@article{2902, keywords = {Asynchronous Video Interview, Language Model, Question Generation, Conversational Agent, Follow-up Question Generation}, author = {Pooja Rao S B and Manish Agnihotri and Dinesh Babu Jayagopi}, title = {Improving Asynchronous Interview Interaction with Follow-up Question Generation}, abstract = {The user experience of an asynchronous video interview system, conventionally is not reciprocal or conversational. Interview applicants expect that, like a typical face-to-face interview, they are innate and coherent. We posit that the planned adoption of limited probing through follow-up questions is an important step towards improving the interaction. We propose a follow-up question generation model (followQG) capable of generating relevant and diverse follow-up questions based on the previously asked questions, and their answers. We implement a 3D virtual interviewing system, Maya, with capability of follow-up question generation. Existing asynchronous interviewing systems are not dynamic with scripted and repetitive questions. In comparison, Maya responds with relevant follow-up questions, a largely unexplored feature of irtual interview systems. We take advantage of the implicit knowledge from deep pre-trained language models to generate rich and varied natural language follow-up questions. Empirical results suggest that followQG generates questions that humans rate as high quality, achieving 77% relevance. A comparison with strong baselines of neural network and rule-based systems show that it produces better quality questions. The corpus used for fine-tuning is made publicly available.}, year = {2021}, journal = {International Journal of Interactive Multimedia and Artificial Intelligence}, volume = {6}, number = {5}, pages = {79-89}, month = {03/2021}, issn = {1989-1660}, url = {https://www.ijimai.org/journal/sites/default/files/2021-02/ijimai_6_5_8.pdf}, doi = {10.9781/ijimai.2021.02.010}, }