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J. Garofolo

Bio: J. Garofolo is an academic researcher from Massachusetts Institute of Technology. The author has contributed to research in topics: Data collection & Information system. The author has an hindex of 1, co-authored 1 publications receiving 203 citations.

Papers
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Proceedings ArticleDOI
21 Mar 1993
TL;DR: This work focuses here on selection of training and test data, evaluation of language understanding, and the continuing search for evaluation methods that will correlate well with expected performance of the technology in applications.
Abstract: The Air Travel Information System (ATIS) domain serves as the common task for DARPA spoken language system research and development The approaches and results possible in this rapidly growing area are structured by available corpora, annotations of that data, and evaluation methods Coordination of this crucial infrastructure is the charter of the Multi-Site ATIS Data COllection Working group (MADCOW) We focus here on selection of training and test data, evaluation of language understanding, and the continuing search for evaluation methods that will correlate well with expected performance of the technology in applications

206 citations


Cited by
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Patent
11 Jan 2011
TL;DR: In this article, an intelligent automated assistant system engages with the user in an integrated, conversational manner using natural language dialog, and invokes external services when appropriate to obtain information or perform various actions.
Abstract: An intelligent automated assistant system engages with the user in an integrated, conversational manner using natural language dialog, and invokes external services when appropriate to obtain information or perform various actions. The system can be implemented using any of a number of different platforms, such as the web, email, smartphone, and the like, or any combination thereof. In one embodiment, the system is based on sets of interrelated domains and tasks, and employs additional functionally powered by external services with which the system can interact.

1,462 citations

Patent
28 Sep 2012
TL;DR: In this article, a virtual assistant uses context information to supplement natural language or gestural input from a user, which helps to clarify the user's intent and reduce the number of candidate interpretations of user's input, and reduces the need for the user to provide excessive clarification input.
Abstract: A virtual assistant uses context information to supplement natural language or gestural input from a user. Context helps to clarify the user's intent and to reduce the number of candidate interpretations of the user's input, and reduces the need for the user to provide excessive clarification input. Context can include any available information that is usable by the assistant to supplement explicit user input to constrain an information-processing problem and/or to personalize results. Context can be used to constrain solutions during various phases of processing, including, for example, speech recognition, natural language processing, task flow processing, and dialog generation.

593 citations

Proceedings ArticleDOI
08 Mar 1994
TL;DR: The migration of the ATIS task to a richer relational database and development corpus (ATIS-3) and the ATis-3 corpus is described, including breakdowns of data by type (e.g. context-independent, context-dependent, and unevaluable) and variations in the data collected at different sites.
Abstract: The Air Travel Information System (ATIS) domain serves as the common evaluation task for ARPA spoken language system developers. To support this task, the Multi-Site ATIS Data COllection Working group (MADCOW) coordinates data collection activities. This paper describes recent MADCOW activities. In particular, this paper describes the migration of the ATIS task to a richer relational database and development corpus (ATIS-3) and describes the ATIS-3 corpus. The expanded database, which includes information on 46 US and Canadian cities and 23,457 flights, was released in the fall of 1992, and data collection for the ATIS-3 corpus began shortly thereafter. The ATIS-3 corpus now consists of a total of 8297 released training utterances and 3211 utterances reserved for testing, collected at BBN, CMU, MIT, NIST and SRI. 2906 of the training utterances have been annotated with the correct information from the database. This paper describes the ATIS-3 corpus in detail, including breakdowns of data by type (e.g. context-independent, context-dependent, and unevaluable)and variations in the data collected at different sites. This paper also includes a description of the ATIS-3 database. Finally, we discuss future data collection and evaluation plans.

403 citations

Patent
08 Sep 2006
TL;DR: In this paper, a method for building an automated assistant includes interfacing a service-oriented architecture that includes a plurality of remote services to an active ontology, where the active ontologies includes at least one active processing element that models a domain.
Abstract: A method and apparatus are provided for building an intelligent automated assistant. Embodiments of the present invention rely on the concept of “active ontologies” (e.g., execution environments constructed in an ontology-like manner) to build and run applications for use by intelligent automated assistants. In one specific embodiment, a method for building an automated assistant includes interfacing a service-oriented architecture that includes a plurality of remote services to an active ontology, where the active ontology includes at least one active processing element that models a domain. At least one of the remote services is then registered for use in the domain.

389 citations

Patent
05 Jun 2009
TL;DR: In this paper, techniques and systems for implementing contextual voice commands are described and a physical input that relates the selected data item to an operation in a second context is received, and the operation is performed on the input data item in the second context.
Abstract: Among other things, techniques and systems are disclosed for implementing contextual voice commands. On a device, a data item in a first context is displayed. On the device, a physical input selecting the displayed data item in the first context is received. On the device, a voice input that relates the selected data item to an operation in a second context is received. The operation is performed on the selected data item in the second context.

385 citations