Communication has been an essential part of being human and living in society. There are
several different languages and variations of them, so you can speak English in one place …

Correct pronunciation is known to be the most difficult part to acquire for (native or non-
native) language learners. The accented speech is thus more variable, and standard …

Semi-supervised learning through pseudo-labeling has become a staple of state-of-the-art
monolingual speech recognition systems. In this work, we extend pseudo-labeling to …

This work explores better adaptation methods to low-resource languages using an external
language model (LM) under the framework of transfer learning. We first build a language …

Abstract Representation learning or pre-training has shown promising performance for low-
resource speech recognition which suffers from the data shortage. Recently, self-supervised …

With the acceleration of globalization, more and more people are willing or required to learn
second languages (L2). One of the major remaining challenges facing current …

Automatic speech recognition (ASR) is a crucial technology for man-machine interaction.
End-to-end models have been studied recently in deep learning for ASR. However, these …

The high cost of data acquisition makes Automatic Speech Recognition (ASR) model
training problematic for most existing languages, including languages that do not even have …

Speech recognition of a language is a key area in the field of pattern recognition. This paper
presents a comprehensive survey on the speech recognition techniques for non-Indian and …

Automatic speech recognition has made huge progress recently. However, the current
modeling strategy still suffers a large performance degradation when facing the low …