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.

Dades bibliogràfiques
Autors principals: Ahmed, Syed Istiaque, Hossain, Md. Jubayer, Hoque, Kayes Mohammad Bin, Tusher, Mahmadur Rahman, Islam, Sajedur
Altres autors: Alam, Md. Golam Rabiul
Format: Thesis
Idioma:English
Publicat: Brac University 2024
Matèries:
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.
Accés en línia:http://hdl.handle.net/10361/24029

Internet

http://hdl.handle.net/10361/24029

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