IDALC: A Semi-Supervised Framework for Intent Detection and Active Learning based Correction

ArXi:2511.05921v3 Announce Type: replace-cross Voice-controlled dialog systems have become immensely popular due to their ability to perform a wide range of actions in response to diverse user queries. These agents possess a predefined set of skills or intents to fulfill specific user tasks. But every system has its own limitations. There are instances where, even for known intents, if any model exhibits low confidence, it results in rejection of utterances that necessitate manual annotation.