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Multiparty Bench is introduced, the first benchmark specifically designed to objectively evaluate conversational speech systems as active participants within multi-party contexts and assesses agent behavior along two primary dimensions: turn-taking awareness and response appropriateness.
AudioICL-Bench is introduced, a diagnostic benchmark whose per-episode rules are resampled so that no correct answer is recoverable from prior knowledge, and its nine tasks are organized along two axes that separate what must be learned from demonstrations from what must be perceived in the signal, enabling failures to...
This paper introduces a syllable-level UASR framework based on masked language modeling, which avoids the need for G2P and the instability of GAN-based methods and generalizes effectively to low-resource languages that have remained particularly difficult for prior methods.
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