World's Best Scientists 2026 revealed!

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Computer Science

D-Index
38
Citations
7030
World Ranking
10144
National Ranking
4275

Research.com Recognitions

  • 2010 - IEEE Fellow For contributions to statistical natural language understanding and spoken dialog management and learning

Overview

Roberto Pieraccini is a researcher affiliated with Google in the United States. Their academic and professional work primarily concentrates on computer science, with a particular focus on artificial intelligence and computer vision and pattern recognition.

The research output includes contributions to topics such as multimodal machine learning applications, topic modeling, speech and dialogue systems, domain adaptation and few-shot learning, and multi-agent systems and negotiation.

  • Multimodal Machine Learning Applications
  • Topic Modeling
  • Speech and dialogue systems
  • Domain Adaptation and Few-Shot Learning
  • Multi-Agent Systems and Negotiation

Their recent publications include:

  • REFINE on Scarce Data: Retrieval Enhancement through Fine-Tuning via Model Fusion of Embedding Models, 2024, arXiv (Cornell University)
  • Pre-Act: Multi-Step Planning and Reasoning Improves Acting in LLM Agents, 2025, arXiv (Cornell University)

Frequent co-authors listed alongside Roberto Pieraccini are Ambuje Gupta, Mrinal Rawat, Andreas Stolcke, and Rushil Goomer.

  • Ambuje Gupta
  • Mrinal Rawat
  • Andreas Stolcke
  • Rushil Goomer

Regarding venues for publication, the researcher has notably contributed to arXiv (Cornell University) for at least two papers.

  • arXiv (Cornell University)

Roberto Pieraccini also has a book published by The MIT Press entitled AI Assistants released in 2021, which has been cited in academic literature.

Their contributions to the field of statistical natural language understanding and spoken dialog management and learning were recognized by the IEEE through the conferment of the IEEE Fellow award in 2010.

Best Publications

  • A stochastic model of human-machine interaction for learning dialog strategies

    E. Levin;R. Pieraccini;W. Eckert

  • Method of using a natural language interface to retrieve information from one or more data resources

    Esther Levin;Shrikanth Sambasivan Narayanan;Roberto Pieraccini;Ilija Zeljkovic

  • User modeling for spoken dialogue system evaluation

    W. Eckert;E. Levin;R. Pieraccini

  • Using Markov decision process for learning dialogue strategies

    E. Levin;R. Pieraccini;W. Eckert

  • Acoustic modeling for large vocabulary speech recognition

    C.H. Lee;L.R. Rabiner;R. Pieraccini;J.G. Wilpon

  • COMBINING ACOUSTIC AND LANGUAGE INFORMATION FOR EMOTION RECOGNITION

    Chul Min Lee;Shrikanth S. Narayanan;Roberto Pieraccini

  • Method and apparatus for multiple value confirmation and correction in spoken dialog systems

    Sasha Porto Caskey;Juan Manuel Huerta;Roberto Pieraccini

  • A stochastic model of computer-human interaction for learning dialogue strategies.

    Esther Levin;Roberto Pieraccini

  • Recognition of negative emotions from the speech signal

    C.M. Lee;S. Narayanan;R. Pieraccini

  • Dynamic planar warping for optical character recognition

    E. Levin;R. Pieraccini

  • The Voice in the Machine: Building Computers That Understand Speech

    Roberto Pieraccini

  • Learning dialogue strategies within the Markov decision process framework

    E. Levin;R. Pieraccini;W. Eckert

  • Automating spoken dialogue management design using machine learning: An industry perspective

    Tim Paek;Roberto Pieraccini

  • Word juncture modeling using inter-word context-dependent phone-like units.

    Egidio P. Giachin;Chin-Hui Lee;Lawrence R. Rabiner;Aaron E. Rosenberg

  • Natural language knowledge servers as network resources

    Edward Dennis Haszto;Esther Levin;Stephen Michael Marcus;Roberto Pieraccini

  • Stochastic automata for language modeling

    Giuseppe Riccardi;Roberto Pieraccini;Enrico Bocchieri

  • A speech understanding system based on statistical representation of semantics

    R. Pieraccini;E. Tzoukermann;Z. Gorelov;J.-L. Gauvain

  • The AT&t-DARPA communicator mixed-initiative spoken dialog system.

    Esther Levin;Shrikanth S. Narayanan;Roberto Pieraccini;Konstantin Biatov

  • Where do we go from here? Research and Commercial Spoken Dialog Systems.

    Roberto Pieraccini;Juan Huerta

  • Improved acoustic modeling for large vocabulary continuous speech recognition

    C.-H. Lee;E. Giachin;L.R. Rabiner;R. Pieraccini

Frequent Co-Authors

Lawrence R. Rabiner
Lawrence R. Rabiner Rutgers, The State University of New Jersey
Chin-Hui Lee
Chin-Hui Lee Georgia Institute of Technology
Anthony Vetro
Anthony Vetro Mitsubishi Electric (United States)
Aleksandra Mojsilovic
Aleksandra Mojsilovic IBM (United States)
Brendan J. Frey
Brendan J. Frey University of Toronto
Andrea Cavallaro
Andrea Cavallaro Queen Mary University of London
Shrikanth S. Narayanan
Shrikanth S. Narayanan University of Southern California
Aaron E. Rosenberg
Aaron E. Rosenberg AT&T (United States)
Fernando Pereira
Fernando Pereira Instituto Superior Técnico
Alex B. Gershman
Alex B. Gershman Technical University of Darmstadt

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