Abstract
Recent advancements in AI resulted in increased availability of conversational assistants that can help with tasks such as seeking times to schedule an event and creating a calendar entry at that time, finding a restaurant and booking a table there at a certain time. However, creating automated agents with human-level intelligence still remains one of the most challenging problems of AI. One key component of such systems is conversational language understanding, which is a holy grail area of research for decades, as it is not a clearly defined task but relies heavily on the AI application it is used for. Nevertheless, this chapter attempts to compile the recent deep learning based literature on such goal-oriented conversational language understanding studies, starting with a historical perspective, pre-deep learning era work, moving toward most recent advances in this field.
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Tur, G., Celikyilmaz, A., He, X., Hakkani-Tür, D., Deng, L. (2018). Deep Learning in Conversational Language Understanding. In: Deng, L., Liu, Y. (eds) Deep Learning in Natural Language Processing. Springer, Singapore. https://doi.org/10.1007/978-981-10-5209-5_2
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