J. Cho, R. Pappagari, P. Zelasko, L. Moro-Velazquez, J. Villalba, and N. Dehak, "Non-Contrastive Self-Supervised Learning of Utterance-Level Speech Representation,” submitted Proc. ICASSP, Singapore, May, 2022.

A. Hussein, S. Chowdhury, A. Abdelali, A. Ali, and N. Dehak, "Code-Switching Text Augmentation for Multilingual Speech Processing,” submitted Proc. ICASSP, Singapore, May, 2022.

P. Zelasko, S. Joshi, Y. Shao, J. Villalba, J. Trmal, N. Dehak, S. Khudanpur, "Parallel WaveGAN Vocoder Re-Synthesis as Adversarial Defense for ASR,” submitted Proc. ICASSP, Singapore, May, 2022.

P. Zelasko, R. Pappagari, and N. Dehak, “What Helps Transformers Recognize Conversational Structure? Importance of Context, Punctuation, and Labels in Dialog Act Recognition.” Transactions of the Association for Computational Linguistics 9, 2021.

S. Joshi , J. Villalba, P. Zelasko, L. Moro-Velazquez, and N. Dehak, “Study of Pre-processing Defenses against Adversarial Attacks on State-of-the-art Speaker Recognition Systems,” IEEE Transactions on Information Forensics and Security, 16, 2021.

L. Moro-Velazquez, J. A. Gomez-Garcia, J. D. Arias-Londono, N. Dehak, and J. I. Godino-Llorente, “Advances in Parkinson's Disease detection and assessment using voice and speech: A review of the articulatory and phonatory aspects,” Biomedical Signal Processing and Control, 66, 102418, 2021.

P. Żelasko, D. Povey, J. Trmal, S. Khudanpur, "Lhotse: a speech data representation library for the modern deep learning ecosystem," Proc. NeurIPS 2021 Data-Centric AI Workshop.

L. Moro-Velazquez, J. A. Gomez-Garcia, N. Dehak, and J. I. Godino-Llorente," New tools for the differential evaluation of Parkinson?s disease using voice and speech processing, “ Proc. IberSPEECH 2021, Valladolid, Spain, March, 2021.

J. Cho , P. Zelasko, J. Villalba, and N. Dehak, "Improving Reconstruction Loss Based Speaker Embedding in Unsupervised and
Semi-Supervised Scenarios,” Proc. ICASSP, Toronto Canada, June, 2021.

S. Feng, P. Zelasko, L. Moro-Velazquez, A. Abavisani, M. Hasegawa-Johnson, O. Scharenborg, and N. Dehak, "How Phonotactics Affect Multilingual and Zero-Shot ASR Performance,” Proc. ICASSP, Toronto Canada, June, 2021.

N. Chen , P. Zelasko, J. Villalba, and N. Dehak, "Focus on the Present: A Regularization Method for the ASR Source-Target Attention Layer” Proc. ICASSP, Toronto Canada, June, 2021.

R. Pappagari, J. Villalba, P. Zelasko, L. Moro-Velazquez, and N. Dehak, "CopyPaste: An Augmentation Method for Speech Emotion Recognition,” Proc. ICASSP, Toronto Canada, June, 2021.

S. Kataria, J. Villalba, and N. Dehak, " Perceptual Loss Based Speech Denoising with an Ensemble of Audio Pattern Recognition and Self-Supervised Models,” Proc. ICASSP, Toronto Canada, June, 2021.

S. Kataria, J. Villalba, P. Zelasko, L. Moro-Velazquez, and N. Dehak, "Deep Feature CycleGANs: Speaker Identity Preserving Non-Parallel Microphone-Telephone Domain Adaptation for Speaker Verification,” Proc. INTERSPEECH, Brno, Czech, August 2021.

N. Chen , P. Zelasko, L. Moro-Velazquez, J. Villalba, and N. Dehak, "Align-Denoise: Single-Pass Non-Autoregressive Speech Recognition, “ Proc. INTERSPEECH, Brno, Czech, August 2021.

N. Chen, Y. Zhang, H. Zen, R. J. Weiss, M. Norouzi, N. Dehak, and W.Chan, "WaveGrad 2: Iterative Refinement for Text-to-Speech Synthesis,” Proc. INTERSPEECH, Brno, Czech, August 2021.

M. Rybicka, J. Villalba, P. Zelasko, N. Dehak, and K. Kowalczyk, "Spine2Net: SpineNet with Res2Net and Time-Squeeze-and-Excitation Blocks for Speaker Recognition” Proc. INTERSPEECH, Brno, Czech, August 2021.

S. Bhati, J. Villalba, P. Zelasko, L. Moro-Velazquez, and N. Dehak, Segmental Contrastive Predictive Coding for Unsupervised Word Segmentation,” Proc. INTERSPEECH, Brno, Czech, August 2021.

J. Villalba, S. Joshi,P. Zelasko, and N. Dehak,  "Representation Learning to Classify and Detect Adversarial Attacks Against Speaker and Speech Recognition Systems,” Proc. INTERSPEECH, Brno, Czech, August 2021.

L. Moro-Velazquez J. A. Gomez-Garcia, N. Dehak, and J. I. Godino-Llorente, "New Tools for the Differential Evaluation of Parkinson?s Disease Using Voice and Speech Processing” Proc. INTERSPEECH, Brno, Czech, August 2021.

R. Pappagari, J. Cho, S. Joshi, L. Moro-Velazquez, P. Zelasko, J. Villalba,and N. Dehak, "Automatic Detection and Assessment
of Alzheimer Disease Using Speech and Language Technologies in Low-Resource Scenarios,” Proc. INTERSPEECH, Brno, Czech, August 2021.

A. Wiacek; N. Dehak; M. A. Lediju Bell, "Extending CohereNet to Retain Physical Features when Classifying Benign or Malignant Breast Masses,” Proc. IEEE International Ultrasonics Symposium (IUS), September 2021.

R. Pappagari, P. Zelasko, J. Villalba, L. Moro-Velazquez, and N. Dehak, "Beyond Isolated Utterances: Conversational Emotion Recognition,” Proc. ASRU, December, 2021.

R. Pappagari, P. Zelasko, A. Mikolajczyk, P. Pezik,, and N. Dehak, "Joint Prediction of Truecasing and Punctuation for Conversational Speech in Low-Resource Scenarios,” Proc. ASRU, December, 2021.

Z. Tan, A. Sarkar, and N. Dehak, “rVAD: An Unsupervised Segment-Based Robust Voice Activity Detection Method,” Computer Speech & Language, Volume 59, Pages 1-21, January 2020.

L. Moro-Velazquez, E. Hernandez-Gonzalez, J. A. Gomez-Garcia, J. I. Godino-Llorente, and N. Dehak, “Analysis of the Effects of Supraglottal Tract Surgical Procedures in Automatic Speaker Recognition Performance.” IEEE/ACM Trans. Audio, Speech, and Language Proc. 2020.

B. T. Bosworth, I. A. Atakhodjaev, M. R. Kossey, B. C. Grubel, D. S. Vresilovic, J. R. Stroud, N. MacFarlane, J. Villalba, N. Dehak, “A. B. Cooper, M. A. Foster, A. C. Foster, Unclonable Photonic Keys Hardened Against Machine Learning Attacks.” APL Photonics 5, 010803 (2020).

N. Chen, S. Watanabe, J. Villalba, P. Zelasko, and N. Dehak, “Non-Autoregressive Transformer for Speech Recognition ,” IEEE Signal Processing Letters, 28, 2020.

L. Moro-Velazquez, and N. Dehak, “A Review of the Use of Prosodic Aspects of Speech for the Automatic Detection and Assessment of Parkinson's Disease.” Proceedings of the 1st Automatic Assessment of Parkinsonian Speech Workshop (AAPS), Communications in Computer and Information Science series, Springer 2020.

J. Villalba, N. Chen, D. Snyder, D. Garcia-Romero, A. McCree, G. Sell,
J. Borgstrom, L. P. García-Perera, F. Richardson, R. Dehak, P. A. Torres-Carrasquillo, and N. Dehak, “State-of-the-art Speaker Recognition with Neural Network Embeddings in NIST SRE18 and Speakers in the Wild Evaluations.” Computer Speech & Language, 60, 101026, 2020.

L. Moro-Velazquez, J. A. Gomez-Garcia, N. Dehak, and J. I. Godino-Llorente, “Analysis of phonatory features for the automatic detection of Parkinson?s Disease in two different corpora.” Proc. MAVEBA, Florence, Italy 2019.
P. S. Nidadavolu, S. Kataria, J. Villalba, P. Garcia-Perera, N. Dehak, "Unsupervised Feature Enhancement for Speaker Verification,” Proc. ICASSP, Barcelona, Spain, May 2020.

S. Kataria, P. S. Nidadavolu, J. Villalba, N. Chen, P. Garcia-Perera, and N. Dehak," Feature Enhancement with Deep Feature Losses for Speaker Verification,” Proc. ICASSP, Barcelona, Spain, May 2020.

R. Pappagari, T. Wang, J. Villalba, N. Chen, and N. Dehak, " X-VECTORS Meet Emotions: A Study on Dependencies between Emotion and Speaker Recognition,” Proc. ICASSP, Barcelona, Spain, May 2020.
L. Moro-Velazquez, J. Villalba, and N. Dehak, " Using X-VECTORS to Automatically Detect Parkinson's Disease from Speech,” Proc. ICASSP, Barcelona, Spain, May 2020.

L. Augustyniak, P. Szymanski, M. Morzy, P. Zelasko, A. Szymczak, J. Mizgajski, Y. Carmiel, and N. Dehak, "Punctuation Prediction in Spontaneous Conversations: Can We Mitigate ASR Errors with Retrofitted Word Embeddings?,” Proc. INTERSPEECH, Shanghai, China, October 2020.

J. Villalba, Y. Zhang, and N. Dehak, "X-VECTORS Meet Adversarial Attacks: Benchmarking Adversarial Robustness in Speaker Verification,” Proc. INTERSPEECH, Shanghai, China, October 2020.

P. Zelasko, L. Moro-Velazquez, M. Hasegawa-Johnson, O. Scharenborg, and N. Dehak, "That Sounds Familiar: an Analysis of Phonetic Representations Transfer Across Languages,” Proc. INTERSPEECH, Shanghai, China, October 2020.

R. Pappagari, J. Cho, L. Moro-Velazquez, and N. Dehak, " Using State of the Art Speaker Recognition and Natural Language Processing Technologies to Detect Alzheimer?s Disease and Assess its Severity,” Proc. INTERSPEECH, Shanghai, China, October 2020.

Y. Zhang, Z. Jiang, J. Villalba, and N. Dehak, "Black-box Attacks on Spoofing Countermeasures Using Transferability of Adversarial Examples,” Proc. INTERSPEECH, Shanghai, China, October 2020.

J. Cho, P. Zelasko, J. Villalba, S. Watanabe, and N. Dehak, "Learning Speaker Embedding from Text-to-Speech,” Proc. INTERSPEECH, Shanghai, China, October 2020.

S. Bhati, J. Villalba, P. Zelasko, and N. Dehak, "Self-Expressing Autoencoders for Unsupervised Spoken Term Discovery,” Proc. INTERSPEECH, Shanghai, China, October 2020.

L. P. Garcia Perera, J. Villalba, H. Bredin, J. Du, D. Castan, A. Cristia, L. Bullock, L. Guo, K. Okabe, P. S. Nidadavolu, S. Kataria, S. Chen, L. Galmant, M. Lavechin, L. Sun, M. Gill, B. Ben-Yair, S. Abdoli, X. Wang, W. Bouaziz, H. Titeux, E. Dupoux, K. A. Lee, and N. Dehak, " Speaker Detection in the Wild: Lessons Learned from JSALT 2019,” Proc. Odyssey speaker and language recognition workshop, Tokyo, Japan, November 2020.

J. Villalba, D. Garcia-Romero, N. Chen, G. Sell, J. Borgstrom, A. McCree, L. P. Garcia Perera, S. Kataria, P. S. Nidadavolu, P. Torres-Carrasquiilo, and N. Dehak," Advances in Speaker Recognition for Telephone and Audio-Visual Data: the JHU-MIT Submission for NIST SRE19,” Proc. Odyssey speaker and language recognition workshop, Tokyo, Japan, November 2020.

S. Kataria, P. S. Nidadavolu, J. Villalba, and N. Dehak," Analysis of Deep Feature Loss Based Enhancement for Speaker Verification,” Proc. Odyssey speaker and language recognition workshop, Tokyo, Japan, November 2020.

L. Moro-Velazquez, J. A. Gomez-Garcia, J.I. Godino-Llorente, J. Villalba, J. Rusz, S. Shattuck-Hufnagel, and N. Dehak, “A forced Gaussians Based Methodology for the Differential Evaluation of Parkinson's Disease by Means of Speech Processing,” Biomedical Signal Processing and Control, Volume 48, Pages 205-220, February 2019.

L. Moro-Velazquez, J. A. Gomez-Garcia, J. I. Godino-Llorente, F. Grandas-Perez, S. Shattuck-Hufnagel, V. Yague-Jimenez, and N. Dehak, “Phonetic Relevance and Phonemic Grouping of Speech in the Automatic Detection of Parkinson's Disease.” Nature Research - Scientific Reports 9, 19066. 2019

J. Cho, S. Watanabe, T. Hori, M. K. Baskar, H. Inaguma, J. Villalba, and N. Dehak, “Language Model Integration Based on Memory Control for Sequence to Sequence Speech Recognition,” Proc. ICASSP, pp. 6191--6195, Brighton, UK, May 2019.

C. Lai, A. Abad, K. Richmond, J. Yamagishi, N. Dehak, S. King, “Attentive Filtering Networks for Audio Replay Attack Detection,” Proc. ICASSP, pp. 6316--6320, Brighton, UK, May 2019.

P. S. Nidadavolu, V. Iglesias, J. Villalba, and N. Dehak, “Investigation on Neural Bandwidth of Telephone Speech for Improved Speaker Recognition,” Proc. ICASSP, pp. 6111--6115, Brighton, UK, May 2019.

P. S. Nidadavolu, J. Villalba, and N. Dehak, “Cycle-GANS for Domain Adaptation of Acoustic Features for Speaker Recognition,” Proc. ICASSP, pp. 6206--6210, Brighton, UK, May 2019.

L. M. Velazquez, J. Cho, S. Watanabe, M. Hasegawa-Johnson, O. Scharenborg, K. Heejin and N. Dehak “Study of the performance of automatic speech recognition systems in speakers with Parkinson's Disease,” Proc. INTERSPEECH, Graz, Austria, September 2019.

S. Bhati, S. Nayak, S. R. M. Kodukula and N. Dehak “ Unsupervised Acoustic Segmentation and Clustering using Siamese Network Embeddings,” Proc. INTERSPEECH, Graz, Austria, September 2019.

J. Villalba, Nanxin Chen, David Snyder, Daniel Garcia-Romero, Alan McCree, Gregory Sell, Jonas Borgstrom, Fred Richardson, Suwon Shon, Francois Grondin, Reda Dehak, Leibny Paola Garcia Perera, Dan Povey, Pedro Torres-Carrasquillo, Sanjeev Khudanpur and N. Dehak “ State-of-the-art Speaker Recognition for Telephone and Video Speech: the JHU-MIT Submission for NIST SRE18,” Proc. INTERSPEECH, Graz, Austria, September 2019.

S. Shon, N. Dehak, Douglas Reynolds and James Glass “MCE 2018: The 1st Multi-target Speaker Detection and Identification Challenge Evaluation,” Proc. INTERSPEECH, Graz, Austria, September 2019.

M. Wiesner, A. Renduchintala, S. atanabe, C. Liu, N. Dehak and S. Khudanpur “Pretraining by Backtranslation for End-to-end ASR in Low-Resource Settings,” Proc. INTERSPEECH, Graz, Austria, September 2019.

C. Lai, N. Chen, J. Villalba, and N. Dehak “ASSERT: Anti-Spoofing with Squeeze-Excitation and Residual neTworks,” Proc. INTERSPEECH, Graz, Austria, September 2019.

D. Snyder, J. Villalba,, N. Chen, D. Povey, G. Sell, N. Dehak and Sanjeev Khudanpur “The JHU Speaker Recognition System for the VOiCES 2019 Challenge,” Proc. INTERSPEECH, Graz, Austria, September 2019.

M. Sarma, P. Ghahremani, D. Povey, N. G\. Kandarpa K. Sarma and N. Dehak “Improving Emotion Identification using Phone Posteriors in Raw Speech Waveform based DNN,” Proc. INTERSPEECH, Graz, Austria, September 2019.

N. Chen, J. Villalba, and N. Dehak “Tied Mixture of Factor Analyzers Layer to Combine Frame Level Representations in Neural Speaker Embeddings,” Proc. INTERSPEECH, Graz, Austria, September 2019.

A. Wiacek, N. Dehak, and M. A. Lediju Bell “CohereNet: A deep learning approach to coherence-based beamforming,” 2019 IEEE International Ultrasonics Symposium (IUS), SEC, Glasgow, Scotland, UK, October 2019.

S. Bhati, C. Liu, J. Villalba, J. Trmal, S. Khudanpur, and N. Dehak “Bottom-Up Unsupervised Word Discovery via Acoustic Units” The 2019 IEEE Global Conference on Signal and Information Processing (GlobalSIP), Ottawa, Canada, November 2019.

S. Bhati, L. M. Velazquez, J. Villalba, and N. Dehak “LSTM Siamese Network for Parkinson's Disease Detection from Speech” The 2019 IEEE Global Conference on Signal and Information Processing (GlobalSIP), Ottawa, Canada, November 2019.

P. S. Nidadavolu, K. Saurabh, J. Villalba, and N. Dehak. “Low-resource domain adaptation for speaker recognition using cycle-GANs,” IEEE ASRU, Singapore, December 2019.

P. Raghavendra, P. Zelasko, J. Villalba, Y. Carmiel, and N. Dehak. “Hierarchical Transformers for Long Document Classification," IEEE ASRU, Singapore, December 2019.

L. Moro-Velazquez, J. A. Gomez-Garci¬a, J.I. Godino-Llorente, J. Villalba, J.R. Orozco-Arroyave, and N. Dehak, “Analysis of Speaker Recognition Methodologies and the Influence of Kinetic Changes to Automatically Detect Parkinson's Disease,” Applied Soft Computing, 62, Pages 649-666. 2018.

J. R. Orozco-Arroyave, J.C. Vesquez-Correa, J. F. Vargas-Bonilla, R. Arora, N. Dehak, P.S. Nidadavolu, H. Christensen, F. Rudzicz, M. Yancheva, H. Chinaei, A. Vann, N. Vogler, T. Bocklet, M. Cernak, J. Hannink, and E. Nöth, “NeuroSpeech: An Open-Source Software for Parkinson's Speech Analysis,” Digital Signal Processing, Volume 77, Pages 207-221, June 2018.

R. Zazo, P.S. Nidadavolu, N. Chen, J. Gonzalez-Rodriguez, and N. Dehak, “Age Estimation in Short Speech Utterances Based on LSTM Recurrent Neural Networks,” IEEE Access 2018, Pages 22524-22530, March 2018.

M. Maciejewski, D. Snyder, V. Manohar, N. Dehak, and S. Khudanpur, “Characterizing Performance Of Speaker Diarization Systems on Far-Field Speech Using Standard Methods,” Proc. ICASSP, pp. 5244--5248, Calgary, Canada, April 2018.

N. Chen, J. Villalba, Y. Carmiel, and N. Dehak, “Measuring Uncertainty in Deep Regression Models: The case of Age Estimation from Speech,” Proc. ICASSP, pp. 4939--4943, Calgary, Canada, April 2018.

R. Pappagari, J. Villalba, N. Dehak, “Joint Verification-Identifcation in End-to-End Multi-Scale CNN Framework for Topic Identification,” Proc. ICASSP, pp. 6199--6203, Calgary, Canada, April 2018.

I. Atakhodjaev, B.T. Bosworth, B.C. Grubel, M.R. Kossey, J. Villalba, A.B. Cooper, N. Dehak, A.C. Foster, and M.A. Foster, “Investigation of Deep Learning Attacks on Nonlinear Silicon Photonic PUFs,” Conference on Lasers and Electro-Optics (CLEO):QELS Fundamental Science, Optical Society of America, 2018.

F. Richardson, P. Torres-Carrasquillo, J. Borgstrom, D. Sturim, Y. Gwon, J. Villalba, J. Trmal, N. Chen, R. Dehak and N. Dehak, “The MIT Lincoln Laboratory/JHU/EPITA-LSE LRE17 System,” Proc. Odyssey speaker and language recognition workshop, pp. 54--59, Les Sables d\textquoteright Olonne, France, June 2018.

J. Villalba, N. Brummer, and N. Dehak, “End-to-End versus Embedding Neural Networks for Language Recognition in Mismatched Conditions,” Proc. Odyssey speaker and language recognition workshop, pp. 112--119, Les Sables d\textquoteright Olonne, France, June 2018.

L. Moro-Velazquez, J. A. Gomez-Garcia, J. I. Godino-Llorente, J. Rusz, S. Skodda, F. Grandas-Perez, J. M. Velazquez, E. Noth, J. R. Orozco-Arroyave, and N. Dehak, “Study of the Automatic Detection of Parkison's Disease Based on Speaker Recognition Technologies and Allophonic Distillation,” Proc. 40th Annual International Conference of the IEEE Engineering in Medicine and Biology Society, pp. 1404--1407. Honolulu, Oahu, July 2018.

P. Zelasko, P. Szyma„ski, J. Mizgajski, A. Szymczak, Y. Carmiel, and N. Dehak, “Punctuation Prediction Model for Conversational Speech,” Proc. Interspeech, pp. 2633--2637, Hyderabad, India, September 2018.

M. Sarma, P. Ghahremani, D. Povey, N. K. Goel, K. K. Sarma, and N. Dehak, “Emotion Identification from Raw Speech Signals Using DNNs,” Proc. Interspeech, pp. 3097--3101, Hyderabad, India, September 2018.

O. Scharenborg, S. Tiesmeyer, M. Hasegawa-Johnson, and N. Dehak, “Visualizing Phoneme Category Adaptation in Deep Neural Networks,” Proc. Interspeech, pp. 1482--1486, Hyderabad, India, September 2018.

M. Wiesner, C. Liu, L. Ondel, C. Harman, V. Manohar, J. Trmal, Z. Huang, S. Khudanpur, and N. Dehak, “Automatic Speech Recognition and Topic Identification from Speech for Almost-Zero-Resource Languages,” Proc. Interspeech, pp. 2052--2056, Hyderabad, India, September 2018.

G. Sell, D. Snyder, A. McCree, D. Garcia-Romero, J. Villalba, M. Maciejewski, V. Manohar, N. Dehak, D. Povey, S. Watanabe, and S. Khudanpur, “Diarization is Hard: Some Experiences and Lessons Learned for the JHU Team in the Inaugural DIHARD Challenge,” Proc. Interspeech, pp. 2808--2812, Hyderabad, India, September 2018.

P. Ghahremani, P. S. Nidadavolu, N. Chen, J. Villalba, D. Povey, S. Khudanpur, and N. Dehak, “End-to-End Deep Neural Network Age Estimation,” Proc. Interspeech, pp. 277--281, Hyderabad, India, September 2018.

P. S. Nidadavolu, C. Lai, J. Villalba, and N. Dehak, “Investigation on Bandwidth Extension for Speaker recognition,” Proc. Interspeech, pp. 1111--1115, Hyderabad, India, September 2018.

P. Frederiksen, J. Villalba, S. Watanabe, Z. Tan, and N. Dehak, “Effectiveness of Single-Channel BLSTM Enhancement for Language Identification,” Proc. Interspeech, pp. 1823--1827, Hyderabad, India, September 2018.

J. Cho, R. Pappagari, P. Kulkarni, J. Villalba, Y. Carmiel, and N. Dehak, “Deep Neural Networks for Emotion Recognition Combining Audio and Transcripts,” Proc. Interspeech, pp. 247--251, Hyderabad, India, September 2018.

N. Chen, J. Villalba, and N. Dehak, “An Investigation of Non-linear i-vectors for Speaker Verification,” Proc. Interspeech, pp. 87--91, Hyderabad, India, September 2018.

Z. Huang, P. Garcia-Perera, J. Villalba, D. Povey, and N. Dehak, “JHU Diarization System Description,” Proc. IberSPEECH, pp. 1--4, Barcelona, Spain, November 2018.

C. Liu, M. Wiesner, S. Watanabe, C. Harman, J. Trmal, N. Dehak, and S. Khudanpur, “Low-Resource Contextual Topic Identification on Speech,” IEEE SLT 2018 Workshop, Athens, Greece, December 2018.

J. Villalba, N. Brummer, and N. Dehak, “Tied Variational Autoencoder Backends for i-Vector Speaker Recognition,” Proc. Interspeech, pp. 1004--1008, Stockholm, Sweden, August 2017.

J. Vasquez-Correa, J. Orozco-Arroyave, R. Arora, E. Noth, N. Dehak, H. Christensen, F. Rudzicz, T. Bocklet, M. Cernak, H. Chinaei, J. Hannink, P. Nidadavolu, M. Yancheva, A. Vann, and N. Vogler, “Multi-view Representation Learning Via GCCA for Multimodal Analysis of Parkinson's Disease,” Proc. ICASSP, pp. 2966--2970, New Orleans, USA, March 2017.

N. Garcia, J.C. Vasquez-Correa, J.R. Orozco-Arroyave, N. Dehak, and E. Noth, “Language Independent Assessment of Motor Impairments of Patients with Parkinson’s Disease Using i-Vectors,” Proc. International Conference on Text, Speech, and Dialogue, pp. 147--155, Prague, Czech Republic, August 2017.

N. Garcia, J. R. Orozco-Arroyave, L.F. D’Haro, N. Dehak, and E. Noth, “Evaluation of the Neurological State of People with Parkinson’s Disease Using I-vectors,” Proc. Interspeech, pp. 299--303, Stockholm, Sweden, August 2017.

P.A. Torres-Carrasquillo, F. Richardson, S. Nercessian, D. Sturim, W. Campbell, Y. Gwon, S. Vattam, N. Dehak, H. Mallidi, P. S. Nidadavolu, R. Li, and R. Dehak, “The MIT-LL, JHU and LRDE NIST 2016 Speaker Recognition Evaluation System,” Proc. Interspeech, pp. 1333--1337, Stockholm, Sweden, August 2017.

L. Moro-Velazquez, J.I. Godino-Llorente, J.A. Gomez-Garcia, J. Villalba, S. Shattuck-Hufnage, and N. Dehak, “Use of Acoustic Landmarks and GMM-UBM Blend in the Automatic Detection of Parkinson's Disease,” 10th International Workshop on Models and Analysis of Vocal Emissions for Biomedical Applications, pp. 73--76 , Firenze, Italy, December 2017.