Alexander Berman


Evaluating N-best Calibration of Natural Language Understanding for Dialogue Systems
Ranim Khojah | Alexander Berman | Staffan Larsson
Proceedings of the 23rd Annual Meeting of the Special Interest Group on Discourse and Dialogue

A Natural Language Understanding (NLU) component can be used in a dialogue system to perform intent classification, returning an N-best list of hypotheses with corresponding confidence estimates. We perform an in-depth evaluation of 5 NLUs, focusing on confidence estimation. We measure and visualize calibration for the 10 best hypotheses on model level and rank level, and also measure classification performance. The results indicate a trade-off between calibration and performance. In particular, Rasa (with Sklearn classifier) had the best calibration but the lowest performance scores, while Watson Assistant had the best performance but a poor calibration.


Lekbot: A talking and playing robot for children with disabilities
Peter Ljunglöf | Britt Claesson | Ingrid Mattsson Müller | Stina Ericsson | Cajsa Ottesjö | Alexander Berman | Fredrik Kronlid
Proceedings of the Second Workshop on Speech and Language Processing for Assistive Technologies

Multimodal Menu-based Dialogue with Speech Cursor in DICO II+
Staffan Larsson | Alexander Berman | Jessica Villing
Proceedings of the ACL-HLT 2011 System Demonstrations