Search Results for author: Qiao Liang

Found 14 papers, 3 papers with code

Personal VAD 2.0: Optimizing Personal Voice Activity Detection for On-Device Speech Recognition

no code implementations8 Apr 2022 Shaojin Ding, Rajeev Rikhye, Qiao Liang, Yanzhang He, Quan Wang, Arun Narayanan, Tom O'Malley, Ian McGraw

Personalization of on-device speech recognition (ASR) has seen explosive growth in recent years, largely due to the increasing popularity of personal assistant features on mobile devices and smart home speakers.

Action Detection Activity Detection +1

Closing the Gap between Single-User and Multi-User VoiceFilter-Lite

no code implementations24 Feb 2022 Rajeev Rikhye, Quan Wang, Qiao Liang, Yanzhang He, Ian McGraw

However, one limitation of VoiceFilter-Lite, and other speaker-conditioned speech models in general, is that these models are usually limited to a single target speaker.

Speaker Verification Speech Recognition

Multi-user VoiceFilter-Lite via Attentive Speaker Embedding

no code implementations2 Jul 2021 Rajeev Rikhye, Quan Wang, Qiao Liang, Yanzhang He, Ian McGraw

In this paper, we propose a solution to allow speaker conditioned speech models, such as VoiceFilter-Lite, to support an arbitrary number of enrolled users in a single pass.

Automatic Speech Recognition Text-Independent Speaker Verification

Personalized Keyphrase Detection using Speaker and Environment Information

no code implementations28 Apr 2021 Rajeev Rikhye, Quan Wang, Qiao Liang, Yanzhang He, Ding Zhao, Yiteng, Huang, Arun Narayanan, Ian McGraw

In this paper, we introduce a streaming keyphrase detection system that can be easily customized to accurately detect any phrase composed of words from a large vocabulary.

Automatic Speech Recognition Speaker Separation +1

JST-RR Model: Joint Modeling of Ratings and Reviews in Sentiment-Topic Prediction

no code implementations18 Feb 2021 Qiao Liang, Shyam Ranganathan, Kaibo Wang, Xinwei Deng

In this work, we propose a probabilistic model to accommodate both textual reviews and overall ratings with consideration of their intrinsic connection for a joint sentiment-topic prediction.

A Better and Faster End-to-End Model for Streaming ASR

no code implementations21 Nov 2020 Bo Li, Anmol Gulati, Jiahui Yu, Tara N. Sainath, Chung-Cheng Chiu, Arun Narayanan, Shuo-Yiin Chang, Ruoming Pang, Yanzhang He, James Qin, Wei Han, Qiao Liang, Yu Zhang, Trevor Strohman, Yonghui Wu

To address this, we explore replacing the LSTM layers in the encoder of our E2E model with Conformer layers [4], which has shown good improvements for ASR.

Audio and Speech Processing Sound

Dynamic Sparsity Neural Networks for Automatic Speech Recognition

no code implementations16 May 2020 Zhaofeng Wu, Ding Zhao, Qiao Liang, Jiahui Yu, Anmol Gulati, Ruoming Pang

In automatic speech recognition (ASR), model pruning is a widely adopted technique that reduces model size and latency to deploy neural network models on edge devices with resource constraints.

Automatic Speech Recognition

A Streaming On-Device End-to-End Model Surpassing Server-Side Conventional Model Quality and Latency

no code implementations28 Mar 2020 Tara N. Sainath, Yanzhang He, Bo Li, Arun Narayanan, Ruoming Pang, Antoine Bruguier, Shuo-Yiin Chang, Wei Li, Raziel Alvarez, Zhifeng Chen, Chung-Cheng Chiu, David Garcia, Alex Gruenstein, Ke Hu, Minho Jin, Anjuli Kannan, Qiao Liang, Ian McGraw, Cal Peyser, Rohit Prabhavalkar, Golan Pundak, David Rybach, Yuan Shangguan, Yash Sheth, Trevor Strohman, Mirko Visontai, Yonghui Wu, Yu Zhang, Ding Zhao

Thus far, end-to-end (E2E) models have not been shown to outperform state-of-the-art conventional models with respect to both quality, i. e., word error rate (WER), and latency, i. e., the time the hypothesis is finalized after the user stops speaking.

Optimizing Speech Recognition For The Edge

no code implementations26 Sep 2019 Yuan Shangguan, Jian Li, Qiao Liang, Raziel Alvarez, Ian McGraw

While most deployed speech recognition systems today still run on servers, we are in the midst of a transition towards deployments on edge devices.

Quantization Speech Recognition

Lingvo: a Modular and Scalable Framework for Sequence-to-Sequence Modeling

3 code implementations21 Feb 2019 Jonathan Shen, Patrick Nguyen, Yonghui Wu, Zhifeng Chen, Mia X. Chen, Ye Jia, Anjuli Kannan, Tara Sainath, Yuan Cao, Chung-Cheng Chiu, Yanzhang He, Jan Chorowski, Smit Hinsu, Stella Laurenzo, James Qin, Orhan Firat, Wolfgang Macherey, Suyog Gupta, Ankur Bapna, Shuyuan Zhang, Ruoming Pang, Ron J. Weiss, Rohit Prabhavalkar, Qiao Liang, Benoit Jacob, Bowen Liang, HyoukJoong Lee, Ciprian Chelba, Sébastien Jean, Bo Li, Melvin Johnson, Rohan Anil, Rajat Tibrewal, Xiaobing Liu, Akiko Eriguchi, Navdeep Jaitly, Naveen Ari, Colin Cherry, Parisa Haghani, Otavio Good, Youlong Cheng, Raziel Alvarez, Isaac Caswell, Wei-Ning Hsu, Zongheng Yang, Kuan-Chieh Wang, Ekaterina Gonina, Katrin Tomanek, Ben Vanik, Zelin Wu, Llion Jones, Mike Schuster, Yanping Huang, Dehao Chen, Kazuki Irie, George Foster, John Richardson, Klaus Macherey, Antoine Bruguier, Heiga Zen, Colin Raffel, Shankar Kumar, Kanishka Rao, David Rybach, Matthew Murray, Vijayaditya Peddinti, Maxim Krikun, Michiel A. U. Bacchiani, Thomas B. Jablin, Rob Suderman, Ian Williams, Benjamin Lee, Deepti Bhatia, Justin Carlson, Semih Yavuz, Yu Zhang, Ian McGraw, Max Galkin, Qi Ge, Golan Pundak, Chad Whipkey, Todd Wang, Uri Alon, Dmitry Lepikhin, Ye Tian, Sara Sabour, William Chan, Shubham Toshniwal, Baohua Liao, Michael Nirschl, Pat Rondon

Lingvo is a Tensorflow framework offering a complete solution for collaborative deep learning research, with a particular focus towards sequence-to-sequence models.

Sequence-To-Sequence Speech Recognition

To Know Where We Are: Vision-Based Positioning in Outdoor Environments

no code implementations19 Jun 2015 Kuan-Wen Chen, Chun-Hsin Wang, Xiao Wei, Qiao Liang, Ming-Hsuan Yang, Chu-Song Chen, Yi-Ping Hung

Augmented reality (AR) displays become more and more popular recently, because of its high intuitiveness for humans and high-quality head-mounted display have rapidly developed.

Image Registration Model Compression

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