Raghavendra Reddy Pappagari
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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
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
Can you tell me how to get past sesame street? sentence-level pretraining beyond language modeling
A Wang, J Hula, P Xia, R Pappagari, RT McCoy, R Patel, N Kim, I Tenney, ...
arXiv preprint arXiv:1812.10860, 2018
Deep Neural Networks for Emotion Recognition Combining Audio and Transcripts.
J Cho, R Pappagari, P Kulkarni, J Villalba, Y Carmiel, N Dehak
Interspeech, 247-251, 2018
Using State of the Art Speaker Recognition and Natural Language Processing Technologies to Detect Alzheimer's Disease and Assess its Severity.
R Pappagari, J Cho, L Moro-Velazquez, N Dehak
Interspeech, 2177-2181, 2020
Significance of analytic phase of speech signals in speaker verification
K Vijayan, PR Reddy, KSR Murty
Speech Communication 81, 54-71, 2016
jiant 1.2: A software toolkit for research on general-purpose text understanding models
A Wang, IF Tenney, Y Pruksachatkun, K Yu, J Hula, P Xia, R Pappagari, ...
Note: http://jiant. info/Cited by: footnote 4, 2019
Copypaste: An augmentation method for speech emotion recognition
R Pappagari, J Villalba, P Żelasko, L Moro-Velazquez, N Dehak
ICASSP 2021-2021 IEEE International Conference on Acoustics, Speech and …, 2021
Automatic Detection and Assessment of Alzheimer Disease Using Speech and Language Technologies in Low-Resource Scenarios.
R Pappagari, J Cho, S Joshi, L Moro-Velázquez, P Zelasko, J Villalba, ...
Interspeech 2021, 3825-3829, 2021
Query word retrieval from continuous speech using GMM posteriorgrams
PR Reddy, K Rout, KSR Murty
2014 International Conference on Signal Processing and Communications (SPCOM …, 2014
Looking for ELMo's friends: Sentence-level pretraining beyond language modeling
SR Bowman, E Pavlick, E Grave, B Van Durme, A Wang, J Hula, P Xia, ...
MT-GenEval: A counterfactual and contextual dataset for evaluating gender accuracy in machine translation
A Currey, M Nădejde, R Pappagari, M Mayer, S Lauly, X Niu, B Hsu, ...
arXiv preprint arXiv:2211.01355, 2022
Joint verification-identification in end-to-end multi-scale CNN framework for topic identification
R Pappagari, J Villalba, N Dehak
2018 IEEE International Conference on Acoustics, Speech and Signal …, 2018
Topic identification of spoken documents using unsupervised acoustic unit discovery
S Kesiraju, R Pappagari, L Ondel, L Burget, N Dehak, S Khudanpur, ...
2017 IEEE International Conference on Acoustics, Speech and Signal …, 2017
Joint prediction of truecasing and punctuation for conversational speech in low-resource scenarios
R Pappagari, P Żelasko, A Mikołajczyk, P Pęzik, N Dehak
2021 IEEE Automatic Speech Recognition and Understanding Workshop (ASRU …, 2021
What helps transformers recognize conversational structure? Importance of context, punctuation, and labels in dialog act recognition
P Żelasko, R Pappagari, N Dehak
Transactions of the Association for Computational Linguistics 9, 1163-1179, 2021
Non-contrastive self-supervised learning of utterance-level speech representations
J Cho, R Pappagari, P Żelasko, L Moro-Velazquez, J Villalba, N Dehak
arXiv preprint arXiv:2208.05413, 2022
Unsupervised spoken word retrieval using Gaussian-Bernoulli restricted Boltzmann machines
RR Pappagari, S Nayak, KSR Murty
Fifteenth Annual Conference of the International Speech Communication …, 2014
Beyond isolated utterances: Conversational emotion recognition
R Pappagari, P Żelasko, J Villalba, L Moro-Velazquez, N Dehak
2021 IEEE Automatic Speech Recognition and Understanding Workshop (ASRU), 39-46, 2021
Experimental studies on effect of speaking mode on spoken term detection
K Rout, PR Reddy, KSR Murty
2015 Twenty First National Conference on Communications (NCC), 1-6, 2015
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