title: Listening to Multi-talker Conversations: Modular and End-to-end Perspectives
abstract: Since the first speech recognition systems were built more than 30 years ago, improvement in voice technology has enabled applications such as smart assistants and automated customer support. However, conversation intelligence of the future requires recognizing free-flowing multi-party conversations, which is a crucial and challenging component that still remains unsolved. In this dissertation, we focus on this problem of speaker-attributed multi-talker speech recognition, and propose two perspe
journal: arXiv (Cornell University)