Comprehensive analysis and development of deep learning models for Bengali character’s spectrogram image classification in child speech: introduction of spectro SETNet

Comprehensive analysis and development of deep learning models for Bengali character’s spectrogram image classification in child speech: introduction of spectro SETNet

This thesis is submitted in partial fulfillment of the requirements for the degree of Bachelor of Science in Computer Science, 2024.

Bibliographische Detailangaben
Hauptverfasser:	Ahmed, Syed Istiaque, Hossain, Md. Jubayer, Hoque, Kayes Mohammad Bin, Tusher, Mahmadur Rahman, Islam, Sajedur
Weitere Verfasser:	Alam, Md. Golam Rabiul
Format:	Abschlussarbeit
Sprache:	English
Veröffentlicht:	Brac University 2024
Schlagworte:	Automatic speech recognition Character’s recognition Deep learning Mel-frequency spectrogram Spectro-SETNet Automatic speech recognition > Data processing. Deep learning (Machine learning). Spectrometer > Data processing.
Online Zugang:	http://hdl.handle.net/10361/24029

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