Natural Language Processing

In Natural Language Processing (NLP), we focus on how computers understand and interact with humans through natural conversation and text. We develop new NLP methods for collecting, processing, analyzing and understanding large amounts of natural language data for diverse applications such as intelligent conversational assistants, natural language search, document intelligence and knowledge acquisition.  

Our research projects span natural language understanding, dialogue systems, document semantics and affect understanding, document re-synthesis, text-mining, structured information extraction, knowledge acquisition and representation, joint language and vision-based understanding of images and videos, deep learning, and the use of natural language for computational creativity.  Our work includes efforts in intelligent assistants, multimodal search, document understanding, content generation, affect modelling, and multimodal content synthesis.  

Meet some of our researchersView More

David Seunghyun Yoon

Research Scientist

Kushal Kafle

Research Scientist

Chris Tensmeyer

Research Scientist

View our latest publicationsView More

DocLayoutTTS: Dataset and Baselines for Layout-informed Document-level Neural Speech Synthesis

Mathur, P., Dernoncourt, F., Tran, Q., Gu, J., Nenkova, A., Morariu, V., Jain, R., Manocha, D. (Sep. 22, 2022)

Interspeech 2022

DynamicToC: Persona-based Table of Contents for Consumption of Long Documents

Maheshwari, H., Shivakumar, N., Jain, S., Karandikar, T., Goyal, N., Aggarwal, V., Shekhar, S. (Jul. 15, 2022)

North American Chapter of the Association for Computational Linguistics (NAACL)

Joint Extraction of Entities, Relations, and Events via Modeling Inter-Instance and Inter-Label Dependencies

Van Nguyen, M., Min, B., Dernoncourt, F., Nguyen, T. (Jul. 15, 2022)

NAACL 2022

Knowledge Graphs

At Adobe Research, research scientists are exploring new ways of using knowledge graphs to develop tools to inform and inspire our customers. Knowledge graphs represent complex real-world material in a rich, interconnected network, helping users find answers that might otherwise be hidden.

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We are looking for researchers, engineers, and interns to take our technologies to the next level. We're recruiting, and we would love to hear from you!