mlsanityData to 7 Oct 2026

BBPE16: UTF-16-based byte-level byte-pair encoding for improved multilingual speech recognition

arXiv 2602.01717 ↗First posted 2 Feb 2026cs.CL cs.AIcited by 0

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Abstract (arXiv)

Multilingual automatic speech recognition (ASR) requires tokenization that efficiently covers many writing systems. Byte-level BPE (BBPE) using UTF-8 is widely adopted for its language-agnostic design and full Unicode coverage, but its variable-length encoding inflates token sequences for non-Latin scripts, such as Chinese, Japanese, and Korean (CJK). Longer sequences increase computational load and memory use. We propose BBPE16, a UTF-16-based BBPE tokenizer that represents most modern scripts with a uniform 2-byte code unit. BBPE16 preserves BBPE's language-agnostic properties while substantially improving cross-lingual token sharing. Across monolingual, bilingual, and trilingual ASR, and in a multilingual continual-learning setup, BBPE16 attains comparable or better accuracy; for Chinese, it reduces token counts by up to 10.4% and lowers decoding iterations by up to 10.3%. These reductions speed up fine-tuning and inference and decrease memory usage, making BBPE16 a practical tokenization choice for multilingual ASR.

Key facts. No citing papers in the map yet (data through 7 Oct 2026). Builds on 19 of its 23 references that are in the map. First posted on arXiv 2 Feb 2026.

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References · 19

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7 more
  1. 2022E-Branchformer: Branchformer with Enhanced merging for speech recognitioncited by 90
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