Natural Language Sentence Generation from API Specifications
Siyu Huo, Kushal Mukherjee, Jayachandu Bandlamudi, Vatche Isahagian,, Vinod Muthusamy, Yara Rizk

TL;DR
This paper presents a system that generates natural language sentences from API specifications to train intent recognition models in chatbots, enhancing accessibility for non-technical users and improving automation interactions.
Contribution
The work introduces a novel method for automatically generating training sentences from API specifications to improve intent recognition in chatbot systems.
Findings
Deep learning-based evaluation shows promising results.
Human-in-the-loop interaction can further enhance system performance.
The approach facilitates accessible API integration for non-technical users.
Abstract
APIs are everywhere; they provide access to automation solutions that could help businesses automate some of their tasks. Unfortunately, they may not be accessible to the business users who need them but are not equipped with the necessary technical skills to leverage them. Wrapping these APIs with chatbot capabilities is one solution to make these automation solutions interactive. In this work, we propose a system to generate sentences to train intent recognition models, a crucial component within chatbots to understand natural language utterances from users. Evaluation of our approach based on deep learning models showed promising and inspiring results, and the human-in-the-loop interaction will provide further improvement on the system.
Peer Reviews
No public reviews on file for this paper yet. If you reviewed it on a platform where reviews are public (OpenReview, ICLR, NeurIPS, ICML), you can paste yours below so the community can read it here.
Videos
No videos yet. Explain this paper in a talk, walkthrough, or lecture? Add one.
Taxonomy
TopicsTopic Modeling · AI in Service Interactions · Misinformation and Its Impacts
