In this paper, we perform an empirical study of performance of feed-forward NNLMs focusing on low-resource languages and transcriptions of conversational speech ...

It is shown that NNLMs learn better word probabilities than state-of-theart n-gram models even when the amount of training data is severely limited, ...

For resource rich languages, recent works have shown Neural Network based Language Models (NNLMs) to be an effective modeling technique for Automatic Speech ...

Apr 16, 2023 · The goal of this paper is to investigate the realm of low resource languages and build a Neural Machine Translation model to achieve state-of-the-art results.

Jan 27, 2024 · Machine translation for low-resource languages poses significant challenges, primarily due to the limited availability of data.

Jun 21, 2024 · Low-resource language neural networks refer to neural network models specifically constructed to tackle challenges associated with low-resource ...

Apr 12, 2024 · In this paper, we revisit state-of-the-art Neural Machine Translation techniques to develop automatic translation systems between German and Bavarian.

Large Language Models (LLMs) have achieved impressive results in Machine Translation by simply following instructions, even without training on parallel data.

Apr 14, 2014 · Hence in this work, we employ deep neural networks to perform continuous language modeling for low resource languages such as Vietnamese, Tamil ...

This article presents a detailed survey of research advancements in low-resource language NMT (LRL-NMT) and quantitative analysis to identify the most popular ...