most citedThe timing bottleneck: Why timing and overlap are mission-critical for conversational user interfaces, speech recognition and dialogue systems

4 citations

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2 papers

cs.AI2024

Mechanisms of Symbol Processing for In-Context Learning in Transformer Networks

Paul Smolensky, Roland Fernandez, Zhenghao Herbert Zhou +3

Large Language Models (LLMs) have demonstrated impressive abilities in symbol processing through in-context learning (ICL). This success flies in the face of decades of critiques a…

cs.CL2023★ 4 cited

The timing bottleneck: Why timing and overlap are mission-critical for conversational user interfaces, speech recognition and dialogue systems

Andreas Liesenfeld, Alianda Lopez, Mark Dingemanse

Speech recognition systems are a key intermediary in voice-driven human-computer interaction. Although speech recognition works well for pristine monologic audio, real-life use cas…