Rui Zhao

Affiliations:
  • Microsoft, USA


According to our database1, Rui Zhao authored at least 30 papers between 2014 and 2024.

Collaborative distances:
  • Dijkstra number2 of four.
  • Erdős number3 of four.

Timeline

Legend:

Book 
In proceedings 
Article 
PhD thesis 
Dataset
Other 

Links

On csauthors.net:

Bibliography

2024
Advanced Long-Content Speech Recognition With Factorized Neural Transducer.
IEEE ACM Trans. Audio Speech Lang. Process., 2024

Advanced Long-Content Speech Recognition With Factorized Neural Transducer.
CoRR, 2024

2023
t-SOT FNT: Streaming Multi-talker ASR with Text-only Domain Adaptation Capability.
CoRR, 2023

Hybrid Attention-based Encoder-decoder Model for Efficient Language Model Adaptation.
CoRR, 2023

Fast and Accurate Factorized Neural Transducer for Text Adaption of End-to-End Speech Recognition Models.
Proceedings of the IEEE International Conference on Acoustics, 2023

LongFNT: Long-Form Speech Recognition with Factorized Neural Transducer.
Proceedings of the IEEE International Conference on Acoustics, 2023

2021
Internal Language Model Estimation for Domain-Adaptive End-to-End Speech Recognition.
Proceedings of the IEEE Spoken Language Technology Workshop, 2021

Improving RNN-T for Domain Scaling Using Semi-Supervised Training with Neural TTS.
Proceedings of the Interspeech 2021, 22nd Annual Conference of the International Speech Communication Association, Brno, Czechia, 30 August, 2021

On Addressing Practical Challenges for RNN-Transducer.
Proceedings of the IEEE Automatic Speech Recognition and Understanding Workshop, 2021

2020
Combination of End-to-End and Hybrid Models for Speech Recognition.
Proceedings of the Interspeech 2020, 2020

Developing RNN-T Models Surpassing High-Performance Hybrid Models with Customization Capability.
Proceedings of the Interspeech 2020, 2020

On the Comparison of Popular End-to-End Models for Large Scale Speech Recognition.
Proceedings of the Interspeech 2020, 2020

Transfer Learning Approaches for Streaming End-to-End Speech Recognition System.
Proceedings of the Interspeech 2020, 2020

Adaptation of RNN Transducer with Text-To-Speech Technology for Keyword Spotting.
Proceedings of the 2020 IEEE International Conference on Acoustics, 2020

High-Accuracy and Low-Latency Speech Recognition with Two-Head Contextual Layer Trajectory LSTM Model.
Proceedings of the 2020 IEEE International Conference on Acoustics, 2020

Exploring Pre-Training with Alignments for RNN Transducer Based End-to-End Speech Recognition.
Proceedings of the 2020 IEEE International Conference on Acoustics, 2020

2019
Advancing Acoustic-to-Word CTC Model With Attention and Mixed-Units.
IEEE ACM Trans. Audio Speech Lang. Process., 2019

Towards Code-switching ASR for End-to-end CTC Models.
Proceedings of the IEEE International Conference on Acoustics, 2019

Improving RNN Transducer Modeling for End-to-End Speech Recognition.
Proceedings of the IEEE Automatic Speech Recognition and Understanding Workshop, 2019

2018
Improved Training for Online End-to-end Speech Recognition Systems.
Proceedings of the Interspeech 2018, 2018

Developing Far-Field Speaker System Via Teacher-Student Learning.
Proceedings of the 2018 IEEE International Conference on Acoustics, 2018

Advancing Acoustic-to-Word CTC Model.
Proceedings of the 2018 IEEE International Conference on Acoustics, 2018

Advancing Connectionist Temporal Classification with Attention Modeling.
Proceedings of the 2018 IEEE International Conference on Acoustics, 2018

2017
Large-Scale Domain Adaptation via Teacher-Student Learning.
Proceedings of the Interspeech 2017, 2017

Acoustic-to-word model without OOV.
Proceedings of the 2017 IEEE Automatic Speech Recognition and Understanding Workshop, 2017

Challenges in and Solutions to Deep Learning Network Acoustic Modeling in Speech Recognition Products at Microsoft.
Proceedings of the New Era for Robust Speech Recognition, Exploiting Deep Learning., 2017

2016
Recurrent support vector machines for speech recognition.
Proceedings of the 2016 IEEE International Conference on Acoustics, 2016

2014
Variable-activation and variable-input deep neural network for robust speech recognition.
Proceedings of the 2014 IEEE Spoken Language Technology Workshop, 2014

Variable-component deep neural network for robust speech recognition.
Proceedings of the INTERSPEECH 2014, 2014

Learning small-size DNN with output-distribution-based criteria.
Proceedings of the INTERSPEECH 2014, 2014


  Loading...