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Comprehensive evaluations of automatic speech recognition (ASR) for Iberian languages remain limited, and low-resource languages, biases, and efficiency trade-offs are underexplored. We benchmark eleven systems, ten open-weight models and one commercial API, across five Iberian languages (Basque, Catalan, Galician, Por...
This paper demonstrates DLaaS (Distributed Learning as a Service) from the developer's vantage point and demonstrates the complete service lifecycle on an industrial smart-home Wake-up Word (WuW) task, using the "Ok Aura"dataset.
A comprehensive benchmark of Federated Learning for multilingual Automatic Speech Recognition (ASR) for multilingual Speech-LLM architectures, evaluating four Speech-LLM architectures on the Multilingual LibriSpeech dataset shows that optimized learning rates are critical for performance.
This work empirically diagnose the root cause across six per-layer methods and three speech-LLM architectures and proposes a two-pool allocation that normalises encoder and LLM parameters into independent pools, and shows that joint $\ell_2$ sensitivity and the original $(\varepsilon,\delta)$-DP guarantee are unchanged...
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 LA...
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