Case studies: multimodal applications in natural language processing

Title

Case studies: multimodal applications in natural language processing

Creator

Nanjundan, Preethi; George, Jossy; Indu, P.V.; Eslamian, Saeid

Description

This chapter explores the incorporation of natural language processing (NLP) with multimodal information sources, including text, speech, and visual information, towards the improvement of practical applications. NLP may very significantly enhance tasks such as sentiment analysis, image captioning, and cross-modal retrieval by combining these modalities. Two examples of deep learning approaches are neural networks and transformers, which are examples of critical approaches for developing robots that analyze and understand complex multimodal inputs. The chapter is full of case examples that illustrate how multimodal NLP can revolutionize many industries, including healthcare data analysis and voice-activated assistant development. These illustrations demonstrate how NLP can enhance user interactions and decision-making processes by offering deeper, more contextual insights. In fact, the chapter also covers issues and ways ahead of multimodal NLPas integrating data, handling faulty or missing data, and how to resolve ethical dilemmas. These ongoing changes will define future artificial intelligence systems with increased adaptability, intuitiveness, and applicability. 2026 Elsevier Inc. All rights reserved.

Source

Multimodal Learning Using Heterogeneous Data;pp.169-175

Date

01-01-2025

Publisher

Elsevier

Subject

artificial intelligence; human-centered computing; human-computer interaction; machine learning; Multimodal NLP, sentiment analysis, image captioning, cross-modal retrieval, deep learning approaches, ethical dilemmas; natural language processing

Coverage

Nanjundan P., Department of Data Science, CHRIST University, Lavasa Campus, Maharashtra, Pune, India; George J., Department of Computer Science, CHRIST University, Karnataka, Bengaluru, India; Indu P.V., Department of Data Science, CHRIST University, Karnataka, Bengaluru, India; Eslamian S., Department of Water Science and Engineering, College of Agriculture, Isfahan University of Technology, Isfahan, Iran

Rights

Restricted Access; Hardcopy may be available in the library

Relation

ISBN: 978-044327528-9; 978-044327529-6;

Format

online

Language

English

Type

Book chapter

Identifier

https://doi.org/10.1016/B978-0-443-27528-9.00007-3

https://www.scopus.com/pages/publications/105032956099?origin=resultslist