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ESCUCHA: A Spanish Speech Benchmark for Heterogeneous Acoustic Conditions

arXiv 2607.17812 ↗First posted 20 Jul 2026cs.CLcited by 0

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Abstract (arXiv)

As large audio language models (LALMs) advance, robust evaluation frameworks have become essential. In this context, Spanish speech understanding under realistic acoustic conditions has received particularly little attention. We introduce ESCUCHA, the first Spanish speech understanding benchmark designed to evaluate LALMs across heterogeneous acoustic conditions and reasoning abilities. ESCUCHA comprises 1,000 human-curated questions paired with audio, totaling 162.9 hours sourced directly ``from the wild'' rather than drawn from existing datasets, with durations ranging from a few seconds to over 80 minutes. The benchmark emphasizes reasoning, spanning 9 perceptual and 10 reasoning categories, and it captures linguistic diversity through multiple Spanish accents and non-normative speech. ESCUCHA further includes multi-audio questions, spoken questions, and audio instructions, and it flags which questions support open-ended evaluation. Benchmarking several state-of-the-art multimodal and speech models reveals substantial performance gaps relative to trained humans.

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References · 20

  1. 2025Qwen3 Technical Reportcited by 8,820
  2. 2025Qwen3-Omni Technical Reportcited by 497
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  10. 2025MMAR: A Challenging Benchmark for Deep Reasoning in Speech, Audio, Music, and Their Mixcited by 117
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  12. 2024video-SALMONN: Speech-Enhanced Audio-Visual Large Language Modelscited by 102
8 more
  1. 2023Dynamic-SUPERB: Towards A Dynamic, Collaborative, and Comprehensive Instruction-Tuning Benchmark for Speechcited by 101
  2. 2024Dynamic-SUPERB Phase-2: A Collaboratively Expanding Benchmark for Measuring the Capabilities of Spoken Language Models with 180 Taskscited by 71
  3. 2025MMAU-Pro: A Challenging and Comprehensive Benchmark for Holistic Evaluation of Audio General Intelligencecited by 61
  4. 2025SAKURA: On the Multi-hop Reasoning of Large Audio-Language Models Based on Speech and Audio Informationcited by 42
  5. 2026OmniVoice: Towards Omnilingual Zero-Shot Text-to-Speech with Diffusion Language Modelscited by 25
  6. 2025Fleurs-SLU: A Massively Multilingual Benchmark for Spoken Language Understandingcited by 4
  7. 2026GlobeAudio: A Multilingual Multicultural Benchmark for Naturalistic Evaluation of Large Audio-Language Modelscited by 2
  8. 2026When Audio-Language Models Fail to Leverage Multimodal Context for Dysarthric Speech Recognitioncited by 1

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