| A practical, self-adaptive voice activity detector for speaker verification with noisy telephone and microphone data T Kinnunen, P Rajan 2013 IEEE international conference on acoustics, speech and signal …, 2013 | 159 | 2013 |
| I4U submission to NIST SRE 2012: A large-scale collaborative effort for noise-robust speaker verification R Saeidi, KA Lee, T Kinnunen, T Hasan, B Fauve, PM Bousquet, E Khoury, ... Annual Conference of the International Speech Communication Association …, 2013 | 91 | 2013 |
| From single to multiple enrollment i-vectors: Practical PLDA scoring variants for speaker verification P Rajan, A Afanasyev, V Hautamäki, T Kinnunen Digital Signal Processing 31, 93-101, 2014 | 69 | 2014 |
| Robustness of phase based features for speaker recognition P Rajan, SHK Parthasarathi, HA Murthy Idiap, 2009 | 51 | 2009 |
| Using group delay functions from all-pole models for speaker recognition P Rajan, TH Kinnunen, J Pohjalainen, P Alku, F Bimbot, C Cerisara, ... Isc-Int Speech Communication Association, 2013 | 49 | 2013 |
| Deep metric learning for bioacoustic classification: Overcoming training data scarcity using dynamic triplet loss A Thakur, D Thapar, P Rajan, A Nigam The Journal of the Acoustical Society of America 146 (1), 534-547, 2019 | 46 | 2019 |
| Effect of multicondition training on i-vector PLDA configurations for speaker recognition. P Rajan, T Kinnunen, V Hautamäki Interspeech, 3694-3697, 2013 | 43 | 2013 |
| Minimax i-vector extractor for short duration speaker verification. V Hautamäki, YC Cheng, P Rajan, CH Lee INTERSPEECH 2013, 3708-3712, 2013 | 39 | 2013 |
| Bird call identification using dynamic kernel based support vector machines and deep neural networks D Chakraborty, P Mukker, P Rajan, AD Dileep 2016 15th IEEE international conference on machine learning and applications …, 2016 | 32 | 2016 |
| Modified group delay feature for musical instrument recognition A Diment, P Rajan, T Heittola, T Virtanen Proc. Int. Symp. Computer Music Multidisciplinary Research, 431-438, 2013 | 29 | 2013 |
| Robustness of group delay representations for noisy speech signals SHK Parthasarathi, R Padmanabhan, HA Murthy International Journal of Speech Technology 14, 361-368, 2011 | 19 | 2011 |
| Compressed convex spectral embedding for bird species classification A Thakur, V Abrol, P Sharma, P Rajan 2018 IEEE International Conference on Acoustics, Speech and Signal …, 2018 | 18 | 2018 |
| Multi-layer perceptron based speech activity detection for speaker verification S Ganapathy, P Rajan, H Hermansky 2011 IEEE Workshop on Applications of Signal Processing to Audio and …, 2011 | 18 | 2011 |
| SVD-based redundancy removal in 1-D CNNs for acoustic scene classification A Singh, P Rajan, A Bhavsar Pattern Recognition Letters 131, 383-389, 2020 | 17 | 2020 |
| Merging human and automatic system decisions to improve speaker recognition performance. RG Hautamäki, V Hautamäki, P Rajan, T Kinnunen Interspeech, 2519-2523, 2013 | 16 | 2013 |
| A layer-wise score level ensemble framework for acoustic scene classification A Singh, A Thakur, P Rajan, A Bhavsar 2018 26th European Signal Processing Conference (EUSIPCO), 837-841, 2018 | 15 | 2018 |
| Deep hidden analysis: A statistical framework to prune feature maps A Singh, P Rajan, A Bhavsar ICASSP 2019-2019 IEEE International Conference on Acoustics, Speech and …, 2019 | 13 | 2019 |
| Deep archetypal analysis based intermediate matching kernel for bioacoustic classification A Thakur, P Rajan IEEE Journal of Selected Topics in Signal Processing 13 (2), 298-309, 2019 | 13 | 2019 |
| Deep Convex Representations: Feature Representations for Bioacoustics Classification. A Thakur, V Abrol, P Sharma, P Rajan Interspeech, 2127-2131, 2018 | 13 | 2018 |
| Acoustic scene classification using deep learning R Patiyal, P Rajan IEEE AASP Challenge on Detection and Classification of Acoustic Scenes and …, 2016 | 13 | 2016 |
Anshul ThakurUniversity of Oxford在 eng.ox.ac.uk 的电子邮件经过验证
