Yan Huang

According to our database1, Yan Huang authored at least 15 papers between 2013 and 2020.

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

Timeline

Legend:

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PhD thesis 
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Online presence:

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Bibliography

2020
Rapid RNN-T Adaptation Using Personalized Speech Synthesis and Neural Language Generator.
Proceedings of the Interspeech 2020, 2020

L-Vector: Neural Label Embedding for Domain Adaptation.
Proceedings of the 2020 IEEE International Conference on Acoustics, 2020

Using Personalized Speech Synthesis and Neural Language Generator for Rapid Speaker Adaptation.
Proceedings of the 2020 IEEE International Conference on Acoustics, 2020

Acoustic Model Adaptation for Presentation Transcription and Intelligent Meeting Assistant Systems.
Proceedings of the 2020 IEEE International Conference on Acoustics, 2020

2019

2017
Don't Count on ASR to Transcribe for You: Breaking Bias with Two Crowds.
Proceedings of the Interspeech 2017, 2017

Improving Mask Learning Based Speech Enhancement System with Restoration Layers and Residual Connection.
Proceedings of the Interspeech 2017, 2017

Improved cepstra minimum-mean-square-error noise reduction algorithm for robust speech recognition.
Proceedings of the 2017 IEEE International Conference on Acoustics, 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
Semi-Supervised Training in Deep Learning Acoustic Model.
Proceedings of the Interspeech 2016, 2016

2015
Regularized sequence-level deep neural network model adaptation.
Proceedings of the INTERSPEECH 2015, 2015

2014
Multi-accent deep neural network acoustic model with accent-specific top layer using the KLD-regularized model adaptation.
Proceedings of the INTERSPEECH 2014, 2014

A comparative analytic study on the Gaussian mixture and context dependent deep neural network hidden Markov models.
Proceedings of the INTERSPEECH 2014, 2014

Towards better performance with heterogeneous training data in acoustic modeling using deep neural networks.
Proceedings of the INTERSPEECH 2014, 2014

2013
Semi-supervised GMM and DNN acoustic model training with multi-system combination and confidence re-calibration.
Proceedings of the INTERSPEECH 2013, 2013


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