Take the Most out of Text Data Augmentation Strategies For Intent Clustering And Induction Based on DSTC 11 Track 2 (2023)

Abstract: A brief introduction to author’s keyinterests and research topics which are: multimodal dialogue systems and impact of data augmentation to NLU performance. In addition to that the author shares his biography and view on the future of dialogue assistants.

## research interests the section is devoted to the author's interests, which are developed in the course of research conducted as part of his development at the university and his professional duties in his paid work. ## spoken dialogue system (sds) research thanks to the recent success and development of llm and technologies such as chatgpt @xcite , users are very keen on dialogue systems, and interest in the subject matter and work will bring a number of improvements and enhancements to the technologies we currently know. although predicting the future of technology for a period of time greater than 5 to 10 years gives the impression of being impossible, there are some fields that are likely to be explored in future works. ## suggested topics for discussion regarding the participation in the dstc11 challenge and the author's topic of research work, the suggestions for the discussion subjects are: the expectations for the dialogue are constantly growing along with the quality of each submodule. the topics presented are particularly important as they relate to improving the quality of the cutting-edge modern nlu module.