4209240619223291eed-748820240924095801401 beie:beie director@blueeyesintelligence.orgWEB-FORM International Journal of Innovative Technology and Exploring Engineering IJITEE 22783075 10.35940/ijitee https://www.ijitee.org/ 09 30 2024 13 10 Department of Computer Science and Engineering, University College of Engineering, Osmania University, Hyderabad (Telangana), India. Sanjeeva Rao Sanku https://orcid.org/0009-0003-5966-4629 Prof. B. Sandhya Department of Computer Science and Engineering, MVSR Engineering College, Hyderabad (Telangana), India. Research into emotion detection is crucial because of the wide range of fields that can benefit from it, including healthcare, intelligent customer service, and education. In comparison to unimodal approaches, multimodal emotion recognition (MER) integrates many modalities including text, facial expressions, and voice to provide better accuracy and robustness. This article provides a historical and present-day overview of MER, focusing on its relevance, difficulties, and approaches. We examine several datasets, comparing and contrasting their features and shortcomings; they include IEMOCAP and MELD. Recent developments in deep learning approaches, particularly fusion strategies such as early, late, and hybrid fusion are covered in the literature review. Data redundancy, complicated feature extraction, and real-time detection are among the identified shortcomings. Our suggested technique enhances emotion recognition accuracy by using deep learning to extract features using a hybrid fusion approach. To overcome existing restrictions and advance the area of MER, this study intends to direct future investigations in the right direction. Examining various data fusion strategies, reviewing new methodologies in multimodal emotion identification, and identifying problems and research needs to make up the primary body of this work. 09 30 2024 18 27 CC-BY-NC-ND 4.0 10.35940/BEIESP.CrossMarkPolicy www.ijitee.org true International Journal of Innovative Technology and Exploring Engineering (IJITEE): https://www.ijitee.org/ Based on my understanding, this article has no conflicts of interest. This article has not been sponsored or funded by any organization or agency. The independence of this research is a crucial factor in affirming its impartiality, as it has been conducted without any external sway. The data provided in this article is exempt from the requirement for ethical approval or participant consent. The adequate resources of this article are publicly accessible. The authorship of this article is contributed equally to all participating individuals. 10.35940/ijitee.J9968.13100924 https://www.ijitee.org/portfolio-item/J996813100924/