Investigating self-supervised, weakly supervised and fully supervised training approaches for multi-domain automatic speech recognition: a study on Bangladeshi Bangla

no code implementations • 24 Oct 2022 • Ahnaf Mozib Samin, M. Humayon Kobir, Md. Mushtaq Shahriyar Rafee, M. Firoz Ahmed, Mehedi Hasan, Partha Ghosh, Shafkat Kibria, M. Shahidur Rahman

We also demonstrate the significance of domain selection while building a corpus by assessing these models on a novel multi-domain Bangladeshi Bangla ASR evaluation benchmark - BanSpeech, which contains approximately 6. 52 hours of human-annotated speech and 8085 utterances from 13 distinct domains.

Automatic Speech Recognition Automatic Speech Recognition (ASR) +2

On Stacked Denoising Autoencoder based Pre-training of ANN for Isolated Handwritten Bengali Numerals Dataset Recognition

no code implementations • 14 Dec 2018 • Al Mehdi Saadat Chowdhury, M. Shahidur Rahman, Asia Khanom, Tamanna Islam Chowdhury, Afaz Uddin

This work attempts to find the most optimal parameter setting of a deep artificial neural network (ANN) for Bengali digit dataset by pre-training it using stacked denoising autoencoder (SDA).

Denoising