1 citations · 1 across the 3 of their papers we have counts for
5 papers
BiRQ: Bi-Level Self-Labeling Random Quantization for Self-Supervised Speech Recognition
Liuyuan Jiang, Xiaodong Cui, Brian Kingsbury +2
Speech is a rich signal, and labeled audio-text pairs are costly, making self-supervised learning essential for scalable representation learning. A core challenge in speech SSL is…
Heterogeneous Self-Supervised Acoustic Pre-Training with Local Constraints
Xiaodong Cui, A F M Saif, Brian Kingsbury +1
Self-supervised pre-training using unlabeled data is widely used in automatic speech recognition. In this paper, we propose a new self-supervised pre-training approach to dealing w…
Objective Soups: Multilingual Multi-Task Modeling for Speech Processing
A F M Saif, Lisha Chen, Xiaodong Cui +3
Training a single model for multilingual, multi-task speech processing (MSP) is severely hampered by conflicting objectives between tasks like speech recognition and translation. W…
Granite-speech: open-source speech-aware LLMs with strong English ASR capabilities
George Saon, Avihu Dekel, Alexander Brooks +21
Granite-speech LLMs are compact and efficient speech language models specifically designed for English ASR and automatic speech translation (AST). The models were trained by modali…
Bilevel Joint Unsupervised and Supervised Training for Automatic Speech Recognition
Xiaodong Cui, A F M Saif, Songtao Lu +4
In this paper, we propose a bilevel joint unsupervised and supervised training (BL-JUST) framework for automatic speech recognition. Compared to the conventional pre-training and f…