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2020 – today
- 2022
[j69]Iván López-Espejo
, Zheng-Hua Tan, John H. L. Hansen, Jesper Jensen:
Deep Spoken Keyword Spotting: An Overview. IEEE Access 10: 4169-4199 (2022)- [j68]Poul Hoang, Zheng-Hua Tan, Jan Mark de Haan, Jesper Jensen:
The Minimum Overlap-Gap Algorithm for Speech Enhancement. IEEE Access 10: 14698-14716 (2022) - [j67]Bjørn Uttrup Dideriksen, Kristoffer Derosche, Zheng-Hua Tan:
iVAE-GAN: Identifiable VAE-GAN Models for Latent Representation Learning. IEEE Access 10: 48405-48418 (2022) - [j66]Poul Hoang, Jan Mark de Haan, Zheng-Hua Tan, Jesper Jensen:
Multichannel Speech Enhancement With Own Voice-Based Interfering Speech Suppression for Hearing Assistive Devices. IEEE ACM Trans. Audio Speech Lang. Process. 30: 706-720 (2022) - [i49]Achintya Kumar Sarkar, Zheng-Hua Tan:
On Training Targets and Activation Functions for Deep Representation Learning in Text-Dependent Speaker Verification. CoRR abs/2201.06426 (2022) - [i48]Fan Yu, Shiliang Zhang, Pengcheng Guo, Yihui Fu, Zhihao Du, Siqi Zheng, Weilong Huang, Lei Xie, Zheng-Hua Tan, DeLiang Wang, Yanmin Qian, Kong Aik Lee, Zhijie Yan, Bin Ma, Xin Xu, Hui Bu:
Summary On The ICASSP 2022 Multi-Channel Multi-Party Meeting Transcription Grand Challenge. CoRR abs/2202.03647 (2022) - 2021
- [j65]Achintya Kumar Sarkar, Zheng-Hua Tan:
Self-segmentation of pass-phrase utterances for deep feature learning in text-dependent speaker verification. Comput. Speech Lang. 70: 101229 (2021) - [j64]Xiaoxu Li, Dongliang Chang, Zhanyu Ma, Zheng-Hua Tan, Jing-Hao Xue, Jie Cao, Jun Guo:
Deep InterBoost networks for small-sample image classification. Neurocomputing 456: 492-503 (2021) - [j63]Cristian J. Vaca-Rubio, Pablo Ramirez-Espinosa, Kimmo Kansanen, Zheng-Hua Tan, Elisabeth de Carvalho, Petar Popovski:
Assessing Wireless Sensing Potential With Large Intelligent Surfaces. IEEE Open J. Commun. Soc. 2: 934-947 (2021) - [j62]Achintya Kumar Sarkar, Zheng-Hua Tan:
Vocal Tract Length Perturbation for Text-Dependent Speaker Verification With Autoregressive Prediction Coding. IEEE Signal Process. Lett. 28: 364-368 (2021) - [j61]Daniel Michelsanti, Zheng-Hua Tan, Shi-Xiong Zhang, Yong Xu, Meng Yu, Dong Yu, Jesper Jensen:
An Overview of Deep-Learning-Based Audio-Visual Speech Enhancement and Separation. IEEE ACM Trans. Audio Speech Lang. Process. 29: 1368-1396 (2021) - [j60]Iván López-Espejo, Zheng-Hua Tan, Jesper Jensen:
A Novel Loss Function and Training Strategy for Noise-Robust Keyword Spotting. IEEE ACM Trans. Audio Speech Lang. Process. 29: 2254-2266 (2021) - [c102]Chien-Cheng Wu, Petar Popovski, Zheng-Hua Tan, Cedomir Stefanovic:
Design of AoI-Aware 5G Uplink Scheduler Using Reinforcement Learning. 5GWF 2021: 176-181 - [c101]Wei Rao, Yihui Fu, Yanxin Hu, Xin Xu, Yvkai Jv, Jiangyu Han, Zhongjie Jiang, Lei Xie, Yannan Wang, Shinji Watanabe, Zheng-Hua Tan, Hui Bu, Tao Yu, Shidong Shang:
Conferencingspeech Challenge: Towards Far-Field Multi-Channel Speech Enhancement for Video Conferencing. ASRU 2021: 679-686 - [c100]Deividas Eringis, John Leth, Zheng-Hua Tan, Rafal Wisniewski, Alireza Fakhrizadeh Esfahani, Mihály Petreczky:
PAC-Bayesian theory for stochastic LTI systems. CDC 2021: 6626-6633 - [c99]Poul Hoang, Zheng-Hua Tan, Jan Mark de Haan, Jesper Jensen:
Joint Maximum Likelihood Estimation of Power Spectral Densities and Relative Acoustic Transfer Functions for Acoustic Beamforming. ICASSP 2021: 6119-6123 - [c98]Giovanni Morrone, Daniel Michelsanti, Zheng-Hua Tan, Jesper Jensen:
Audio-Visual Speech Inpainting with Deep Learning. ICASSP 2021: 6653-6657 - [c97]Morten Østergaard Nielsen, Jan Østergaard, Jesper Jensen, Zheng-Hua Tan:
Compression of DNNs Using Magnitude Pruning and Nonlinear Information Bottleneck Training. MLSP 2021: 1-6 - [c96]Yuying Xie, Thomas Arildsen, Zheng-Hua Tan:
Disentangled Speech Representation Learning Based on Factorized Hierarchical Variational Autoencoder with Self-Supervised Objective. MLSP 2021: 1-6 - [c95]Md. Sahidullah, Achintya Kumar Sarkar, Ville Vestman, Xuechen Liu, Romain Serizel, Tomi Kinnunen, Zheng-Hua Tan, Emmanuel Vincent:
UIAI System for Short-Duration Speaker Verification Challenge 2020. SLT 2021: 323-329 - [c94]Anders E. Kalør, Daniel Michelsanti, Federico Chiariotti, Zheng-Hua Tan, Petar Popovski:
Remote Anomaly Detection in Industry 4.0 Using Resource-Constrained Devices. SPAWC 2021: 251-255 - [i47]Achintya Kumar Sarkar, Md. Sahidullah, Zheng-Hua Tan:
Data Generation Using Pass-phrase-dependent Deep Auto-encoders for Text-Dependent Speaker Verification. CoRR abs/2102.02074 (2021) - [i46]Deividas Eringis, John Leth, Zheng-Hua Tan, Rafal Wisniewski, Alireza Fakhrizadeh Esfahani, Mihály Petreczky:
PAC-Bayesian theory for stochastic LTI systems. CoRR abs/2103.12866 (2021) - [i45]Morten Kolbæk, Zheng-Hua Tan, Søren Holdt Jensen, Jesper Jensen:
On TasNet for Low-Latency Single-Speaker Speech Enhancement. CoRR abs/2103.14882 (2021) - [i44]Wei Rao, Yihui Fu, Yanxin Hu, Xin Xu, Yvkai Jv, Jiangyu Han, Zhongjie Jiang, Lei Xie, Yannan Wang, Shinji Watanabe, Zheng-Hua Tan, Hui Bu, Tao Yu, Shidong Shang:
INTERSPEECH 2021 ConferencingSpeech Challenge: Towards Far-field Multi-Channel Speech Enhancement for Video Conferencing. CoRR abs/2104.00960 (2021) - [i43]Max Væhrens, Andreas Jonas Fuglsig, Anders Post Jacobsen, Nicolai Almskou Rasmussen, Victor Mølbach Nissen, Joachim Roland Hejslet, Zheng-Hua Tan:
Improvement of Noise-Robust Single-Channel Voice Activity Detection with Spatial Pre-processing. CoRR abs/2104.05481 (2021) - [i42]Deividas Eringis, John Leth, Zheng-Hua Tan, Rafal Wisniewski, Mihály Petreczky:
Optimal Prediction of Unmeasured Output from Measurable Outputs In LTI Systems. CoRR abs/2109.02384 (2021) - [i41]Anders E. Kalør, Daniel Michelsanti, Federico Chiariotti, Zheng-Hua Tan, Petar Popovski:
Remote Anomaly Detection in Industry 4.0 Using Resource-Constrained Devices. CoRR abs/2110.05757 (2021) - [i40]Chien-Cheng Wu, Petar Popovski, Zheng-Hua Tan, Cedomir Stefanovic:
Design of AoI-Aware 5G Uplink Scheduler UsingReinforcement Learning. CoRR abs/2110.09995 (2021) - [i39]Andreas Jonas Fuglsig, Jan Østergaard, Jesper Jensen, Lars Søndergaard Bertelsen, Peter Mariager, Zheng-Hua Tan:
Joint Far- and Near-End Speech Intelligibility Enhancement based on the Approximated Speech Intelligibility Index. CoRR abs/2111.07759 (2021) - [i38]Iván López-Espejo, Zheng-Hua Tan, John H. L. Hansen, Jesper Jensen:
Deep Spoken Keyword Spotting: An Overview. CoRR abs/2111.10592 (2021) - 2020
- [j59]Zheng-Hua Tan, Achintya Kumar Sarkar, Najim Dehak:
rVAD: An unsupervised segment-based robust voice activity detection method. Comput. Speech Lang. 59: 1-21 (2020) - [j58]Bhaskar D. Rao, Zheng-Hua Tan:
Highlights From the Machine Learning for Signal Processing Technical Committee [In the Spotlight]. IEEE Signal Process. Mag. 37(6): 200-202 (2020) - [j57]Morten Kolbæk, Zheng-Hua Tan, Søren Holdt Jensen, Jesper Jensen:
On Loss Functions for Supervised Monaural Time-Domain Speech Enhancement. IEEE ACM Trans. Audio Speech Lang. Process. 28: 825-838 (2020) - [j56]Iván López-Espejo, Zheng-Hua Tan, Jesper Jensen:
Improved External Speaker-Robust Keyword Spotting for Hearing Assistive Devices. IEEE ACM Trans. Audio Speech Lang. Process. 28: 1233-1247 (2020) - [j55]Juan M. Martín-Doñas, Jesper Jensen, Zheng-Hua Tan, Angel M. Gomez, Antonio M. Peinado:
Online Multichannel Speech Enhancement Based on Recursive EM and DNN-Based Speech Presence Estimation. IEEE ACM Trans. Audio Speech Lang. Process. 28: 3080-3094 (2020) - [j54]Xiaoxu Li, Dongliang Chang, Zhanyu Ma, Zheng-Hua Tan, Jing-Hao Xue, Jie Cao, Jingyi Yu, Jun Guo:
OSLNet: Deep Small-Sample Classification With an Orthogonal Softmax Layer. IEEE Trans. Image Process. 29: 6482-6495 (2020) - [j53]Miklas Strøm Kristoffersen, Sven Ewan Shepstone, Zheng-Hua Tan:
The Importance of Context When Recommending TV Content: Dataset and Algorithms. IEEE Trans. Multim. 22(6): 1531-1541 (2020) - [c93]Cristian J. Vaca-Rubio, Pablo Ramirez-Espinosa, Robin Jess-Williams, Kimmo Kansanen, Zheng-Hua Tan, Elisabeth de Carvalho, Petar Popovski:
A Primer on Large Intelligent Surface (LIS) for Wireless Sensing in an Industrial Setting. CrownCom 2020: 126-138 - [c92]Iván López-Espejo, Zheng-Hua Tan, Jesper Jensen:
Exploring Filterbank Learning for Keyword Spotting. EUSIPCO 2020: 331-335 - [c91]Saeid Samizade, Zheng-Hua Tan, Chao Shen, Xiaohong Guan:
Adversarial Example Detection by Classification for Deep Speech Recognition. ICASSP 2020: 3102-3106 - [c90]Poul Hoang, Zheng-Hua Tan, Thomas Lunner, Jan Mark de Haan, Jesper Jensen:
Maximum Likelihood Estimation of the Interference-Plus-Noise Cross Power Spectral Density Matrix for Own Voice Retrieval. ICASSP 2020: 6939-6943 - [c89]Zeyu Song, Dongliang Chang, Zhanyu Ma, Xiaoxu Li, Zheng-Hua Tan:
CC-Loss: Channel Correlation Loss for Image Classification. ICPR 2020: 7601-7608 - [c88]Daniel Michelsanti, Olga Slizovskaia, Gloria Haro, Emilia Gómez, Zheng-Hua Tan, Jesper Jensen:
Vocoder-Based Speech Synthesis from Silent Videos. INTERSPEECH 2020: 3530-3534 - [i37]Miklas S. Kristoffersen, Sven Ewan Shepstone, Zheng-Hua Tan:
Context-Aware Recommendations for Televisions Using Deep Embeddings with Relaxed N-Pairs Loss Objective. CoRR abs/2002.01554 (2020) - [i36]Daniel Michelsanti, Olga Slizovskaia, Gloria Haro, Emilia Gómez, Zheng-Hua Tan, Jesper Jensen:
Vocoder-Based Speech Synthesis from Silent Videos. CoRR abs/2004.02541 (2020) - [i35]Xiaoxu Li, Dongliang Chang, Zhanyu Ma, Zheng-Hua Tan, Jing-Hao Xue, Jie Cao, Jingyi Yu, Jun Guo:
OSLNet: Deep Small-Sample Classification with an Orthogonal Softmax Layer. CoRR abs/2004.09033 (2020) - [i34]Achintya Kumar Sarkar, Zheng-Hua Tan:
On Bottleneck Features for Text-Dependent Speaker Verification Using X-vectors. CoRR abs/2005.07383 (2020) - [i33]Iván López-Espejo, Zheng-Hua Tan, Jesper Jensen:
Exploring Filterbank Learning for Keyword Spotting. CoRR abs/2006.00217 (2020) - [i32]Cristian J. Vaca-Rubio, Pablo Ramirez-Espinosa, Robin Jess-Williams, Kimmo Kansanen, Zheng-Hua Tan, Elisabeth de Carvalho, Petar Popovski:
A Primer on Large Intelligent Surface (LIS) for Wireless Sensing in an Industrial Setting. CoRR abs/2006.06563 (2020) - [i31]Achintya Kumar Sarkar, Himangshu Sarma, Priyanka Dwivedi, Zheng-Hua Tan:
Data augmentation enhanced speaker enrollment for text-dependent speaker verification. CoRR abs/2007.08004 (2020) - [i30]Md. Sahidullah, Achintya Kumar Sarkar, Ville Vestman, Xuechen Liu, Romain Serizel, Tomi Kinnunen, Zheng-Hua Tan, Emmanuel Vincent:
UIAI System for Short-Duration Speaker Verification Challenge 2020. CoRR abs/2007.13118 (2020) - [i29]Daniel Michelsanti, Zheng-Hua Tan, Shi-Xiong Zhang, Yong Xu, Meng Yu, Dong Yu, Jesper Jensen:
An Overview of Deep-Learning-Based Audio-Visual Speech Enhancement and Separation. CoRR abs/2008.09586 (2020) - [i28]Giovanni Morrone, Daniel Michelsanti, Zheng-Hua Tan, Jesper Jensen:
Audio-Visual Speech Inpainting with Deep Learning. CoRR abs/2010.04556 (2020) - [i27]Jiyang Xie, Zhanyu Ma, Guoqiang Zhang, Jing-Hao Xue, Zheng-Hua Tan, Jun Guo:
Advanced Dropout: A Model-free Methodology for Bayesian Dropout Optimization. CoRR abs/2010.05244 (2020) - [i26]Zeyu Song, Dongliang Chang, Zhanyu Ma, Xiaoxu Li, Zheng-Hua Tan:
CC-Loss: Channel Correlation Loss For Image Classification. CoRR abs/2010.05469 (2020) - [i25]Cristian J. Vaca-Rubio, Pablo Ramirez-Espinosa, Kimmo Kansanen, Zheng-Hua Tan, Elisabeth de Carvalho, Petar Popovski:
Assessing Wireless Sensing Potential with Large Intelligent Surfaces. CoRR abs/2011.08465 (2020) - [i24]Achintya Kumar Sarkar, Zheng-Hua Tan:
Vocal Tract Length Perturbation for Text-Dependent Speaker Verification with Autoregressive Prediction Coding. CoRR abs/2011.12536 (2020)
2010 – 2019
- 2019
- [j52]Yonggang Qi, Zheng-Hua Tan:
SketchSegNet+: An End-to-End Learning of RNN for Multi-Class Sketch Semantic Segmentation. IEEE Access 7: 102717-102726 (2019) - [j51]Daniel Michelsanti, Zheng-Hua Tan, Sigurdur Sigurdsson, Jesper Jensen:
Deep-learning-based audio-visual speech enhancement in presence of Lombard effect. Speech Commun. 115: 38-50 (2019) - [j50]Morten Kolbaek, Zheng-Hua Tan, Jesper Jensen:
On the Relationship Between Short-Time Objective Intelligibility and Short-Time Spectral-Amplitude Mean-Square Error for Speech Enhancement. IEEE ACM Trans. Audio Speech Lang. Process. 27(2): 283-295 (2019) - [j49]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. IEEE ACM Trans. Audio Speech Lang. Process. 27(8): 1267-1279 (2019) - [c87]Poul Hoang, Zheng-Hua Tan, Jan Mark de Haan, Thomas Lunner, Jesper Jensen:
Robust Bayesian and Maximum a Posteriori Beamforming for Hearing Assistive Devices. GlobalSIP 2019: 1-5 - [c86]Daniel Michelsanti, Zheng-Hua Tan, Sigurdur Sigurdsson, Jesper Jensen:
Effects of Lombard Reflex on the Performance of Deep-learning-based Audio-visual Speech Enhancement Systems. ICASSP 2019: 6615-6619 - [c85]Daniel Michelsanti, Zheng-Hua Tan, Sigurdur Sigurdsson, Jesper Jensen:
On Training Targets and Objective Functions for Deep-learning-based Audio-visual Speech Enhancement. ICASSP 2019: 8077-8081 - [c84]Iván López-Espejo, Zheng-Hua Tan, Jesper Jensen:
Keyword Spotting for Hearing Assistive Devices Robust to External Speakers. INTERSPEECH 2019: 3223-3227 - [c83]Jiyang Xie, Zhanyu Ma, Guoqiang Zhang, Jing-Hao Xue, Zheng-Hua Tan, Jun Guo:
Soft Dropout And Its Variational Bayes Approximation. MLSP 2019: 1-6 - [c82]Andrea Coifman, Péter Rohoska, Miklas S. Kristoffersen, Sven Ewan Shepstone, Zheng-Hua Tan:
Subjective Annotations for Vision-based Attention Level Estimation. VISIGRAPP (5: VISAPP) 2019: 249-256 - [i23]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) - [i22]Daniel Michelsanti, Zheng-Hua Tan, Sigurdur Sigurdsson, Jesper Jensen:
Deep-Learning-Based Audio-Visual Speech Enhancement in Presence of Lombard Effect. CoRR abs/1905.12605 (2019) - [i21]Zheng-Hua Tan, Achintya Kumar Sarkar, Najim Dehak:
rVAD: An Unsupervised Segment-Based Robust Voice Activity Detection Method. CoRR abs/1906.03588 (2019) - [i20]Iván López-Espejo, Zheng-Hua Tan, Jesper Jensen:
Keyword Spotting for Hearing Assistive Devices Robust to External Speakers. CoRR abs/1906.09417 (2019) - [i19]Morten Kolbæk, Zheng-Hua Tan, Søren Holdt Jensen, Jesper Jensen:
On Loss Functions for Supervised Monaural Time-Domain Speech Enhancement. CoRR abs/1909.01019 (2019) - [i18]Miklas S. Kristoffersen, Jacob L. Wieland, Sven Ewan Shepstone, Zheng-Hua Tan, Vinoba Vinayagamoorthy:
Deep Joint Embeddings of Context and Content for Recommendation. CoRR abs/1909.06076 (2019) - [i17]Saeid Samizade, Zheng-Hua Tan, Chao Shen, Xiaohong Guan:
Adversarial Example Detection by Classification for Deep Speech Recognition. CoRR abs/1910.10013 (2019) - 2018
- [j48]Achintya Kumar Sarkar, Zheng-Hua Tan:
Incorporating pass-phrase dependent background models for text-dependent speaker verification. Comput. Speech Lang. 47: 259-271 (2018) - [j47]Zhanyu Ma, Jen-Tzung Chien, Zheng-Hua Tan, Yi-Zhe Song, Jalil Taghia, Ming Xiao:
Recent advances in machine learning for non-Gaussian data processing. Neurocomputing 278: 1-3 (2018) - [j46]Jen-Tzung Chien, Chao-Hsi Lee, Zheng-Hua Tan:
Latent Dirichlet mixture model. Neurocomputing 278: 12-22 (2018) - [j45]Zheng-Hua Tan, Nicolai Bæk Thomsen, Xiaodong Duan, Evgenios Vlachos, Sven Ewan Shepstone, Morten Højfeldt Rasmussen, Jesper Lisby Højvang:
iSocioBot: A Multimodal Interactive Social Robot. Int. J. Soc. Robotics 10(1): 5-19 (2018) - [j44]Xiaodong Duan, Zheng-Hua Tan:
A spatial self-similarity based feature learning method for face recognition under varying poses. Pattern Recognit. Lett. 111: 109-116 (2018) - [j43]Renhua Peng, Zheng-Hua Tan, Xiaodong Li, Chengshi Zheng:
A perceptually motivated LP residual estimator in noisy and reverberant environments. Speech Commun. 96: 129-141 (2018) - [j42]Asger Heidemann Andersen, Jan Mark de Haan, Zheng-Hua Tan, Jesper Jensen:
Refinement and validation of the binaural short time objective intelligibility measure for spatially diverse conditions. Speech Commun. 102: 1-13 (2018) - [j41]Sven Ewan Shepstone, Zheng-Hua Tan, Søren Holdt Jensen:
Audio-Based Granularity-Adapted Emotion Classification. IEEE Trans. Affect. Comput. 9(2): 176-190 (2018) - [j40]Md. Sahidullah, Dennis Alexander Lehmann Thomsen, Rosa González Hautamäki, Tomi Kinnunen, Zheng-Hua Tan, Robert Parts, Martti Pitkänen:
Robust Voice Liveness Detection and Speaker Verification Using Throat Microphones. IEEE ACM Trans. Audio Speech Lang. Process. 26(1): 44-56 (2018) - [j39]Mojtaba Farmani, Michael Syskind Pedersen, Zheng-Hua Tan, Jesper Jensen:
Bias-Compensated Informed Sound Source Localization Using Relative Transfer Functions. IEEE ACM Trans. Audio Speech Lang. Process. 26(7): 1271-1285 (2018) - [j38]Asger Heidemann Andersen, Jan Mark de Haan, Zheng-Hua Tan, Jesper Jensen:
Nonintrusive Speech Intelligibility Prediction Using Convolutional Neural Networks. IEEE ACM Trans. Audio Speech Lang. Process. 26(10): 1925-1939 (2018) - [j37]Sven Ewan Shepstone, Zheng-Hua Tan, Miklas S. Kristoffersen:
Using Closed-Set Speaker Identification Score Confidence to Enhance Audio-Based Collaborative Filtering for Multiple Users. IEEE Trans. Consumer Electron. 64(1): 11-18 (2018) - [j36]Zhanyu Ma, Jing-Hao Xue, Arne Leijon, Zheng-Hua Tan, Zhen Yang, Jun Guo:
Decorrelation of Neutral Vector Variables: Theory and Applications. IEEE Trans. Neural Networks Learn. Syst. 29(1): 129-143 (2018) - [j35]Hong Yu, Zheng-Hua Tan, Zhanyu Ma, Rainer Martin, Jun Guo:
Spoofing Detection in Automatic Speaker Verification Systems Using DNN Classifiers and Dynamic Acoustic Features. IEEE Trans. Neural Networks Learn. Syst. 29(10): 4633-4644 (2018) - [j34]Jun Guo, Zheng-Hua Tan, Sung Ho Cho, Guoqiang Zhang:
Wireless Personal Communications: Machine Learning for Big Data Processing in Mobile Internet. Wirel. Pers. Commun. 102(3): 2093-2098 (2018) - [c81]Morten Kolbæk, Zheng-Hua Tan, Jesper Jensen:
Monaural Speech Enhancement Using Deep Neural Networks by Maximizing a Short-Time Objective Intelligibility Measure. ICASSP 2018: 5059-5063 - [c80]Peter Sibbern Frederiksen, Jesús Villalba, Shinji Watanabe, Zheng-Hua Tan, Najim Dehak:
Effectiveness of Single-Channel BLSTM Enhancement for Language Identification. INTERSPEECH 2018: 1823-1827 - [c79]Evgenios Vlachos, Zheng-Hua Tan:
Public perception of android robots: Indications from an analysis of YouTube comments. IROS 2018: 1255-1260 - [c78]Gabriele Trovato, Renato Paredes, Javier Balvin, Francisco Cuéllar, Nicolai Bæk Thomsen, Søren Bech, Zheng-Hua Tan:
The Sound or Silence: Investigating the Influence of Robot Noise on Proxemics. RO-MAN 2018: 713-718 - [c77]Miklas S. Kristoffersen, Sven Ewan Shepstone, Zheng-Hua Tan:
A Dataset for Inferring Contextual Preferences of Users Watching TV. UMAP 2018: 367-368 - [i16]Morten Kolbæk, Zheng-Hua Tan, Jesper Jensen:
Monaural Speech Enhancement using Deep Neural Networks by Maximizing a Short-Time Objective Intelligibility Measure. CoRR abs/1802.00604 (2018) - [i15]Ioannis T. Christou, Emmanouil Amolochitis, Zheng-Hua Tan:
A Parallel/Distributed Algorithmic Framework for Mining All Quantitative Association Rules. CoRR abs/1804.06764 (2018) - [i14]Morten Kolbæk, Zheng-Hua Tan, Jesper Jensen:
On the Equivalence between Objective Intelligibility and Mean-Squared Error for Deep Neural Network based Speech Enhancement. CoRR abs/1806.08404 (2018) - [i13]Miklas S. Kristoffersen, Sven Ewan Shepstone, Zheng-Hua Tan:
The Importance of Context When Recommending TV Content: Dataset and Algorithms. CoRR abs/1808.00337 (2018) - [i12]Daniel Michelsanti, Zheng-Hua Tan, Sigurdur Sigurdsson, Jesper Jensen:
On Training Targets and Objective Functions for Deep-Learning-Based Audio-Visual Speech Enhancement. CoRR abs/1811.06234 (2018) - [i11]Daniel Michelsanti, Zheng-Hua Tan, Sigurdur Sigurdsson, Jesper Jensen:
Effects of Lombard Reflex on the Performance of Deep-Learning-Based Audio-Visual Speech Enhancement Systems. CoRR abs/1811.06250 (2018) - [i10]Andrea Coifman, Péter Rohoska, Miklas S. Kristoffersen, Sven Ewan Shepstone, Zheng-Hua Tan:
Subjective Annotations for Vision-Based Attention Level Estimation. CoRR abs/1812.04949 (2018) - 2017
- [j33]Hong Yu, Zheng-Hua Tan, Yiming Zhang, Zhanyu Ma, Jun Guo:
DNN Filter Bank Cepstral Coefficients for Spoofing Detection. IEEE Access 5: 4779-4787 (2017) - [j32]Morten Kolbæk, Zheng-Hua Tan, Jesper Jensen:
Speech Intelligibility Potential of General and Specialized Deep Neural Network Based Speech Enhancement Systems. IEEE ACM Trans. Audio Speech Lang. Process. 25(1): 149-163 (2017) - [j31]Mojtaba Farmani, Michael Syskind Pedersen, Zheng-Hua Tan, Jesper Jensen:
Informed Sound Source Localization Using Relative Transfer Functions for Hearing Aid Applications. IEEE ACM Trans. Audio Speech Lang. Process. 25(3): 611-623 (2017) - [j30]Morten Kolbaek, Dong Yu, Zheng-Hua Tan, Jesper Jensen:
Multitalker Speech Separation With Utterance-Level Permutation Invariant Training of Deep Recurrent Neural Networks. IEEE ACM Trans. Audio Speech Lang. Process. 25(10): 1901-1913 (2017) - [j29]Swati Prasad, Zheng-Hua Tan, Ramjee Prasad:
Frame Selection for Robust Speaker Identification: A Hybrid Approach. Wirel. Pers. Commun. 97(1): 933-950 (2017) - [j28]Stefanos Astaras, Aristodemos Pnevmatikakis, Zheng-Hua Tan:
Visual Detection of Events of Interest from Urban Activity. Wirel. Pers. Commun. 97(2): 1877-1888 (2017) - [c76]Dong Yu, Morten Kolbæk, Zheng-Hua Tan, Jesper Jensen:
Permutation invariant training of deep models for speaker-independent multi-talker speech separation. ICASSP 2017: 241-245 - [c75]Asger Heidemann Andersen, Jan Mark de Haan, Zheng-Hua Tan, Jesper Jensen:
A non-intrusive Short-Time Objective Intelligibility measure. ICASSP 2017: 5085-5089 - [c74]Tomi Kinnunen, Md. Sahidullah, Mauro Falcone, Luca Costantini, Rosa González Hautamäki, Dennis Alexander Lehmann Thomsen, Achintya Kumar Sarkar, Zheng-Hua Tan, Héctor Delgado, Massimiliano Todisco, Nicholas W. D. Evans, Ville Hautamäki, Kong-Aik Lee:
RedDots replayed: A new replay spoofing attack corpus for text-dependent speaker verification research. ICASSP 2017: 5395-5399 - [c73]Xiaodong Duan, Nicolai Bæk Thomsen, Zheng-Hua Tan, Børge Lindberg, Søren Holdt Jensen:
Weighted Score Based Fast Converging CO-training with Application to Audio-Visual Person Identification. ICTAI 2017: 610-617 - [c72]Hong Yu, Zheng-Hua Tan, Zhanyu Ma, Jun Guo:
Adversarial Network Bottleneck Features for Noise Robust Speaker Verification. INTERSPEECH 2017: 1492-1496 - [c71]Daniel Michelsanti, Zheng-Hua Tan:
Conditional Generative Adversarial Networks for Speech Enhancement and Noise-Robust Speaker Verification. INTERSPEECH 2017: 2008-2012 - [c70]Achintya Kumar Sarkar, Md. Sahidullah, Zheng-Hua Tan, Tomi Kinnunen:
Improving Speaker Verification Performance in Presence of Spoofing Attacks Using Out-of-Domain Spoofed Data. INTERSPEECH 2017: 2611-2615