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.

Bibliografiska uppgifter
Huvudupphovsmän: Ahmed, Syed Istiaque, Hossain, Md. Jubayer, Hoque, Kayes Mohammad Bin, Tusher, Mahmadur Rahman, Islam, Sajedur
Övriga upphovsmän: Alam, Md. Golam Rabiul
Materialtyp: Lärdomsprov
Språk:English
Publicerad: Brac University 2024
Ämnen:
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.
Länkar:http://hdl.handle.net/10361/24029

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