Speech Recognition of High Impact Model Using Deep Learning Technique: A Review
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Tarih
2025
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Yayıncı
Institute of Electrical and Electronics Engineers Inc.
Erişim Hakkı
info:eu-repo/semantics/closedAccess
Özet
Machine learning has been the subject of enormous study in speech processing, particularly in speech recognition, for the last decades. On the other hand, deep learning's potential use in speech recognition has been the subject of much study in recent years. New evidence suggests that deep learning has far-reaching applications across many domains and has significantly contributed to AI. Several applications involving voice have demonstrated encouraging outcomes when using deep learning models. There has been a recent growth of attention-based approaches and models that apply transfer learning to enormous datasets, which offers added motivation for ASR. Focussing on several deep-learning models, it provides a summary and comparison of the state-of-the-art approaches used in this field of study. Additionally, we have evaluated the models on speech datasets to learn how they function on various datasets for practical application. Academics interested in open-source ASR could use this study as a jumping-off point for future research on issues like minimizing data dependence, increasing generalisability across languages with limited resources, speaker variability, noise conditions, and identifying and resolving obstacles to advancing existing research.
Açıklama
Conference name : 7th International Congress on Human-Computer Interaction, Optimization and Robotic Applications, ICHORA 2025
Conference city : Ankara
Conference date : 23 May 2025 - 24 May 2025
Conference code : 209351
Anahtar Kelimeler
deep learning, deep neural network, Speech emotion recognition, Speech recognition
Kaynak
ICHORA 2025 - 2025 7th International Congress on Human-Computer Interaction, Optimization and Robotic Applications, Proceedings
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Scopus Q Değeri
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Künye
Hussein, H. H., Karan, O., Kurnaz, S., & Turkben, A. K. (2025, May). Speech Recognition of High Impact Model Using Deep Learning Technique: A Review. In 2025 7th International Congress on Human-Computer Interaction, Optimization and Robotic Applications (ICHORA) (pp. 1-10). IEEE. 10.1109/ICHORA65333.2025.11017051
