Raghavendra Reddy Pappagari

About Raghavendra Reddy Pappagari

Raghavendra Reddy Pappagari, With an exceptional h-index of 13 and a recent h-index of 12 (since 2020), a distinguished researcher at Johns Hopkins University, specializes in the field of Spoken Language Understanding, Emotion Recognition, Health-related applications, Speaker Verification, Dialogue Systems.

His recent articles reflect a diverse array of research interests and contributions to the field:

M3T: A new benchmark dataset for multi-modal document-level machine translation

Towards Better Understanding of Spoken Conversations: Assessment of Emotion and Sentiment

MT-GenEval: A counterfactual and contextual dataset for evaluating gender accuracy in machine translation

Non-contrastive self-supervised learning of utterance-level speech representations

Copypaste: An augmentation method for speech emotion recognition

Beyond isolated utterances: Conversational emotion recognition

Joint prediction of truecasing and punctuation for conversational speech in low-resource scenarios

What helps transformers recognize conversational structure? Importance of context, punctuation, and labels in dialog act recognition

Raghavendra Reddy Pappagari Information

University

Position

The

Citations(all)

984

Citations(since 2020)

917

Cited By

296

hIndex(all)

13

hIndex(since 2020)

12

i10Index(all)

17

i10Index(since 2020)

15

Email

University Profile Page

Google Scholar

Raghavendra Reddy Pappagari Skills & Research Interests

Spoken Language Understanding

Emotion Recognition

Health-related applications

Speaker Verification

Dialogue Systems

Top articles of Raghavendra Reddy Pappagari

Title

Journal

Author(s)

Publication Date

M3T: A new benchmark dataset for multi-modal document-level machine translation

Benjamin Hsu

Xiaoyu Liu

Huayang Li

Yoshinari Fujinuma

Maria Nădejde

...

2024

Towards Better Understanding of Spoken Conversations: Assessment of Emotion and Sentiment

Raghavendra Reddy Pappagari

2022/2/8

MT-GenEval: A counterfactual and contextual dataset for evaluating gender accuracy in machine translation

arXiv preprint arXiv:2211.01355

Anna Currey

Maria Nădejde

Raghavendra Pappagari

Mia Mayer

Stanislas Lauly

...

2022/11/2

Non-contrastive self-supervised learning of utterance-level speech representations

arXiv preprint arXiv:2208.05413

Jaejin Cho

Raghavendra Pappagari

Piotr Żelasko

Laureano Moro-Velazquez

Jesús Villalba

...

2022/8/10

Copypaste: An augmentation method for speech emotion recognition

Raghavendra Pappagari

Jesús Villalba

Piotr Żelasko

Laureano Moro-Velazquez

Najim Dehak

2021/6/6

Beyond isolated utterances: Conversational emotion recognition

Raghavendra Pappagari

Piotr Żelasko

Jesús Villalba

Laureano Moro-Velazquez

Najim Dehak

2021/12/13

Joint prediction of truecasing and punctuation for conversational speech in low-resource scenarios

Raghavendra Pappagari

Piotr Żelasko

Agnieszka Mikołajczyk

Piotr Pęzik

Najim Dehak

2021/12/13

What helps transformers recognize conversational structure? Importance of context, punctuation, and labels in dialog act recognition

Transactions of the Association for Computational Linguistics

Piotr Żelasko

Raghavendra Pappagari

Najim Dehak

2021/10/27

Automatic Detection and Assessment of Alzheimer Disease Using Speech and Language Technologies in Low-Resource Scenarios.

Interspeech

Raghavendra Pappagari

Jaejin Cho

Sonal Joshi

Laureano Moro-Velázquez

Piotr Zelasko

...

2021/8/30

Using State of the Art Speaker Recognition and Natural Language Processing Technologies to Detect Alzheimer's Disease and Assess its Severity.

Raghavendra Pappagari

Jaejin Cho

Laureano Moro-Velazquez

Najim Dehak

2020/10

x-vectors meet emotions: A study on dependencies between emotion and speaker recognition

Raghavendra Pappagari

Tianzi Wang

Jesus Villalba

Nanxin Chen

Najim Dehak

2020/5/4

See List of Professors in Raghavendra Reddy Pappagari University(Johns Hopkins University)

Co-Authors

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