Speech and Facial Recognition Using Feature Extraction and Deep Learning Algorithms with Memory

T. Mani Kumar, G. Shanmukha Reddy, K. Hari Krishna, Ch Chandu, V. Ajay

2025

Abstract

Nowadays, all contemporary departments are using facts science, synthetic intelligence, machine cutting-edge, and deep gaining knowledge state modern strategies to investigate, get statistical reports, are expecting, and determine the effects by the usage of various algorithms. photo processing is likewise a trending technology to enforce the manner with photographs. lots latest posted content material on social networks gives an awesome opportunity to examine customers’ feelings, allowing the fast improvement brand new emotion-conscious applications. as an example, a pastime management system or personalised commercial machine can make treasured recommendations or schedule in an emotion-sensing manner. in this task, we're going to investigate sentiment and remarks evaluation based totally on customer's facial reactions, feelings, and sentiments the use of emotion reputation generation. "Speech Emotion recognition (SER)" makes this feasible. Diverse researchers have created a diffusion cutting-edge system to extract emotions from the speech move. The rapid advancements in speech and facial recognition technologies have significant potential to contribute to several (SDGs), particularly in areas such as quality education, health, and equality. The study discovers the integration of feature extraction techniques, deep learning algorithms for enhancing speech and facial recognition systems, focusing on the inclusion of memory components to improve accuracy and adaptability. By employing advanced neural network architectures and memory-augmented models, the proposed system not only boosts recognition performance but also enables long-term learning from diverse and dynamic input data. The SDGs, involves this study contributes to be enabling more effective human-computer interaction, the technology can be used in educational tools that cater to diverse learning needs, including people with disabilities.

Paper Citation

in Harvard Style

Kumar T., Reddy G., Krishna K., Chandu C. and Ajay V. (2025). Speech and Facial Recognition Using Feature Extraction and Deep Learning Algorithms with Memory. In Proceedings of the 1st International Conference on Research and Development in Information, Communication, and Computing Technologies - ICRDICCT`25; ISBN 978-989-758-777-1, SciTePress, pages 651-659. DOI: 10.5220/0013918300004919

in Bibtex Style

@conference{icrdicct`2525,
author={T. Kumar and G. Reddy and K. Krishna and Ch Chandu and V. Ajay},
title={Speech and Facial Recognition Using Feature Extraction and Deep Learning Algorithms with Memory},
booktitle={Proceedings of the 1st International Conference on Research and Development in Information, Communication, and Computing Technologies - ICRDICCT`25},
year={2025},
pages={651-659},
publisher={SciTePress},
organization={INSTICC},
doi={10.5220/0013918300004919},
isbn={978-989-758-777-1},
}

in EndNote Style

TY - CONF

JO - Proceedings of the 1st International Conference on Research and Development in Information, Communication, and Computing Technologies - ICRDICCT`25
TI - Speech and Facial Recognition Using Feature Extraction and Deep Learning Algorithms with Memory
SN - 978-989-758-777-1
AU - Kumar T.
AU - Reddy G.
AU - Krishna K.
AU - Chandu C.
AU - Ajay V.
PY - 2025
SP - 651
EP - 659
DO - 10.5220/0013918300004919
PB - SciTePress