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Robert S. Belvin

dblp:27/6314 · DBLP profile ↗
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5ranked-venue papers
4as first author
0since 2021 · last 2018
—ORCID · none

Domains — the database's venue-derived domains; a paper can count in several

Artificial intelligence and machine learning · 4 · 4 first-authorGraphics, computer vision, multimedia, augmented reality and games · 2 · 2 first-authorDatabases, data management, data science and information retrieval · 1

Expertise — from the expertise taxonomy: the topics of the expert's papers under the CCF categories. A weight counts papers with recency: 1 for a paper about the topic, 0.3 when the topic is its context, halved every five years.

Artificial intelligence
1 paper
Machine translation · 100%
Interdisciplinary, comprehensive, and emerging computing
1 paper
Medical and health informatics · 100%

Topics — the 2 heaviest of 2, each with the papers that count most for it

TopicWeightPapersLastEvidence papers
Natural language and speech › Machine translation › speech translation
speech-to-speech translation
0.112005
Transonics: A Practical Speech-to-Speech Translator for English-Farsi Medical Dialogs · ACL 2005
Medical and health informatics › clinical text processing
clinical dialogue
0.012005
Transonics: A Practical Speech-to-Speech Translator for English-Farsi Medical Dialogs · ACL 2005
YearPublicationVenuePosition
2018 Collaborative exploratory search for information filtering and large-scale information triage
abstract
Modern information seekers face dynamic streams of large‐scale heterogeneous data that are both intimidating and overwhelming. They need a strategy to filter this barrage of massive data sets, and to find all of the information responding to their information needs, despite the pressures imposed by schedules and budgets. In this applied research, we present an exploratory search strategy that allows professional information seekers to efficiently and effectively triage all of the data. We demonstrate that exploratory search is particularly useful for information filtering and large‐scale information triage, regardless of the language of the data, and regardless of the particular industry, whether finance, medical, business, government, information technology, news, or legal. Our strategy reduces a dauntingly large volume of information into a manageable, high‐precision data set, suitable for focused reading. This strategy is interdisciplinary, integrating concepts from information filtering, information triage, and exploratory search. Key aspects include advanced search software, interdisciplinary paired search, asynchronous collaborative search, attention to linguistic phenomena, and aggregated search results in the form of a search matrix or search grid. We present the positive results of a task‐oriented evaluation in a real‐world setting, discuss these results from a qualitative perspective, and share future research areas.
Paul M. Herceg, Timothy B. Allison, Robert S. Belvin, Evelyne Tzoukermann
J. Assoc. Inf. Sci. Technol.3
2005 Transonics: A Practical Speech-to-Speech Translator for English-Farsi Medical Dialogs
Robert S. Belvin, Emil Ettelaie, Sudeep Gandhe, Panayiotis G. Georgiou, Kevin Knight, Daniel Marcu, Scott Millward, Shri Narayanan, Howard Neely, David R. Traum
ACL1
2004 A Fine-Grained Evaluation Method for Speech-to-Speech Machine Translation Using Concept Annotations
Robert S. Belvin, Susanne Z. Riehemann, Kristin Precoda
LREC1
2000 What²s next: a case study in the multidimensionality of a dialog system
Robert S. Belvin, Ron Burns, Cheryl Hein
INTERSPEECH1
2000 Spoken language navigation systems for drivers
Robert S. Belvin, Ron Burns, Cheryl Hein
INTERSPEECH1