| The multi-channel wall street journal audio visual corpus (MC-WSJ-AV): Specification and initial experiments M Lincoln, I McCowan, J Vepa, HK Maganti IEEE Workshop on Automatic Speech Recognition and Understanding, 2005., 357-362, 2005 | 217 | 2005 |
| Speech Emotion Recognition Using Spectrogram & Phoneme Embedding. P Yenigalla, A Kumar, S Tripathi, C Singh, S Kar, J Vepa Interspeech 2018, 3688-3692, 2018 | 202 | 2018 |
| The AMI system for the transcription of speech in meetings T Hain, L Burget, J Dines, G Garau, V Wan, M Karafiat, J Vepa, M Lincoln 2007 IEEE International Conference on Acoustics, Speech and Signal …, 2007 | 150 | 2007 |
| New objective distance measures for spectral discontinuities in concatenative speech synthesis J Vepa, S King, P Taylor IEEE, 2002 | 111 | 2002 |
| The segmentation of multi-channel meeting recordings for automatic speech recognition J Dines, J Vepa, T Hain IDIAP, 2006 | 100 | 2006 |
| Juicer: A weighted finite-state transducer speech decoder D Moore, J Dines, MM Doss, J Vepa, O Cheng, T Hain Machine Learning for Multimodal Interaction: Third International Workshop …, 2006 | 82 | 2006 |
| Gated mechanism for attention based multi modal sentiment analysis A Kumar, J Vepa ICASSP 2020-2020 IEEE International Conference on Acoustics, Speech and …, 2020 | 80 | 2020 |
| Using posterior-based features in template matching for speech recognition G Aradilla, J Vepa, H Bourlard IDIAP, 2006 | 79 | 2006 |
| Classification of heart murmurs using cepstral features and support vector machines J Vepa 2009 Annual International Conference of the IEEE Engineering in Medicine and …, 2009 | 70 | 2009 |
| The AMI meeting transcription system: Progress and performance T Hain, L Burget, J Dines, G Garau, M Karafiat, M Lincoln, J Vepa, V Wan Machine Learning for Multimodal Interaction: Third International Workshop …, 2006 | 61 | 2006 |
| Join cost for unit selection speech synthesis J Vepa The University of Edinburgh. College of Science and Engineering. School of …, 2004 | 60 | 2004 |
| An acoustic model based on Kullback-Leibler divergence for posterior features G Aradilla, J Vepa, H Bourlard 2007 IEEE International Conference on Acoustics, Speech and Signal …, 2007 | 48 | 2007 |
| Segmentation of heart sounds using simplicity features and timing information J Vepa, P Tolay, A Jain 2008 ieee international conference on acoustics, speech and signal …, 2008 | 45 | 2008 |
| Posterior based keyword spotting with a priori thresholds H Ketabdar, J Vepa, S Bengio, H Bourlard Interspeech 2006, 1939-Wed1CaP. 11, 2006 | 45 | 2006 |
| Lung sound analysis for wheeze episode detection A Jain, J Vepa 2008 30th Annual International Conference of the IEEE Engineering in …, 2008 | 44 | 2008 |
| Objective distance measures for spectral discontinuities in concatenative speech synthesis J Vepa, P Taylor | 43 | 2002 |
| Improving speech recognition using a data-driven approach G Aradilla, J Vepa, H Bourlard Proceedings of Interspeech 2005, 3333-3336, 2005 | 40 | 2005 |
| Hierarchical neural networks feature extraction for LVCSR system F Valente, J Vepa, C Plahl, C Gollan, H Hermansky, R Schlüter Interspeech 2007, 42-45, 2007 | 31 | 2007 |
| Phoneme-bert: Joint language modelling of phoneme sequence and asr transcript MN Sundararaman, A Kumar, J Vepa arXiv preprint arXiv:2102.00804, 2021 | 28 | 2021 |
| Subjective evaluation of join cost and smoothing methods for unit selection speech synthesis J Vepa, S King IEEE Transactions on audio, speech, and language processing 14 (5), 1763-1771, 2006 | 28 | 2006 |
