Question Answering (QA) systems can support health coaches in facilitating clients' lifestyle behavior changes (e.g., in adopting healthy sleep habits). In this paper, we formulate a domain-specific QA task for sleep coaching. To this end, we release SleepQA, a dataset created from 7,005 passages comprising 4,250 training examples with single annotations and 750 examples with 5-way annotations. We train a bi-encoder retrieval system on our dataset and perform extensive automated and human evaluations of the resulting end-to-end QA system. Comparisons of our model with various baselines shows improvements for domain-specific natural language processing on real-world questions. We hope that this dataset will lead to wider research interest in this important health domain.

@inproceedings{Bojic-et-al-ML4H-22, abstract = {Question Answering (QA) systems can support health coaches in facilitating clients' lifestyle behavior changes (e.g., in adopting healthy sleep habits). In this paper, we formulate a domain-specific QA task for sleep coaching. To this end, we release SleepQA, a dataset created from 7,005 passages comprising 4,250 training examples with single annotations and 750 examples with 5-way annotations. We train a bi-encoder retrieval system on our dataset and perform extensive automated and human evaluations of the resulting end-to-end QA system. Comparisons of our model with various baselines shows improvements for domain-specific natural language processing on real-world questions. We hope that this dataset will lead to wider research interest in this important health domain.}, address = {New Orleans, USA}, author = {Iva Bojic and Qi Ong and Megh Thakkar and Esha Kamran and Irving Shua and Rei Pang and Jessica Chen and Vaaruni Nayak and Shafiq Joty and Josip Car}, booktitle = {2022 Machine Learning for Health (Proceedings Track)}, numpages = {9}, publisher = {Proceedings for Machine Learning Research (PMLR)}, series = {ML4H@NeurIPS'22}, title = {SleepQA: A Health Coaching Dataset on Sleep for Extractive Question Answering}, url = {https://openreview.net/pdf?id=YJbrADZZ8l8}, year = {2022} }