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Crafting ASR and Conversational Models for an Agriculture Chatbot

Published: 11 April 2022 Publication History

Abstract

In recent years, artificial intelligence chatbots have attracted more and more attention. The stability and accuracy of automatic speech recognition (ASR) have been improved, making voice more critical in the transaction process and voice consultation of e-commerce purchases. ASR matches the learning model based on contextual cues. Eliminating unnecessary text plays an important role. We use the LSTM model and change it to contextualized custom text. In addition, to use our robot for testing, we propose a multi-task model that can jointly perform content re-scoring and has excellent responsiveness in the text of the input entity. Therefore, this article recommends using ASR technology to interpret and predict the answers to the LSTM model, allowing users to obtain expected results from actual measurements and understand which aspects are suitable for predicting specific emotions tested on this group. This article discusses chatbots and the design techniques used in platform translation, early and modern chatbots combined with ASR and artificial intelligence technology.

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Cited By

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  • (2024)Beyond Text and Speech in Conversational Agents: Mapping the Design Space of AvatarsProceedings of the 2024 ACM Designing Interactive Systems Conference10.1145/3643834.3661563(1875-1894)Online publication date: 1-Jul-2024
  • (2023)Artificial Intelligence Based Chatbot for Healthcare ApplicationsIoT, Cloud and Data Science10.4028/p-atr6jg(370-377)Online publication date: 27-Feb-2023

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          cover image ACM Other conferences
          CIIS '21: Proceedings of the 2021 4th International Conference on Computational Intelligence and Intelligent Systems
          November 2021
          95 pages
          ISBN:9781450385930
          DOI:10.1145/3507623
          Permission to make digital or hard copies of all or part of this work for personal or classroom use is granted without fee provided that copies are not made or distributed for profit or commercial advantage and that copies bear this notice and the full citation on the first page. Copyrights for components of this work owned by others than ACM must be honored. Abstracting with credit is permitted. To copy otherwise, or republish, to post on servers or to redistribute to lists, requires prior specific permission and/or a fee. Request permissions from [email protected]

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          Publication History

          Published: 11 April 2022

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          Author Tags

          1. AI Chatbots
          2. ASR conversational Design techniques
          3. Generative and Rulue based
          4. Machine learning
          5. Neural network

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          • (2024)Beyond Text and Speech in Conversational Agents: Mapping the Design Space of AvatarsProceedings of the 2024 ACM Designing Interactive Systems Conference10.1145/3643834.3661563(1875-1894)Online publication date: 1-Jul-2024
          • (2023)Artificial Intelligence Based Chatbot for Healthcare ApplicationsIoT, Cloud and Data Science10.4028/p-atr6jg(370-377)Online publication date: 27-Feb-2023

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