no code implementations • 27 Apr 2022 • Sanyuan Chen, Yu Wu, Chengyi Wang, Shujie Liu, Zhuo Chen, Peidong Wang, Gang Liu, Jinyu Li, Jian Wu, Xiangzhan Yu, Furu Wei
Recently, self-supervised learning (SSL) has demonstrated strong performance in speaker recognition, even if the pre-training objective is designed for speech recognition.
no code implementations • 11 Apr 2022 • Jian Xue, Peidong Wang, Jinyu Li, Matt Post, Yashesh Gaur
Neural transducers have been widely used in automatic speech recognition (ASR).
no code implementations • 1 Mar 2022 • Yufeng Yang, Peidong Wang, DeLiang Wang
The proposed model builds on a state-of-the-art recognition system using a bi-directional long short-term memory (BLSTM) model with utterance-wise dropout and iterative speaker adaptation, but employs a Conformer encoder instead of the BLSTM network.
no code implementations • 29 Oct 2021 • Glenn Liu, Peidong Wang, Matthew Beveridge, Young-Oh Kwon, Iddo Drori
Atlantic Multidecadal Variability (AMV) describes variations of North Atlantic sea surface temperature with a typical cycle of between 60 and 70 years.
no code implementations • 28 Oct 2021 • Yixuan Zhang, Zhuo Chen, Jian Wu, Takuya Yoshioka, Peidong Wang, Zhong Meng, Jinyu Li
In this paper, we propose to apply recurrent selective attention network (RSAN) to CSS, which generates a variable number of output channels based on active speaker counting.
1 code implementation • ICCV 2021 • Yuwei Cheng, Jiannan Zhu, Mengxin Jiang, Jie Fu, Changsong Pang, Peidong Wang, Kris Sankaran, Olawale Onabola, Yimin Liu, Dianbo Liu, Yoshua Bengio
To promote the practical application for autonomous floating wastes cleaning, we present FloW, the first dataset for floating waste detection in inland water areas.
no code implementations • 9 Nov 2020 • Peidong Wang, DeLiang Wang
On-device end-to-end speech recognition poses a high requirement on model efficiency.
no code implementations • 27 Oct 2020 • Peidong Wang, Tara N. Sainath, Ron J. Weiss
We propose a multitask training method for attention-based end-to-end speech recognition models.
no code implementations • 20 Oct 2020 • Peidong Wang, Zhuo Chen, DeLiang Wang, Jinyu Li, Yifan Gong
We propose speaker separation using speaker inventories and estimated speech (SSUSIES), a framework leveraging speaker profiles and estimated speech for speaker separation.
2 code implementations • 4 Oct 2020 • Zhong-Qiu Wang, Peidong Wang, DeLiang Wang
Although our system is trained on simulated room impulse responses (RIR) based on a fixed number of microphones arranged in a given geometry, it generalizes well to a real array with the same geometry.
no code implementations • 11 Mar 2019 • Peidong Wang, Ke Tan, DeLiang Wang
In this study, we analyze the distortion problem, compare different acoustic models, and investigate a distortion-independent training scheme for monaural speech recognition.
no code implementations • 14 Dec 2016 • Peidong Wang, Zhongqiu Wang, DeLiang Wang
This paper presented our work on applying Recurrent Deep Stacking Networks (RDSNs) to Robust Automatic Speech Recognition (ASR) tasks.
no code implementations • 14 Dec 2016 • Peidong Wang, DeLiang Wang
This paper proposed a class of novel Deep Recurrent Neural Networks which can incorporate language-level information into acoustic models.