17 citations · 24 across the 7 of their papers we have counts for
8 papers
Active Learning for Neural Machine Translation
Neeraj Vashistha, Kriti Singh, Ramakant Shakya
The machine translation mechanism translates texts automatically between different natural languages, and Neural Machine Translation (NMT) has gained attention for its rational con…
XLS-R: Self-supervised Cross-lingual Speech Representation Learning at Scale
Arun Babu, Changhan Wang, Andros Tjandra +10
This paper presents XLS-R, a large-scale model for cross-lingual speech representation learning based on wav2vec 2.0. We train models with up to 2B parameters on nearly half a mill…
Conformer-Based Self-Supervised Learning for Non-Speech Audio Tasks
Sangeeta Srivastava, Yun Wang, Andros Tjandra +4
Representation learning from unlabeled data has been of major interest in artificial intelligence research. While self-supervised speech representation learning has been popular in…
Improved Language Identification Through Cross-Lingual Self-Supervised Learning
Andros Tjandra, Diptanu Gon Choudhury, Frank Zhang +6
Language identification greatly impacts the success of downstream tasks such as automatic speech recognition. Recently, self-supervised speech representations learned by wav2vec 2.…
A Multi-View Approach To Audio-Visual Speaker Verification
Leda Sarı, Kritika Singh, Jiatong Zhou +3
Although speaker verification has conventionally been an audio-only task, some practical applications provide both audio and visual streams of input. In these cases, the visual str…
Large scale weakly and semi-supervised learning for low-resource video ASR
Kritika Singh, Vimal Manohar, Alex Xiao +7
Many semi- and weakly-supervised approaches have been investigated for overcoming the labeling cost of building high quality speech recognition systems. On the challenging task of…
Training ASR models by Generation of Contextual Information
Kritika Singh, Dmytro Okhonko, Jun Liu +8
Supervised ASR models have reached unprecedented levels of accuracy, thanks in part to ever-increasing amounts of labelled training data. However, in many applications and locales,…
Multilingual Graphemic Hybrid ASR with Massive Data Augmentation
Chunxi Liu, Qiaochu Zhang, Xiaohui Zhang +3
Towards developing high-performing ASR for low-resource languages, approaches to address the lack of resources are to make use of data from multiple languages, and to augment the t…