# Challenges and Opportunities of Speech Recognition for Bengali Language

arXiv: https://arxiv.org/abs/2109.13217 · HTML: https://mlsanity.com/paper/2109.13217/

## Key facts

- Cited by 1 papers in the map (data through 14 Oct 2026).
- Builds on 10 of its 96 references that are in the map.
- First posted on arXiv 27 Sep 2021.

## Builds on (most cited first, 10 of 10)

- [wav2vec 2.0: A Framework for Self-Supervised Learning of Speech Representations](https://mlsanity.com/paper/2006.11477/) (2020)
- [Empirical Evaluation of Gated Recurrent Neural Networks on Sequence Modeling](https://mlsanity.com/paper/1412.3555/) (2014)
- [Attention-Based Models for Speech Recognition](https://mlsanity.com/paper/1506.07503/) (2015)
- [Deep Speech: Scaling up end-to-end speech recognition](https://mlsanity.com/paper/1412.5567/) (2014)
- [Light Gated Recurrent Units for Speech Recognition](https://mlsanity.com/paper/1803.10225/) (2018)
- [Meta Learning for End-to-End Low-Resource Speech Recognition](https://mlsanity.com/paper/1910.12094/) (2019)
- [Building competitive direct acoustics-to-word models for English conversational speech recognition](https://mlsanity.com/paper/1712.03133/) (2017)
- [Implementation Of Back-Propagation Neural Network For Isolated Bangla Speech Recognition](https://mlsanity.com/paper/1308.3785/) (2013)
- [Prodorshok I: A Bengali Isolated Speech Dataset for Voice-Based Assistive Technologies - A comparative analysis of the effects of data augmentation on HMM-GMM and DNN classifiers](https://mlsanity.com/paper/1712.03579/) (2017)
- [Comprehending Real Numbers: Development of Bengali Real Number Speech Corpus](https://mlsanity.com/paper/1803.10136/) (2018)

## Built on by (most cited first, 1 of 1)

- [Model Adaptation for ASR in low-resource Indian Languages](https://mlsanity.com/paper/2307.07948/) (2023)

## Abstract (arXiv)

Speech recognition is a fascinating process that offers the opportunity to interact and command the machine in the field of human-computer interactions. Speech recognition is a language-dependent system constructed directly based on the linguistic and textual properties of any language. Automatic Speech Recognition (ASR) systems are currently being used to translate speech to text flawlessly. Although ASR systems are being strongly executed in international languages, ASR systems' implementation in the Bengali language has not reached an acceptable state. In this research work, we sedulously disclose the current status of the Bengali ASR system's research endeavors. In what follows, we acquaint the challenges that are mostly encountered while constructing a Bengali ASR system. We split the challenges into language-dependent and language-independent challenges and guide how the particular complications may be overhauled. Following a rigorous investigation and highlighting the challenges, we conclude that Bengali ASR systems require specific construction of ASR architectures based on the Bengali language's grammatical and phonetic structure.