41 citations · 48 across the 8 of their papers we have counts for
8 papers
Towards Word-Level End-to-End Neural Speaker Diarization with Auxiliary Network
Yiling Huang, Weiran Wang, Guanlong Zhao +3
While standard speaker diarization attempts to answer the question "who spoken when", most of relevant applications in reality are more interested in determining "who spoken what".…
USM-SCD: Multilingual Speaker Change Detection Based on Large Pretrained Foundation Models
Guanlong Zhao, Yongqiang Wang, Jason Pelecanos +5
We introduce a multilingual speaker change detection model (USM-SCD) that can simultaneously detect speaker turns and perform ASR for 96 languages. This model is adapted from a spe…
Augmenting Transformer-Transducer Based Speaker Change Detection With Token-Level Training Loss
Guanlong Zhao, Quan Wang, Han Lu +2
In this work we propose a novel token-based training strategy that improves Transformer-Transducer (T-T) based speaker change detection (SCD) performance. The conventional T-T base…
Exploring Sequence-to-Sequence Transformer-Transducer Models for Keyword Spotting
Beltrán Labrador, Guanlong Zhao, Ignacio López Moreno +3
In this paper, we present a novel approach to adapt a sequence-to-sequence Transformer-Transducer ASR system to the keyword spotting (KWS) task. We achieve this by replacing the ke…
Highly Efficient Real-Time Streaming and Fully On-Device Speaker Diarization with Multi-Stage Clustering
Quan Wang, Yiling Huang, Han Lu +2
While recent research advances in speaker diarization mostly focus on improving the quality of diarization results, there is also an increasing interest in improving the efficiency…
LSTM Acoustic Models Learn to Align and Pronounce with Graphemes
Arindrima Datta, Guanlong Zhao, Bhuvana Ramabhadran +1
Automated speech recognition coverage of the world's languages continues to expand. However, standard phoneme based systems require handcrafted lexicons that are difficult and expe…
Improved Techniques for Learning to Dehaze and Beyond: A Collective Study
Yu Liu, Guanlong Zhao, Boyuan Gong +8
Here we explore two related but important tasks based on the recently released REalistic Single Image DEhazing (RESIDE) benchmark dataset: (i) single image dehazing as a low-level…
PAD-Net: A Perception-Aided Single Image Dehazing Network
Yu Liu, Guanlong Zhao
In this work, we investigate the possibility of replacing the loss with perceptually derived loss functions (SSIM, MS-SSIM, etc.) in training an end-to-end dehazing neural…