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.

書誌詳細
主要な著者: Ahmed, Syed Istiaque, Hossain, Md. Jubayer, Hoque, Kayes Mohammad Bin, Tusher, Mahmadur Rahman, Islam, Sajedur
その他の著者: Alam, Md. Golam Rabiul
フォーマット: 学位論文
言語:English
出版事項: Brac University 2024
主題:
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.
オンライン･アクセス:http://hdl.handle.net/10361/24029

インターネット

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

類似資料