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ORCIDRahul Gupta 0001
Person information
- affiliation: Amazon.com
- affiliation: University of Southern California, Signal Analysis and Interpretation Lab, SAIL, Department of Electrical Engineering, Los Angeles, CA, USA
- affiliation (former): Indian Institute of Technology, Department of electrical engineering, Kharagpur, India
Other persons with the same name
- Rahul Gupta — disambiguation page
- Rahul Gupta 0002
![[0000-0002-9370-1820]](https://dblp.org/img/orcid-mark.12x12.png "0000-0002-9370-1820")
— University of Cyprus, Nicosia, Cyprus (and 3 more)
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2020 – today
- 2024
[i41]Tiantian Feng, Anil Ramakrishna, Jimit Majmudar, Charith Peris, Jixuan Wang, Clement Chung, Richard S. Zemel, Morteza Ziyadi, Rahul Gupta:
Partial Federated Learning. CoRR abs/2403.01615 (2024)- 2023
- [c70]Caleb Ziems, William Held, Jingfeng Yang, Jwala Dhamala, Rahul Gupta, Diyi Yang:
Multi-VALUE: A Framework for Cross-Dialectal English NLP. ACL (1) 2023: 744-768 - [c69]Mustafa Özdayi, Charith Peris, Jack FitzGerald, Christophe Dupuy, Jimit Majmudar, Haidar Khan, Rahil Parikh, Rahul Gupta:
Controlling the Extraction of Memorized Data from Large Language Models via Prompt-Tuning. ACL (2) 2023: 1512-1521 - [c68]Ninareh Mehrabi, Palash Goyal, Apurv Verma, Jwala Dhamala, Varun Kumar, Qian Hu, Kai-Wei Chang, Richard S. Zemel, Aram Galstyan, Rahul Gupta:
Resolving Ambiguities in Text-to-Image Generative Models. ACL (1) 2023: 14367-14388 - [c67]Jack Good, Jimit Majmudar, Christophe Dupuy, Jixuan Wang, Charith Peris, Clement Chung, Richard S. Zemel, Rahul Gupta:
Coordinated Replay Sample Selection for Continual Federated Learning. EMNLP (Industry Track) 2023: 331-342 - [c66]Jiao Sun, Yufei Tian, Wangchunshu Zhou, Nan Xu, Qian Hu, Rahul Gupta, John Frederick Wieting, Nanyun Peng, Xuezhe Ma:
Evaluating Large Language Models on Controlled Generation Tasks. EMNLP 2023: 3155-3168 - [c65]Anil Ramakrishna, Rahul Gupta, Jens Lehmann, Morteza Ziyadi:
INVITE: a Testbed of Automatically Generated Invalid Questions to Evaluate Large Language Models for Hallucinations. EMNLP (Findings) 2023: 5422-5429 - [c64]Qian Hu, Palash Goyal, Rahul Gupta:
Faithful Model Evaluation for Model-Based Metrics. EMNLP 2023: 7484-7489 - [c63]Anaelia Ovalle, Palash Goyal, Jwala Dhamala, Zachary Jaggers, Kai-Wei Chang, Aram Galstyan, Richard S. Zemel, Rahul Gupta:
"I'm fully who I am": Towards Centering Transgender and Non-Binary Voices to Measure Biases in Open Language Generation. FAccT 2023: 1246-1266 - [c62]Christophe Dupuy, Jimit Majmudar, Jixuan Wang, Tanya G. Roosta, Rahul Gupta, Clement Chung, Jie Ding, Salman Avestimehr:
Quantifying Catastrophic Forgetting in Continual Federated Learning. ICASSP 2023: 1-5 - [c61]Ansel MacLaughlin, Anna Rumshisky, Rinat Khaziev, Anil Ramakrishna, Yuval Merhav, Rahul Gupta:
Self-Healing Through Error Detection, Attribution, and Retraining. ICASSP 2023: 1-5 - [c60]Tiantian Feng, Digbalay Bose, Tuo Zhang, Rajat Hebbar, Anil Ramakrishna, Rahul Gupta, Mi Zhang, Salman Avestimehr, Shrikanth Narayanan:
FedMultimodal: A Benchmark for Multimodal Federated Learning. KDD 2023: 4035-4045 - [c59]Rahul Gupta, Lisa Bauer, Kai-Wei Chang, Jwala Dhamala, Aram Galstyan, Palash Goyal, Qian Hu, Avni Khatri, Rohit Parimi, Charith Peris, Apurv Verma, Richard S. Zemel, Prem Natarajan:
Incorporating Fairness in Large Scale NLU Systems. WSDM 2023: 1289-1290 - [c58]Charith Peris, Christophe Dupuy, Jimit Majmudar, Rahil Parikh, Sami Smaili, Richard S. Zemel, Rahul Gupta:
Privacy in the Time of Language Models. WSDM 2023: 1291-1292 - [i40]Anaelia Ovalle, Palash Goyal, Jwala Dhamala, Zachary Jaggers, Kai-Wei Chang, Aram Galstyan, Richard S. Zemel, Rahul Gupta:
"I'm fully who I am": Towards Centering Transgender and Non-Binary Voices to Measure Biases in Open Language Generation. CoRR abs/2305.09941 (2023) - [i39]Mustafa Safa Özdayi, Charith Peris, Jack FitzGerald, Christophe Dupuy, Jimit Majmudar, Haidar Khan, Rahil Parikh, Rahul Gupta:
Controlling the Extraction of Memorized Data from Large Language Models via Prompt-Tuning. CoRR abs/2305.11759 (2023) - [i38]Tiantian Feng, Digbalay Bose, Tuo Zhang, Rajat Hebbar, Anil Ramakrishna, Rahul Gupta, Mi Zhang, Salman Avestimehr, Shrikanth Narayanan:
FedMultimodal: A Benchmark For Multimodal Federated Learning. CoRR abs/2306.09486 (2023) - [i37]Ninareh Mehrabi, Palash Goyal, Christophe Dupuy, Qian Hu, Shalini Ghosh, Richard S. Zemel, Kai-Wei Chang, Aram Galstyan, Rahul Gupta:
FLIRT: Feedback Loop In-context Red Teaming. CoRR abs/2308.04265 (2023) - [i36]Jiao Sun, Yufei Tian, Wangchunshu Zhou, Nan Xu, Qian Hu, Rahul Gupta, John Frederick Wieting, Nanyun Peng, Xuezhe Ma:
Evaluating Large Language Models on Controlled Generation Tasks. CoRR abs/2310.14542 (2023) - [i35]Jack Good, Jimit Majmudar, Christophe Dupuy, Jixuan Wang, Charith Peris, Clement Chung, Richard S. Zemel, Rahul Gupta:
Coordinated Replay Sample Selection for Continual Federated Learning. CoRR abs/2310.15054 (2023) - [i34]Junyi Li, Ninareh Mehrabi, Charith Peris, Palash Goyal, Kai-Wei Chang, Aram Galstyan, Richard S. Zemel, Rahul Gupta:
On the steerability of large language models toward data-driven personas. CoRR abs/2311.04978 (2023) - [i33]Ninareh Mehrabi, Palash Goyal, Anil Ramakrishna, Jwala Dhamala, Shalini Ghosh, Richard S. Zemel, Kai-Wei Chang, Aram Galstyan, Rahul Gupta:
JAB: Joint Adversarial Prompting and Belief Augmentation. CoRR abs/2311.09473 (2023) - [i32]Anaelia Ovalle, Ninareh Mehrabi, Palash Goyal, Jwala Dhamala, Kai-Wei Chang, Richard S. Zemel, Aram Galstyan, Rahul Gupta:
Are you talking to ['xem'] or ['x', 'em']? On Tokenization and Addressing Misgendering in LLMs with Pronoun Tokenization Parity. CoRR abs/2312.11779 (2023) - [i31]Palash Goyal, Qian Hu, Rahul Gupta:
Faithful Model Evaluation for Model-Based Metrics. CoRR abs/2312.17254 (2023) - 2022
- [j5]Anil Ramakrishna, Rahul Gupta, Shrikanth Narayanan:
Joint Multi-Dimensional Model for Global and Time-Series Annotations. IEEE Trans. Affect. Comput. 13(1): 473-484 (2022) - [j4]Saurabh Sahu, Rahul Gupta, Carol Y. Espy-Wilson:
Modeling Feature Representations for Affective Speech Using Generative Adversarial Networks. IEEE Trans. Affect. Comput. 13(2): 1098-1110 (2022) - [c57]Rahil Parikh, Christophe Dupuy, Rahul Gupta:
Canary Extraction in Natural Language Understanding Models. ACL (2) 2022: 552-560 - [c56]Yang Trista Cao, Yada Pruksachatkun, Kai-Wei Chang, Rahul Gupta, Varun Kumar, Jwala Dhamala, Aram Galstyan:
On the Intrinsic and Extrinsic Fairness Evaluation Metrics for Contextualized Language Representations. ACL (2) 2022: 561-570 - [c55]Umang Gupta, Jwala Dhamala, Varun Kumar, Apurv Verma, Yada Pruksachatkun, Satyapriya Krishna, Rahul Gupta, Kai-Wei Chang, Greg Ver Steeg, Aram Galstyan:
Mitigating Gender Bias in Distilled Language Models via Counterfactual Role Reversal. ACL (Findings) 2022: 658-678 - [c54]Satyapriya Krishna, Rahul Gupta, Apurv Verma, Jwala Dhamala, Yada Pruksachatkun, Kai-Wei Chang:
Measuring Fairness of Text Classifiers via Prediction Sensitivity. ACL (1) 2022: 5830-5842 - [c53]Stefan Schroedl, Manoj Kumar, Kiana Hajebi, Morteza Ziyadi, Sriram Venkatapathy, Anil Ramakrishna, Rahul Gupta, Pradeep Natarajan:
Improving Large-Scale Conversational Assistants using Model Interpretation based Training Sample Selection. EMNLP (Industry Track) 2022: 371-378 - [c52]Christophe Dupuy, Radhika Arava, Rahul Gupta, Anna Rumshisky:
An Efficient DP-SGD Mechanism for Large Scale NLU Models. ICASSP 2022: 4118-4122 - [c51]Nikhita Vedula, Rahul Gupta, Aman Alok, Mukund Sridhar, Shankar Ananthakrishnan:
Advin: Automatically Discovering Novel Domains and Intents from User Text Utterances. ICASSP 2022: 7627-7631 - [c50]Christophe Dupuy, Tanya G. Roosta, Leo Long, Clement Chung, Rahul Gupta, Salman Avestimehr:
Learnings from Federated Learning in The Real World. ICASSP 2022: 8767-8771 - [c49]Manoj Kumar, Anna Rumshisky, Rahul Gupta:
Chasing the Tail with Domain Generalization: A Case Study on Frequency-Enriched Datasets. AACL/IJCNLP (1) 2022: 1-11 - [c48]Manoj Kumar, Yuval Merhav, Haidar Khan, Rahul Gupta, Anna Rumshisky, Wael Hamza:
Controlled Data Generation via Insertion Operations for NLU. NAACL-HLT (Industry Papers) 2022: 54-61 - [c47]Bill Yuchen Lin, Chaoyang He, Zihang Ze, Hulin Wang, Yufen Hua, Christophe Dupuy, Rahul Gupta, Mahdi Soltanolkotabi, Xiang Ren, Salman Avestimehr:
FedNLP: Benchmarking Federated Learning Methods for Natural Language Processing Tasks. NAACL-HLT (Findings) 2022: 157-175 - [c46]Peyman Passban, Tanya G. Roosta, Rahul Gupta, Ankit Chadha, Clement Chung:
Training Mixed-Domain Translation Models via Federated Learning. NAACL-HLT 2022: 2576-2586 - [c45]Rahul Sharma, Anil Ramakrishna, Ansel MacLaughlin, Anna Rumshisky, Jimit Majmudar, Clement Chung, Salman Avestimehr, Rahul Gupta:
Federated Learning with Noisy User Feedback. NAACL-HLT 2022: 2726-2739 - [c44]Jwala Dhamala, Varun Kumar, Rahul Gupta, Kai-Wei Chang, Aram Galstyan:
An Analysis of The Effects of Decoding Algorithms on Fairness in Open-Ended Language Generation. SLT 2022: 655-662 - [i30]Christophe Dupuy, Tanya G. Roosta, Leo Long, Clement Chung, Rahul Gupta, Salman Avestimehr:
Learnings from Federated Learning in the Real world. CoRR abs/2202.03925 (2022) - [i29]Satyapriya Krishna, Rahul Gupta, Apurv Verma, Jwala Dhamala, Yada Pruksachatkun, Kai-Wei Chang:
Measuring Fairness of Text Classifiers via Prediction Sensitivity. CoRR abs/2203.08670 (2022) - [i28]Umang Gupta, Jwala Dhamala, Varun Kumar, Apurv Verma, Yada Pruksachatkun, Satyapriya Krishna, Rahul Gupta, Kai-Wei Chang, Greg Ver Steeg, Aram Galstyan:
Mitigating Gender Bias in Distilled Language Models via Counterfactual Role Reversal. CoRR abs/2203.12574 (2022) - [i27]Rahil Parikh, Christophe Dupuy, Rahul Gupta:
Canary Extraction in Natural Language Understanding Models. CoRR abs/2203.13920 (2022) - [i26]Yang Trista Cao, Yada Pruksachatkun, Kai-Wei Chang, Rahul Gupta, Varun Kumar, Jwala Dhamala, Aram Galstyan:
On the Intrinsic and Extrinsic Fairness Evaluation Metrics for Contextualized Language Representations. CoRR abs/2203.13928 (2022) - [i25]Peyman Passban, Tanya G. Roosta, Rahul Gupta, Ankit Chadha, Clement Chung:
Training Mixed-Domain Translation Models via Federated Learning. CoRR abs/2205.01557 (2022) - [i24]Rahul Sharma, Anil Ramakrishna, Ansel MacLaughlin, Anna Rumshisky, Jimit Majmudar, Clement Chung, Salman Avestimehr, Rahul Gupta:
Federated Learning with Noisy User Feedback. CoRR abs/2205.03092 (2022) - [i23]Jimit Majmudar, Christophe Dupuy, Charith Peris, Sami Smaili, Rahul Gupta, Richard S. Zemel:
Differentially Private Decoding in Large Language Models. CoRR abs/2205.13621 (2022) - [i22]Saleh Soltan, Shankar Ananthakrishnan, Jack FitzGerald, Rahul Gupta, Wael Hamza, Haidar Khan, Charith Peris, Stephen Rawls, Andy Rosenbaum, Anna Rumshisky, Chandana Satya Prakash, Mukund Sridhar, Fabian Triefenbach, Apurv Verma, Gökhan Tür, Prem Natarajan:
AlexaTM 20B: Few-Shot Learning Using a Large-Scale Multilingual Seq2Seq Model. CoRR abs/2208.01448 (2022) - [i21]Jwala Dhamala, Varun Kumar, Rahul Gupta, Kai-Wei Chang, Aram Galstyan:
An Analysis of the Effects of Decoding Algorithms on Fairness in Open-Ended Language Generation. CoRR abs/2210.03826 (2022) - [i20]Aman Alok, Rahul Gupta, Shankar Ananthakrishnan:
Design Considerations For Hypothesis Rejection Modules In Spoken Language Understanding Systems. CoRR abs/2211.09711 (2022) - [i19]Ninareh Mehrabi, Palash Goyal, Apurv Verma, Jwala Dhamala, Varun Kumar, Qian Hu, Kai-Wei Chang, Richard S. Zemel, Aram Galstyan, Rahul Gupta:
Is the Elephant Flying? Resolving Ambiguities in Text-to-Image Generative Models. CoRR abs/2211.12503 (2022) - 2021
- [c43]Yada Pruksachatkun, Satyapriya Krishna, Jwala Dhamala, Rahul Gupta, Kai-Wei Chang:
Does Robustness Improve Fairness? Approaching Fairness with Word Substitution Robustness Methods for Text Classification. ACL/IJCNLP (Findings) 2021: 3320-3331 - [c42]Satyapriya Krishna, Rahul Gupta, Christophe Dupuy:
ADePT: Auto-encoder based Differentially Private Text Transformation. EACL 2021: 2435-2439 - [c41]Justin Payan, Yuval Merhav, He Xie, Satyapriya Krishna, Anil Ramakrishna, Mukund Sridhar, Rahul Gupta:
Towards Realistic Single-Task Continuous Learning Research for NER. EMNLP (Findings) 2021: 3773-3783 - [c40]Jwala Dhamala, Tony Sun, Varun Kumar, Satyapriya Krishna, Yada Pruksachatkun, Kai-Wei Chang, Rahul Gupta:
BOLD: Dataset and Metrics for Measuring Biases in Open-Ended Language Generation. FAccT 2021: 862-872 - [c39]Manoj Kumar, Varun Kumar, Hadrien Glaude, Cyprien de Lichy, Aman Alok, Rahul Gupta:
Protoda: Efficient Transfer Learning for Few-Shot Intent Classification. SLT 2021: 966-972 - [i18]Jwala Dhamala, Tony Sun, Varun Kumar, Satyapriya Krishna, Yada Pruksachatkun, Kai-Wei Chang, Rahul Gupta:
BOLD: Dataset and Metrics for Measuring Biases in Open-Ended Language Generation. CoRR abs/2101.11718 (2021) - [i17]Manoj Kumar, Varun Kumar, Hadrien Glaude, Cyprien de Lichy, Aman Alok, Rahul Gupta:
ProtoDA: Efficient Transfer Learning for Few-Shot Intent Classification. CoRR abs/2101.11753 (2021) - [i16]Satyapriya Krishna, Rahul Gupta, Christophe Dupuy:
ADePT: Auto-encoder based Differentially Private Text Transformation. CoRR abs/2102.01502 (2021) - [i15]Yada Pruksachatkun, Satyapriya Krishna, Jwala Dhamala, Rahul Gupta, Kai-Wei Chang:
Does Robustness Improve Fairness? Approaching Fairness with Word Substitution Robustness Methods for Text Classification. CoRR abs/2106.10826 (2021) - [i14]Christophe Dupuy, Radhika Arava, Rahul Gupta, Anna Rumshisky:
An Efficient DP-SGD Mechanism for Large Scale NLP Models. CoRR abs/2107.14586 (2021) - [i13]Justin Payan, Yuval Merhav, He Xie, Satyapriya Krishna, Anil Ramakrishna, Mukund Sridhar, Rahul Gupta:
Towards Realistic Single-Task Continuous Learning Research for NER. CoRR abs/2110.14694 (2021) - 2020
- [c38]Ansel MacLaughlin, Jwala Dhamala, Anoop Kumar, Sriram Venkatapathy, Ragav Venkatesan, Rahul Gupta:
Evaluating the Effectiveness of Efficient Neural Architecture Search for Sentence-Pair Tasks. Insights 2020: 22-31 - [c37]Aman Alok, Rahul Gupta, Shankar Ananthakrishnan:
Design Considerations for Hypothesis Rejection Modules in Spoken Language Understanding Systems. ICASSP 2020: 8049-8053 - [i12]Anil Ramakrishna, Rahul Gupta, Shrikanth Narayanan:
Joint Multi-Dimensional Model for Global and Time-Series Annotations. CoRR abs/2005.03117 (2020) - [i11]Aarsh Patel, Rahul Gupta, Mukund Harakere, Satyapriya Krishna, Aman Alok, Peng Liu:
Towards classification parity across cohorts. CoRR abs/2005.08033 (2020) - [i10]Nikhita Vedula, Rahul Gupta, Aman Alok, Mukund Sridhar:
Automatic Discovery of Novel Intents & Domains from Text Utterances. CoRR abs/2006.01208 (2020) - [i9]Ansel MacLaughlin, Jwala Dhamala, Anoop Kumar, Sriram Venkatapathy, Ragav Venkatesan, Rahul Gupta:
Evaluating the Effectiveness of Efficient Neural Architecture Search for Sentence-Pair Tasks. CoRR abs/2010.04249 (2020)
2010 – 2019
- 2019
- [c36]Taruna Agrawal, Rahul Gupta, Shrikanth S. Narayanan:
On Evaluating CNN Representations for Low Resource Medical Image Classification. ICASSP 2019: 1363-1367 - [c35]Rahul Gupta, Aman Alok, Shankar Ananthakrishnan:
One-vs-All Models for Asynchronous Training: An Empirical Analysis. INTERSPEECH 2019: 794-798 - [i8]Taruna Agrawal, Rahul Gupta, Shrikanth S. Narayanan:
On evaluating CNN representations for low resource medical image classification. CoRR abs/1903.11176 (2019) - [i7]Rahul Gupta, Aman Alok, Shankar Ananthakrishnan:
One-vs-All Models for Asynchronous Training: An Empirical Analysis. CoRR abs/1906.08858 (2019) - [i6]Saurabh Sahu, Rahul Gupta, Carol Y. Espy-Wilson:
Modeling Feature Representations for Affective Speech using Generative Adversarial Networks. CoRR abs/1911.00030 (2019) - 2018
- [j3]Rahul Gupta, Kartik Audhkhasi, Zach Jacokes, Agata Rozga, Shrikanth S. Narayanan:
Modeling Multiple Time Series Annotations as Noisy Distortions of the Ground Truth: An Expectation-Maximization Approach. IEEE Trans. Affect. Comput. 9(1): 76-89 (2018) - [c34]Saurabh Sahu, Rahul Gupta, Ganesh Sivaraman, Carol Y. Espy-Wilson:
Smoothing Model Predictions Using Adversarial Training Procedures for Speech Based Emotion Recognition. ICASSP 2018: 4934-4938 - [c33]Rahul Gupta, Saurabh Sahu, Carol Y. Espy-Wilson, Shrikanth S. Narayanan:
Semi-Supervised and Transfer Learning Approaches for Low Resource Sentiment Classification. ICASSP 2018: 5109-5113 - [c32]Saurabh Sahu, Rahul Gupta, Carol Y. Espy-Wilson:
On Enhancing Speech Emotion Recognition Using Generative Adversarial Networks. INTERSPEECH 2018: 3693-3697 - [c31]Chengwei Su, Rahul Gupta, Shankar Ananthakrishnan, Spyros Matsoukas:
A Re-Ranker Scheme For Integrating Large Scale NLU Models. SLT 2018: 670-676 - [i5]Saurabh Sahu, Rahul Gupta, Ganesh Sivaraman, Wael AbdAlmageed, Carol Y. Espy-Wilson:
Adversarial Auto-encoders for Speech Based Emotion Recognition. CoRR abs/1806.02146 (2018) - [i4]Rahul Gupta, Saurabh Sahu, Carol Y. Espy-Wilson, Shrikanth S. Narayanan:
Semi-supervised and Transfer learning approaches for low resource sentiment classification. CoRR abs/1806.02863 (2018) - [i3]Saurabh Sahu, Rahul Gupta, Carol Y. Espy-Wilson:
On Enhancing Speech Emotion Recognition using Generative Adversarial Networks. CoRR abs/1806.06626 (2018) - [i2]Chengwei Su, Rahul Gupta, Shankar Ananthakrishnan, Spyros Matsoukas:
A Re-ranker Scheme for Integrating Large Scale NLU models. CoRR abs/1809.09605 (2018) - 2017
- [c30]Taruna Agrawal, Rahul Gupta, Shrikanth S. Narayanan:
Multimodal detection of fake social media use through a fusion of classification and pairwise ranking systems. EUSIPCO 2017: 1045-1049 - [c29]Sabyasachee Baruah, Rahul Gupta, Shrikanth S. Narayanan:
A knowledge transfer and boosting approach to the prediction of affect in movies. ICASSP 2017: 2876-2880 - [c28]Saurabh Sahu, Rahul Gupta, Ganesh Sivaraman, Wael AbdAlmageed, Carol Y. Espy-Wilson:
Adversarial Auto-Encoders for Speech Based Emotion Recognition. INTERSPEECH 2017: 1243-1247 - [c27]Qinyi Luo, Rahul Gupta, Shrikanth S. Narayanan:
Transfer Learning Between Concepts for Human Behavior Modeling: An Application to Sincerity and Deception Prediction. INTERSPEECH 2017: 1462-1466 - [c26]Rahul Gupta, Saurabh Sahu, Carol Y. Espy-Wilson, Shrikanth S. Narayanan:
An Affect Prediction Approach Through Depression Severity Parameter Incorporation in Neural Networks. INTERSPEECH 2017: 3122-3126 - [c25]Taruna Agrawal, Rahul Gupta, Saurabh Sahu, Carol Y. Espy-Wilson:
SCL-UMD at the Medico Task-MediaEval 2017: Transfer Learning based Classification of Medical Images. MediaEval 2017 - 2016
- [j2]Rahul Gupta, Kartik Audhkhasi, Sungbok Lee, Shrikanth S. Narayanan:
Detecting paralinguistic events in audio stream using context in features and probabilistic decisions. Comput. Speech Lang. 36: 72-92 (2016) - [j1]Rahul Gupta, Daniel Bone, Sungbok Lee, Shrikanth S. Narayanan:
Analysis of engagement behavior in children during dyadic interactions using prosodic cues. Comput. Speech Lang. 37: 47-66 (2016) - [c24]Rahul Gupta, Theodora Chaspari, Jangwon Kim, Naveen Kumar, Daniel Bone, Shrikanth S. Narayanan:
Pathological speech processing: State-of-the-art, current challenges, and future directions. ICASSP 2016: 6470-6474 - [c23]Rahul Gupta, Nishant Nath, Taruna Agrawal, Panayiotis G. Georgiou, David C. Atkins, Shrikanth S. Narayanan:
Laughter Valence Prediction in Motivational Interviewing Based on Lexical and Acoustic Cues. INTERSPEECH 2016: 505-509 - [c22]Daniel Bone, Somer Bishop, Rahul Gupta, Sungbok Lee, Shrikanth S. Narayanan:
Acoustic-Prosodic and Turn-Taking Features in Interactions with Children with Neurodevelopmental Disorders. INTERSPEECH 2016: 1185-1189 - [c21]Rahul Gupta, Shrikanth S. Narayanan:
Predicting Affective Dimensions Based on Self Assessed Depression Severity. INTERSPEECH 2016: 1427-1431 - [c20]Anil Ramakrishna, Rahul Gupta, Ruth B. Grossman, Shrikanth S. Narayanan:
An Expectation Maximization Approach to Joint Modeling of Multidimensional Ratings Derived from Multiple Annotators. INTERSPEECH 2016: 1555-1559 - [c19]Brandon M. Booth, Rahul Gupta, Pavlos Papadopoulos, Ruchir Travadi, Shrikanth S. Narayanan:
Automatic Estimation of Perceived Sincerity from Spoken Language. INTERSPEECH 2016: 2021-2025 - [c18]Manoj Kumar, Rahul Gupta, Daniel Bone, Nikolaos Malandrakis, Somer Bishop, Shrikanth S. Narayanan:
Objective Language Feature Analysis in Children with Neurodevelopmental Disorders During Autism Assessment. INTERSPEECH 2016: 2721-2725 - [c17]Krishna Somandepalli, Rahul Gupta, Md. Nasir, Brandon M. Booth, Sungbok Lee, Shrikanth S. Narayanan:
Online Affect Tracking with Multimodal Kalman Filters. AVEC@ACM Multimedia 2016: 59-66 - [i1]Rahul Gupta, Shrikanth S. Narayanan:
Inferring object rankings based on noisy pairwise comparisons from multiple annotators. CoRR abs/1612.04413 (2016) - 2015
- [c16]Rahul Gupta, Naveen Kumar, Shrikanth S. Narayanan:
Affect prediction in music using boosted ensemble of filters. EUSIPCO 2015: 11-15 - [c15]Rahul Gupta, Kartik Audhkhasi, Shrikanth S. Narayanan:
A mixture of experts approach towards intelligibility classification of pathological speech. ICASSP 2015: 1986-1990 - [c14]Sandeep Nallan Chakravarthula, Rahul Gupta, Brian R. Baucom, Panayiotis G. Georgiou:
A language-based generative model framework for behavioral analysis of couples' therapy. ICASSP 2015: 2090-2094 - [c13]Matthew P. Black, Daniel Bone, Zisis Iason Skordilis, Rahul Gupta, Wei Xia, Pavlos Papadopoulos, Sandeep Nallan Chakravarthula, Bo Xiao, Maarten Van Segbroeck, Jangwon Kim, Panayiotis G. Georgiou, Shrikanth S. Narayanan:
Automated evaluation of non-native English pronunciation quality: combining knowledge- and data-driven features at multiple time scales. INTERSPEECH 2015: 493-497 - [c12]Jangwon Kim, Md. Nasir, Rahul Gupta, Maarten Van Segbroeck, Daniel Bone, Matthew P. Black, Zisis Iason Skordilis, Zhaojun Yang, Panayiotis G. Georgiou, Shrikanth S. Narayanan:
Automatic estimation of parkinson's disease severity from diverse speech tasks. INTERSPEECH 2015: 914-918 - [c11]Rahul Gupta, Theodora Chaspari, Panayiotis G. Georgiou, David C. Atkins, Shrikanth S. Narayanan:
Analysis and modeling of the role of laughter in motivational interviewing based psychotherapy conversations. INTERSPEECH 2015: 1962-1966 - [c10]Taruna Agrawal, Rahul Gupta, Shrikanth S. Narayanan:
Retrieving Social Images using Relevance Filtering and Diverse Selection. MediaEval 2015 - [c9]Rahul Gupta, Shrikanth S. Narayanan:
Predicting Affect in Music Using Regression Methods on Low Level Features. MediaEval 2015 - 2014
- [c8]Rahul Gupta, Kartik Audhkhasi, Shrikanth S. Narayanan:
Training ensemble of diverse classifiers on feature subsets. ICASSP 2014: 2927-2931 - [c7]Rahul Gupta, Panayiotis G. Georgiou, David C. Atkins, Shrikanth S. Narayanan:
Predicting client's inclination towards target behavior change in motivational interviewing and investigating the role of laughter. INTERSPEECH 2014: 208-212 - [c6]Rahul Gupta, Sankaranarayanan Ananthakrishnan, Zhaojun Yang, Shrikanth S. Narayanan:
Variable Span disfluency detection in ASR transcripts. INTERSPEECH 2014: 2892-2896 - [c5]Naveen Kumar, Rahul Gupta, Tanaya Guha, Colin Vaz, Maarten Van Segbroeck, Jangwon Kim, Shrikanth S. Narayanan:
Affective Feature Design and Predicting Continuous Affective Dimensions from Music. MediaEval 2014 - [c4]Rahul Gupta, Nikolaos Malandrakis, Bo Xiao, Tanaya Guha, Maarten Van Segbroeck, Matthew Black, Alexandros Potamianos, Shrikanth S. Narayanan:
Multimodal Prediction of Affective Dimensions and Depression in Human-Computer Interactions. AVEC@MM 2014: 33-40 - 2013
- [c3]Rahul Gupta, Kartik Audhkhasi, Sungbok Lee, Shrikanth S. Narayanan:
Paralinguistic event detection from speech using probabilistic time-series smoothing and masking. INTERSPEECH 2013: 173-177 - 2012
- [c2]Rahul Gupta, Chi-Chun Lee, Shrikanth S. Narayanan:
Classification of emotional content of sighs in dyadic human interactions. ICASSP 2012: 2265-2268 - [c1]Rahul Gupta, Chi-Chun Lee, Daniel Bone, Agata Rozga, Sungbok Lee, Shrikanth S. Narayanan:
Acoustical analysis of engagement behavior in children. WOCCI 2012: 25-31
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