mlsanityData to 14 Oct 2026

Speech LLMs in Low-Resource Scenarios: Data Volume Requirements and the Impact of Pretraining on High-Resource Languages

arXiv 2508.05149 ↗First posted 7 Aug 2025eess.AS cs.AI cs.CLcited by 7

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Abstract (arXiv)

Large language models (LLMs) have demonstrated potential in handling spoken inputs for high-resource languages, reaching state-of-the-art performance in various tasks. However, their applicability is still less explored in low-resource settings. This work investigates the use of Speech LLMs for low-resource Automatic Speech Recognition using the SLAM-ASR framework, where a trainable lightweight projector connects a speech encoder and a LLM. Firstly, we assess training data volume requirements to match Whisper-only performance, re-emphasizing the challenges of limited data. Secondly, we show that leveraging mono- or multilingual projectors pretrained on high-resource languages reduces the impact of data scarcity, especially with small training sets. Using multilingual LLMs (EuroLLM, Salamandra) with whisper-large-v3-turbo, we evaluate performance on several public benchmarks, providing insights for future research on optimizing Speech LLMs for low-resource languages and multilinguality.

Key facts. Cited by 7 papers in the map (data through 14 Oct 2026). Builds on 17 of its 23 references that are in the map. First posted on arXiv 7 Aug 2025.

Builds on

17 of 23 references.

References · 17

  1. 2023Visual Instruction Tuningcited by 7,869
  2. 2022Robust Speech Recognition via Large-Scale Weak Supervisioncited by 4,057
  3. 2019Common Voice: A Massively-Multilingual Speech Corpuscited by 1,384
  4. 2023Qwen-Audio: Advancing Universal Audio Understanding via Unified Large-Scale Audio-Language Modelscited by 608
  5. 2023SALMONN: Towards Generic Hearing Abilities for Large Language Modelscited by 506
  6. 2022FLEURS: Few-shot Learning Evaluation of Universal Representations of Speechcited by 469
  7. 2023Multimodal Large Language Models: A Surveycited by 195
  8. 2023On decoder-only architecture for speech-to-text and large language model integrationcited by 145
  9. 2023Prompting Large Language Models with Speech Recognition Abilitiescited by 140
  10. 2024EuroLLM: Multilingual Language Models for Europecited by 106
  11. 2024An Embarrassingly Simple Approach for LLM with Strong ASR Capacitycited by 88
  12. 2024Seed-ASR: Understanding Diverse Speech and Contexts with LLM-based Speech Recognitioncited by 63
5 more
  1. 2024Large Language Models are Strong Audio-Visual Speech Recognition Learnerscited by 42
  2. 2024Performance evaluation of SLAM-ASR: The Good, the Bad, the Ugly, and the Way Forwardcited by 17
  3. 2020Deep Neural Networks for Automatic Speech Processing: A Survey from Large Corpora to Limited Datacited by 9
  4. 2024SALSA: Speedy ASR-LLM Synchronous Aggregationcited by 8
  5. 2024Zero-resource Speech Translation and Recognition with LLMscited by 6

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Cited by year (2026 to 14 Oct)

Citing papers per year: 2026: 7.

7 papers.

  1. 2026Multimodal In-context Learning for ASR of Low-resource Languagescited by 2
  2. 2026Language Family Matters: Evaluating LLM-Based ASR Across Linguistic Boundariescited by 2
  3. 2026On the Role of Encoder Depth: Pruning Whisper and LoRA Fine-Tuning in SLAM-ASRcited by 2
  4. 2026Hard to Be Heard: Phoneme-Level ASR Analysis of Phonologically Complex, Low-Resource Endangered Languagescited by 2
  5. 2026MEUSLI: a Multilingual Projector for LLM-based ASR and Beyondcited by 1
  6. 2026LuxSQA: Ask Me in Luxembourgish with TTS-Augmented Spoken Question Answeringcited by 0
  7. 2026The Eloquence submission for Task 2 of the Interspeech 2026 MLC-SLM challengecited by 0