Yan Huang
Affiliations:- Microsoft Corporation, Redmond, WA, USA
According to our database1,
Yan Huang
authored at least 17 papers
between 2013 and 2023.
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Bibliography
2023
Multi Transcription-Style Speech Transcription Using Attention-Based Encoder-Decoder Model.
Proceedings of the IEEE Automatic Speech Recognition and Understanding Workshop, 2023
2021
Rapid Speaker Adaptation for Conformer Transducer: Attention and Bias Are All You Need.
Proceedings of the Interspeech 2021, 22nd Annual Conference of the International Speech Communication Association, Brno, Czechia, 30 August, 2021
2020
Rapid RNN-T Adaptation Using Personalized Speech Synthesis and Neural Language Generator.
Proceedings of the Interspeech 2020, 2020
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
Proceedings of the IEEE Automatic Speech Recognition and Understanding Workshop, 2019
2017
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
Proceedings of the Interspeech 2016, 2016
2015
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