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Hao Tang 0002
Person information
- affiliation: University of Edinburgh, School of Informatics, UK
- affiliation: Massachusetts Institute of Technology, Computer Science and Artificial Intelligence Laboratory, Cambridge, MA, USA
- affiliation (PhD 2017): Toyota Technological Institute at Chicago, IL, USA
- affiliation (former): National Taiwan University, Taipei, Taiwan
Other persons with the same name
- Hao Tang — disambiguation page
- Hao Tang 0001 — Hewlett-Packard Labs., Multimedia Interaction & Understanding Laboratory, Palo Alto, CA, USA (and 3 more)
- Hao Tang 0003
— Tsinghua University, Department of Philosophy, Beijing, China (and 4 more)
- Hao Tang 0004
- Hao Tang 0005
- Hao Tang 0006
- Hao Tang 0007
- Hao Tang 0008
- Hao Tang 0009
- Hao Tang 0010 — University of California, Irvine, Department of Computer Science, CA, USA
- Hao Tang 0011
- Hao Tang 0012
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2020 – today
- 2024
- [i30]Tzu-Quan Lin, Hung-yi Lee, Hao Tang:
DAISY: Data Adaptive Self-Supervised Early Exit for Speech Representation Models. CoRR abs/2406.05464 (2024) - [i29]Tzu-Quan Lin, Guan-Ting Lin, Hung-yi Lee, Hao Tang:
Property Neurons in Self-Supervised Speech Transformers. CoRR abs/2409.05910 (2024) - [i28]Sung-Lin Yeh, Hao Tang:
Estimating the Completeness of Discrete Speech Units. CoRR abs/2409.06109 (2024) - [i27]Gene-Ping Yang, Hao Tang:
A Simple HMM with Self-Supervised Representations for Phone Segmentation. CoRR abs/2409.09646 (2024) - 2023
- [j6]Siqi Sun
Improving Seq2Seq TTS Frontends With Transcribed Speech Audio. IEEE ACM Trans. Audio Speech Lang. Process. 31: 1940-1952 (2023) - [c29]Tzu-Quan Lin, Hung-Yi Lee, Hao Tang:
MelHuBERT: A Simplified Hubert on Mel Spectrograms. ASRU 2023: 1-8 - [c28]Gene-Ping Yang, Hao Tang:
Towards Matching Phones and Speech Representations. ASRU 2023: 1-8 - [c27]Sung-Lin Yeh, Hao Tang:
Learning Dependencies of Discrete Speech Representations with Neural Hidden Markov Models. ICASSP 2023: 1-5 - [c26]Chin-Yun Yu, Sung-Lin Yeh, György Fazekas, Hao Tang:
Conditioning and Sampling in Variational Diffusion Models for Speech Super-Resolution. ICASSP 2023: 1-5 - [i26]Gene-Ping Yang, Hao Tang:
Towards Matching Phones and Speech Representations. CoRR abs/2310.17558 (2023) - 2022
- [j5]Gene-Ping Yang
Autoregressive Predictive Coding: A Comprehensive Study. IEEE J. Sel. Top. Signal Process. 16(6): 1380-1390 (2022) - [c25]Gene-Ping Yang, Hao Tang:
Supervised Attention in Sequence-to-Sequence Models for Speech Recognition. ICASSP 2022: 7222-7226 - [c24]Dan Wells
Phonetic Analysis of Self-supervised Representations of English Speech. INTERSPEECH 2022: 3583-3587 - [c23]Sung-Lin Yeh, Hao Tang:
Autoregressive Co-Training for Learning Discrete Speech Representation. INTERSPEECH 2022: 5000-5004 - [c22]Yen Meng, Hsuan-Jui Chen, Jiatong Shi, Shinji Watanabe
On Compressing Sequences for Self-Supervised Speech Models. SLT 2022: 1128-1135 - [i25]Sung-Lin Yeh, Hao Tang:
Autoregressive Co-Training for Learning Discrete Speech Representations. CoRR abs/2203.15840 (2022) - [i24]Gene-Ping Yang, Hao Tang:
Supervised Attention in Sequence-to-Sequence Models for Speech Recognition. CoRR abs/2204.12308 (2022) - [i23]Yen Meng, Hsuan-Jui Chen, Jiatong Shi, Shinji Watanabe
On Compressing Sequences for Self-Supervised Speech Models. CoRR abs/2210.07189 (2022) - [i22]Chin-Yun Yu, Sung-Lin Yeh, György Fazekas, Hao Tang:
Conditioning and Sampling in Variational Diffusion Models for Speech Super-resolution. CoRR abs/2210.15793 (2022) - [i21]Sung-Lin Yeh, Hao Tang:
Learning Dependencies of Discrete Speech Representations with Neural Hidden Markov Models. CoRR abs/2210.16659 (2022) - [i20]Tzu-Quan Lin, Hung-yi Lee, Hao Tang:
MelHuBERT: A simplified HuBERT on Mel spectrogram. CoRR abs/2211.09944 (2022) - [i19]Tzu-Quan Lin, Tsung-Huan Yang, Chun-Yao Chang, Kuang-Ming Chen, Tzu-hsun Feng, Hung-yi Lee, Hao Tang:
Compressing Transformer-based self-supervised models for speech processing. CoRR abs/2211.09949 (2022) - 2020
- [c21]François Grondin, Hao Tang, James R. Glass:
Audio-Visual Calibration with Polynomial Regression for 2-D Projection Using SVD-PHAT. ICASSP 2020: 4856-4860 - [c20]Yu-An Chung, Hao Tang, James R. Glass:
Vector-Quantized Autoregressive Predictive Coding. INTERSPEECH 2020: 3760-3764 - [i18]François Grondin, Hao Tang, James R. Glass:
Audio-Visual Calibration with Polynomial Regression for 2-D Projection Using SVD-PHAT. CoRR abs/2002.01440 (2020) - [i17]Yu-An Chung, Hao Tang, James R. Glass:
Vector-Quantized Autoregressive Predictive Coding. CoRR abs/2005.08392 (2020)
2010 – 2019
- 2019
- [j4]Achintya Kumar Sarkar
Time-Contrastive Learning Based Deep Bottleneck Features for Text-Dependent Speaker Verification. IEEE ACM Trans. Audio Speech Lang. Process. 27(8): 1267-1279 (2019) - [c19]Yu-An Chung, Wei-Ning Hsu, Hao Tang, James R. Glass:
An Unsupervised Autoregressive Model for Speech Representation Learning. INTERSPEECH 2019: 146-150 - [c18]Logan Ford, Hao Tang, François Grondin, James R. Glass:
A Deep Residual Network for Large-Scale Acoustic Scene Analysis. INTERSPEECH 2019: 2568-2572 - [c17]Suwon Shon, Hao Tang, James R. Glass:
VoiceID Loss: Speech Enhancement for Speaker Verification. INTERSPEECH 2019: 2888-2892 - [i16]Yu-An Chung, Wei-Ning Hsu, Hao Tang, James R. Glass:
An Unsupervised Autoregressive Model for Speech Representation Learning. CoRR abs/1904.03240 (2019) - [i15]Suwon Shon, Hao Tang, James R. Glass:
VoiceID Loss: Speech Enhancement for Speaker Verification. CoRR abs/1904.03601 (2019) - [i14]Achintya Kumar Sarkar, Zheng-Hua Tan, Hao Tang, Suwon Shon, James R. Glass:
Time-Contrastive Learning Based Deep Bottleneck Features for Text-Dependent Speaker Verification. CoRR abs/1905.04554 (2019) - 2018
- [c16]Wei-Ning Hsu, Hao Tang, James R. Glass:
Unsupervised Adaptation with Interpretable Disentangled Representations for Distant Conversational Speech Recognition. INTERSPEECH 2018: 1576-1580 - [c15]Hao Tang, Wei-Ning Hsu, François Grondin, James R. Glass:
A Study of Enhancement, Augmentation and Autoencoder Methods for Domain Adaptation in Distant Speech Recognition. INTERSPEECH 2018: 2928-2932 - [c14]Hao Tang, James R. Glass:
On Training Recurrent Networks with Truncated Backpropagation Through time in Speech Recognition. SLT 2018: 48-55 - [c13]Suwon Shon, Hao Tang, James R. Glass:
Frame-Level Speaker Embeddings for Text-Independent Speaker Recognition and Analysis of End-to-End Model. SLT 2018: 1007-1013 - [i13]Hao Tang, Wei-Ning Hsu, François Grondin, James R. Glass:
A Study of Enhancement, Augmentation, and Autoencoder Methods for Domain Adaptation in Distant Speech Recognition. CoRR abs/1806.04841 (2018) - [i12]Wei-Ning Hsu, Hao Tang, James R. Glass:
Unsupervised Adaptation with Interpretable Disentangled Representations for Distant Conversational Speech Recognition. CoRR abs/1806.04872 (2018) - [i11]Hao Tang, James R. Glass:
On Training Recurrent Networks with Truncated Backpropagation Through Time in Speech Recognition. CoRR abs/1807.03396 (2018) - [i10]Suwon Shon, Hao Tang, James R. Glass:
Frame-level speaker embeddings for text-independent speaker recognition and analysis of end-to-end model. CoRR abs/1809.04437 (2018) - [i9]Hao Tang, James R. Glass:
On The Inductive Bias of Words in Acoustics-to-Word Models. CoRR abs/1810.13407 (2018) - 2017
- [j3]Taehwan Kim, Jonathan Keane, Weiran Wang, Hao Tang, Jason Riggle, Gregory Shakhnarovich, Diane Brentari, Karen Livescu
Lexicon-free fingerspelling recognition from video: Data, models, and signer adaptation. Comput. Speech Lang. 46: 209-232 (2017) - [j2]Hao Tang
End-to-End Neural Segmental Models for Speech Recognition. IEEE J. Sel. Top. Signal Process. 11(8): 1254-1264 (2017) - [j1]Mark A. Hasegawa-Johnson
ASR for Under-Resourced Languages From Probabilistic Transcription. IEEE ACM Trans. Audio Speech Lang. Process. 25(1): 46-59 (2017) - [c12]Shubham Toshniwal, Hao Tang, Liang Lu, Karen Livescu
Multitask Learning with Low-Level Auxiliary Tasks for Encoder-Decoder Based Speech Recognition. INTERSPEECH 2017: 3532-3536 - [i8]Shubham Toshniwal, Hao Tang, Liang Lu, Karen Livescu:
Multitask Learning with Low-Level Auxiliary Tasks for Encoder-Decoder Based Speech Recognition. CoRR abs/1704.01631 (2017) - [i7]Hao Tang, Liang Lu, Lingpeng Kong, Kevin Gimpel, Karen Livescu, Chris Dyer, Noah A. Smith, Steve Renals:
End-to-End Neural Segmental Models for Speech Recognition. CoRR abs/1708.00531 (2017) - [i6]Hao Tang:
Sequence Prediction with Neural Segmental Models. CoRR abs/1709.01572 (2017) - 2016
- [c11]Chunxi Liu, Preethi Jyothi, Hao Tang, Vimal Manohar, Rose Sloan, Tyler Kekona, Mark Hasegawa-Johnson, Sanjeev Khudanpur:
Adapting ASR for under-resourced languages using mismatched transcriptions. ICASSP 2016: 5840-5844 - [c10]Taehwan Kim, Weiran Wang, Hao Tang, Karen Livescu
Signer-independent fingerspelling recognition with deep neural network adaptation. ICASSP 2016: 6160-6164 - [c9]Hao Tang, Weiran Wang, Kevin Gimpel, Karen Livescu
Efficient Segmental Cascades for Speech Recognition. INTERSPEECH 2016: 1903-1907 - [c8]Weiran Wang, Hao Tang, Karen Livescu
Triphone State-Tying via Deep Canonical Correlation Analysis. INTERSPEECH 2016: 3444-3448 - [c7]Hao Tang, Weiran Wang, Kevin Gimpel, Karen Livescu
End-to-end training approaches for discriminative segmental models. SLT 2016: 496-502 - [i5]Taehwan Kim, Weiran Wang, Hao Tang, Karen Livescu:
Signer-independent Fingerspelling Recognition with Deep Neural Network Adaptation. CoRR abs/1602.04278 (2016) - [i4]Hao Tang, Weiran Wang, Kevin Gimpel, Karen Livescu:
Efficient Segmental Cascades for Speech Recognition. CoRR abs/1608.00929 (2016) - [i3]Taehwan Kim, Jonathan Keane, Weiran Wang, Hao Tang, Jason Riggle, Gregory Shakhnarovich, Diane Brentari, Karen Livescu:
Lexicon-Free Fingerspelling Recognition from Video: Data, Models, and Signer Adaptation. CoRR abs/1609.07876 (2016) - [i2]Hao Tang, Weiran Wang, Kevin Gimpel, Karen Livescu:
End-to-End Training Approaches for Discriminative Segmental Models. CoRR abs/1610.06700 (2016) - 2015
- [c6]Hao Tang, Weiran Wang, Kevin Gimpel, Karen Livescu
Discriminative segmental cascades for feature-rich phone recognition. ASRU 2015: 561-568 - [i1]Hao Tang, Weiran Wang, Kevin Gimpel, Karen Livescu:
Discriminative Segmental Cascades for Feature-Rich Phone Recognition. CoRR abs/1507.06073 (2015) - 2014
- [c5]Hao Tang, Shinji Watanabe
Log-linear dialog manager. ICASSP 2014: 4092-4096 - [c4]Hao Tang, Kevin Gimpel, Karen Livescu:
A comparison of training approaches for discriminative segmental models. INTERSPEECH 2014: 1219-1223 - 2012
- [c3]Hao Tang, Joseph Keshet, Karen Livescu:
Discriminative Pronunciation Modeling: A Large-Margin, Feature-Rich Approach. ACL (1) 2012: 194-203 - 2010
- [c2]Hao Tang, Chao-Hong Meng, Lin-Shan Lee:
An initial attempt for phoneme recognition using Structured Support Vector Machine (SVM). ICASSP 2010: 4926-4929
2000 – 2009
- 2009
- [c1]Hung-yi Lee
Spoken term detection from bilingual spontaneous speech using code-switched lattice-based structures for words and subword units. ASRU 2009: 410-415
Coauthor Index
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last updated on 2024-10-28 21:16 CET by the dblp team
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