Benchmarking Natural Language Understanding Services for Building Conversational Agents
| Autor: | Pawel Swietojanski, Verena Rieser, Arash Eshghi, Xingkun Liu |
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| Rok vydání: | 2021 |
| Předmět: |
business.industry
Computer science Watson Process (engineering) Natural language understanding 020206 networking & telecommunications 02 engineering and technology Benchmarking computer.software_genre Annotation Task (computing) Stress (linguistics) 0202 electrical engineering electronic engineering information engineering Feature (machine learning) 020201 artificial intelligence & image processing Artificial intelligence business computer Natural language processing |
| Zdroj: | Lecture Notes in Electrical Engineering ISBN: 9789811593222 IWSDS |
| Popis: | We have recently seen the emergence of several publicly available Natural Language Understanding (NLU) toolkits, which map user utterances to structured, but more abstract, Dialogue Act (DA) or Intent specifications, while making this process accessible to the lay developer. In this paper, we present the first wide coverage evaluation and comparison of some of the most popular NLU services, on a large, multi-domain (21 domains) dataset of 25 K user utterances that we have collected and annotated with Intent and Entity Type specifications and which will be released as part of this submission (https://github.com/xliuhw/NLU-Evaluation-Data). The results show that on Intent classification Watson significantly outperforms the other platforms, namely, Dialogflow, LUIS and Rasa; though these also perform well. Interestingly, on Entity Type recognition, Watson performs significantly worse due to its low Precision (At the time of producing the camera-ready version of this paper, we noticed the seemingly recent addition of a ‘Contextual Entity’ annotation tool to Watson, much like e.g. in Rasa. We’d threfore like to stress that this paper does not include an evaluation of this feature in Watson NLU.). Again, Dialogflow, LUIS and Rasa perform well on this task. |
| Databáze: | OpenAIRE |
| Externí odkaz: |
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