learn.ifs.name

PUMA: language tokens for low-resource multilingual ASR

Oukid et al., 2026, PUMA (Findings of ACL 2026)

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3 cards in “4.5 Ablation & limits” · whole deck

4.5 Ablation & limits

  1. What does the PUMA ablation remove, and what is the overall effect?
    It removes the language tokens from the ULP (simultaneous setting). WER rises for every language, slightly for Wolof, Igbo, Shona and Xhosa, strongly for Fon (0.207 → 0.296) and Arabic (0.384 → 0.505).
    • Oukid et al., 2026, PUMA (Findings of ACL 2026), §4.5, pp. 377–378, table 5
  2. What limitation do the authors themselves state?
    Zero-shot performance is limited by the deliberately lightweight design, compared with large systems like Omnilingual ASR that use massive capacity and LLM-based representations.
    • Oukid et al., 2026, PUMA (Findings of ACL 2026), Limitations, p. 378
  3. What future work does the paper propose?
    Multi-token language representations (capturing phonetic, orthographic and prosodic traits), Mixture-of-Experts strategies, and frugal LLM-inspired architectures within a constrained parameter budget.
    • Oukid et al., 2026, PUMA (Findings of ACL 2026), §5, Limitations, p. 378

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