PUMA: language tokens for low-resource multilingual ASR

1 Problem & idea

1. What is PUMA, in one sentence?
   Projected Universal Multilingual ASR: one shared multilingual ASR model that becomes language-aware through a small shared Universal Language Projection (ULP) module plus a learnable token per language, instead of language-specific adapters.
   • Oukid et al., 2026, PUMA (Findings of ACL 2026), Abstract, p. 371
2. Why is ASR still poor for many African languages, according to PUMA's introduction?
   Limited annotated data, rich morphology, and high phonetic variability.
   • Oukid et al., 2026, PUMA (Findings of ACL 2026), §1, p. 371
3. What scaling problem of existing multilingual ASR approaches does PUMA target?
   Adapters, conditioning modules or per-language fine-tuning add parameters for every language, so the model grows as languages are added and scaling to new languages gets expensive.
   • Oukid et al., 2026, PUMA (Findings of ACL 2026), §1, p. 371
4. List PUMA's four claimed contributions.
   (1) A lightweight architecture with no language-specific adapters. (2) The ULP module with learnable language tokens and full parameter sharing. (3) Evaluation on ten low-resource languages under monolingual, progressive and simultaneous training. (4) Competitive or better results than larger models, supervised and zero-shot, with far fewer trainable parameters.
   • Oukid et al., 2026, PUMA (Findings of ACL 2026), §1, pp. 371–372