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Indian Institute of Technology Madras
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Evaluating AudioLLMs reveals that many models fail to leverage contextual information effectively, challenging assumptions about their pretraining capabilities.
Current ASR systems stumble significantly when faced with the nuances of real-world Indian speech, as revealed by a new benchmark exposing geographic performance disparities and the impact of audio quality, speaking rate, and device type.
