tool, and the script makes both harder: words are not separated by spaces, and number words occur inside ordinary words. We present Tha, a Khmer text normalization and inverse text normalization toolkit built from weighted finite-state transducers. It segments and classifies a whole line in one shortest-path search, and a second transducer rejects token boundaries inside a Khmer syllable. On Google's Khmer test suite, Tha agrees with the reference on all 274 cardinals up to one spelling variant, and on 2,906 real TTS prompts, 153 of the 158 sentences it rewrites are correct. Tha is open source under the Apache 2.0 license.

Abstract:Text-to-speech needs written text in spoken form, and speech recognition output needs the reverse. For Khmer, neither direction has a maintained open-source tool, and the script makes both harder: words are not separated by spaces, and number words occur inside ordinary words. We present Tha, a Khmer text normalization and inverse text normalization toolkit built from weighted finite-state transducers. It segments and classifies a whole line in one shortest-path search, and a second transducer rejects token boundaries inside a Khmer syllable. On Google's Khmer test suite, Tha agrees with the reference on all 274 cardinals up to one spelling variant, and on 2,906 real TTS prompts, 153 of the 158 sentences it rewrites are correct. Tha is open source under the Apache 2.0 license.

Computation and Language (cs.CL)

arXiv:2609.30984 [cs.CL]

(or arXiv:2609.30984v1 [cs.CL] for this version)

https://doi.org/10.48550/arXiv.2609.30984 Focus to learn more arXiv-issued DOI via DataCite (pending registration)

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Full text under the publisher's open licence · 219 words

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