Enhancing Automatic Speech Recognition for Punjabi Dialects: An Experimental Analysis of Incorporating Prosodic Features and Acoustic Variability Mitigation
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Publisher
Springer Science and Business Media LLC
Link
https://link.springer.com/content/pdf/10.1007/s42979-024-03111-w.pdf
Reference41 articles.
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3. Shahnawazuddin S, Adiga N, Kathania HK, Sai BT. Creating speaker independent ASR system through prosody modification-based data augmentation. Pattern Recognit Lett. 2020;131:213–8. https://doi.org/10.1016/j.patrec.2019.12.019.
4. Imaizumi R, Masumura R, Shiota S, Kiya H. End-to-end Japanese multi-dialect speech recognition and dialect identification with multi-task learning. APSIPA Trans Signal Inf Process, 2022;11(1).
5. Kadyan V, Hasija T, Singh A. Prosody features based low resource Punjabi children ASR and T-NT classifier using data augmentation. Multimed Tools Appl. 2023;82(3):3973–94.
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