| Front-end factor analysis for speaker verification N Dehak, PJ Kenny, R Dehak, P Dumouchel, P Ouellet IEEE Transactions on Audio, Speech, and Language Processing 19 (4), 788-798, 2010 | 5182 | 2010 |
| A study of interspeaker variability in speaker verification P Kenny, P Ouellet, N Dehak, V Gupta, P Dumouchel IEEE Transactions on Audio, Speech, and Language Processing 16 (5), 980-988, 2008 | 900 | 2008 |
| Language recognition via i-Vectors and dimensionality reduction. N Dehak, PA Torres-Carrasquillo, DA Reynolds, R Dehak Interspeech, 857-860, 2011 | 625 | 2011 |
| Deep neural network approaches to speaker and language recognition F Richardson, D Reynolds, N Dehak IEEE signal processing letters 22 (10), 1671-1675, 2015 | 567 | 2015 |
| Support vector machines versus fast scoring in the low-dimensional total variability space for speaker verification. N Dehak, R Dehak, P Kenny, N Brümmer, P Ouellet, P Dumouchel Interspeech 9, 1559-1562, 2009 | 506 | 2009 |
| Hierarchical transformers for long document classification R Pappagari, P Zelasko, J Villalba, Y Carmiel, N Dehak 2019 IEEE automatic speech recognition and understanding workshop (ASRU …, 2019 | 353 | 2019 |
| Cosine similarity scoring without score normalization techniques. N Dehak, R Dehak, JR Glass, DA Reynolds, P Kenny Odyssey 15, 2010 | 291 | 2010 |
| Diarization is Hard: Some Experiences and Lessons Learned for the JHU Team in the Inaugural DIHARD Challenge. G Sell, D Snyder, A McCree, D Garcia-Romero, J Villalba, M Maciejewski, ... Interspeech, 2808-2812, 2018 | 264 | 2018 |
| Unsupervised methods for speaker diarization: An integrated and iterative approach SH Shum, N Dehak, R Dehak, JR Glass IEEE Transactions on Audio, Speech, and Language Processing 21 (10), 2015-2028, 2013 | 224 | 2013 |
| Modeling prosodic features with joint factor analysis for speaker verification N Dehak, P Dumouchel, P Kenny IEEE Transactions on Audio, Speech, and Language Processing 15 (7), 2095-2103, 2007 | 218 | 2007 |
| ASSERT: Anti-spoofing with squeeze-excitation and residual networks CI Lai, N Chen, J Villalba, N Dehak arXiv preprint arXiv:1904.01120, 2019 | 212 | 2019 |
| A unified deep neural network for speaker and language recognition F Richardson, D Reynolds, N Dehak arXiv preprint arXiv:1504.00923, 2015 | 208 | 2015 |
| Emotion Identification from Raw Speech Signals Using DNNs. M Sarma, P Ghahremani, D Povey, NK Goel, KK Sarma, N Dehak Interspeech, 3097-3101, 2018 | 176 | 2018 |
| Comparison of scoring methods used in speaker recognition with joint factor analysis O Glembek, L Burget, N Dehak, N Brummer, P Kenny 2009 IEEE International Conference on Acoustics, Speech and Signal …, 2009 | 175 | 2009 |
| Advances in Parkinson's disease detection and assessment using voice and speech: A review of the articulatory and phonatory aspects L Moro-Velazquez, JA Gomez-Garcia, JD Arias-Londoño, N Dehak, ... Biomedical Signal Processing and Control 66, 102418, 2021 | 166 | 2021 |
| rVAD: An unsupervised segment-based robust voice activity detection method ZH Tan, N Dehak Computer speech & language 59, 1-21, 2020 | 165 | 2020 |
| Automatic Dialect Detection in Arabic Broadcast Speech A Ali, N Dehak, P Cardinal, S Khurana, SH Yella, J Glass, P Bell, ... Interspeech, San Francisco, USA,, 2934-2938, 2016 | 165 | 2016 |
| NeuroSpeech: An open-source software for Parkinson's speech analysis JR Orozco-Arroyave, JC Vásquez-Correa, JF Vargas-Bonilla, R Arora, ... Digital Signal Processing 77, 207-221, 2018 | 156 | 2018 |
| x-vectors meet emotions: A study on dependencies between emotion and speaker recognition R Pappagari, T Wang, J Villalba, N Chen, N Dehak ICASSP 2020-2020 IEEE International Conference on Acoustics, Speech and …, 2020 | 153 | 2020 |
| State-of-the-art speaker recognition with neural network embeddings in NIST SRE18 and speakers in the wild evaluations J Villalba, N Chen, D Snyder, D Garcia-Romero, A McCree, G Sell, ... Computer Speech & Language 60, 101026, 2020 | 153 | 2020 |
Jesús VillalbaJohns Hopkins UniversityBestätigte E-Mail-Adresse bei jhu.edu
