Natural conversations make both speech recognition and speaker attribution challenging for ASR, as speakers take turns, overlap, and reappear over time. We propose STAM-ASR, Speaker-Temporal Anchoring with Memory, a lightweight framework that extends an already pretrained AudioLLM for multi-speaker ASR. Without relying...
This study reviews multi-turn conversational AI across text-only dialogue, AudioLLMs and speech-native systems, multimodal and omni-modal systems, and tool-augmented agents, and concludes with a research agenda for systems that can remember, revise, ground, speak, listen, act, and adapt across turns, modalities, and cu...
S. Sara, Zien Sheikh Ali, Hunzalah Hassan Bhatti et al.· 3 citations
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