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Personalised Emotion Detection from Text Using Machine Learning

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Computer Science and Engineering in Health Services (COMPSE 2022)

Part of the book series: EAI/Springer Innovations in Communication and Computing ((EAISICC))

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Abstract

This research discusses an emotion recognition system, which is an important component of many effective computing technologies for natural language processing, based on open-source platforms with automatic speech recognition (ASR) and text analysis, and which is used for user-based customised sentiment analysis. PocketSphinx as ASR and Word2vec model, K-means clustering, and TfidfVectoriser for text automatic analysis are used to design the proposed framework. Further, the dataset that is used for testing and training the model is from International Survey on Emotion Antecedents and Reactions (ISEAR). This research yields a user-dependent system that will function as a tailored assistant for identifying emotional responses and discovering innovative applications. The suggested model greatly outperforms the prior models, with an efficiency of 81% and an f-measure of 89%.

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Author information

Authors and Affiliations

  1. Department of Computer Science and Engineering, Indian Institute of Information Technology, Kottayam, Kerala, India

    A. V. Bhavya, R. H. Dhanush, J. Sangeetha & Arun Cyril Jose

Authors
  1. A. V. Bhavya
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  2. R. H. Dhanush
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  3. J. Sangeetha
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  4. Arun Cyril Jose
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Corresponding author

Correspondence to Arun Cyril Jose .

Editor information

Editors and Affiliations

  1. Engineering Department, National Autonomous University of Mexico, Mexico City, Distrito Federal, Mexico

    José Antonio Marmolejo-Saucedo

  2. Facultad de Ciencias Economicas Y Empresariales, Universidad Panamericana, Ciudad de Mexico, Mexico

    Roman Rodríguez-Aguilar

  3. Universiti Teknologi Petronas, Tronoh, Perak, Malaysia

    Pandian Vasant

  4. Graduate Program in Systems Engineering, Nuevo Leon State University, San Nicolás de los Garza, Mexico

    Igor Litvinchev

  5. School of Engineering, Universidad Anahuac México, Naucalpan de Juárez, Mexico

    Brenda M. Retana-Blanco

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© 2024 The Author(s), under exclusive license to Springer Nature Switzerland AG

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Bhavya, A.V., Dhanush, R.H., Sangeetha, J., Jose, A.C. (2024). Personalised Emotion Detection from Text Using Machine Learning. In: Marmolejo-Saucedo, J.A., Rodríguez-Aguilar, R., Vasant, P., Litvinchev, I., Retana-Blanco, B.M. (eds) Computer Science and Engineering in Health Services. COMPSE 2022. EAI/Springer Innovations in Communication and Computing. Springer, Cham. https://doi.org/10.1007/978-3-031-34750-4_10

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  • DOI: https://doi.org/10.1007/978-3-031-34750-4_10

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  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-031-34749-8

  • Online ISBN: 978-3-031-34750-4

  • eBook Packages: EngineeringEngineering (R0)

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