English

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

Computation and Language 2026-02-03 v1 Artificial Intelligence

Abstract

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.

Cite

@article{arxiv.2602.01717,
  title  = {BBPE16: UTF-16-based byte-level byte-pair encoding for improved multilingual speech recognition},
  author = {Hyunsik Kim and Haeri Kim and Munhak Lee and Kyungmin Lee},
  journal= {arXiv preprint arXiv:2602.01717},
  year   = {2026}
}

Comments

accepted to ICASSP 2026