End-to-End Speech Recognition on Conversations
Journal: Figshare
Year: 2020

Processing of conversations is a core technique in conversational AI. However, current speech recognition solutions, even the state-of-the-art systems, model a single, isolated utterance, not an entire conversation. These systems are therefore unable to use potentially important contextual information that spans across multiple utterances or speakers in a conversation. This thesis focuses<br>on designing an End-to-End speech recognition system that processes entire conversations. To achieve this