Detecting Off-Topic Spoken Response with NLP

Time: Thursday 17-Sept-2020 14:00 (This is a past event.)


Artifacts

Motivation / Abstract
Increased demand to learn English for business and education has led to growing interest in automatic spoken language assessment and teaching systems. With this shift to automated approaches, it is important that systems reliably assess all aspects of a candidate’s responses, one of which is whether the response from the candidate is relevant to the prompt provided. This paper will give audience an understanding of how off-topic detection can be done fairly accurately with seen and unseen prompts.
Questions Discussed
- How is the task of off-topic spoken response detection formulated?
- How do we get the data for such task?
- What algorithms or ensemble performs well in this task?
- How this method can be implemented in Testing Services, will it be effective?
- What are the other applications of this algorithm?
Stream Categories:
 Natural Language Processing