Integration of NLP and Speech-to-text applications with Chatbot

D. Inupakutika, M. Nadim, G. R. Gunnam, S. Kaghyan, D. Akopian, San Antonio, P. Chalela, Amelie G Ramirez

Research output: Contribution to journalConference articlepeer-review

Abstract

With the evolving artificial intelligence technology, the chatbots are becoming smarter and faster lately. Chatbots are typically available round the clock providing continuous support and services. A chatbot or a conversational agent is a program or software that can communicate using natural language with humans. The challenge of developing an intelligent chatbot still exists ever since the onset of artificial intelligence. The functionality of chatbots can range from business oriented short conversations to healthcare intervention based longer conversations. However, the primary role that the chatbots have to play is in understanding human utterances in order to respond appropriately. To that end, there is an increased emergence of Natural Language Understanding (NLU) engines by popular cloud service providers. The NLU services identify entities and intents from the user utterances provided as input. Thus, in order to integrate such understanding to a chatbot, this paper presents a study on existing major NLU platforms. Then, we present a case study chatbot integrated with Google DialogFlow and IBM Watson NLU services and discuss their intent recognition performance.

Keywords

  • Apps
  • Chatbot
  • Deep learning
  • Dialog system
  • Natural language processing

ASJC Scopus subject areas

  • Computer Graphics and Computer-Aided Design
  • Computer Science Applications
  • Human-Computer Interaction
  • Software
  • Electrical and Electronic Engineering
  • Atomic and Molecular Physics, and Optics

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