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Metalogue multi-Issue bargaining dialogue
Title
Metalogue multi-Issue bargaining dialogue / Linguistic Data Consortium.
ISBN
1585638056
Publication
[Philadelphia, PA] : [Linguistic Data Consortium], [2017]
Physical Description
1 online resource
Local Notes
Access is available to the Yale community.
Notes
Authors: Volha Petukhova, Andrei Malchanau, Youssef Oualil, Dietrich Klakow, Christopher Stevens, Harmen de Weerd, Niels Taatgen.
Data source: microphone conversation.
Applications: speech recognition, spoken dialogue modeling, language modeling.
LDC number: LDC2017S11.
In English.
Title from resource home page (LDC website, viewed September 21, 2020).
Access and use
Access restricted by licensing agreement.
Summary
"Metalogue Multi-Issue Bargaining Dialogue was developed by the Metalogue Consortium under the European Community's Seventh Framework Programme for Research and Technological Development. This release consists of approximately 2.5 hours of semantically annotated English dialogue data that includes speech and transcripts. The goal of the Metalogue project was to develop a dialogue system with flexible dialogue management to enable the system's behavior in setting goals, choosing strategies and monitoring various processes. Participants were involved in a multi-issue bargaining scenario in which a representative of a city council and a representative of small business owners negotiated the implementation of new anti-smoking regulations. The negotiation involved four issues, each with four or five options. Participants received a preference profile for each scenario and negotiated for an agreement with the highest value based on their preference information. Negotiators were not allowed to accept an agreement with a negative value or to share their preference profiles with other participants. Six unique subjects (undergraduates between 19 and 25 years of age) participated in the collection. The dialogue speech was captured with two headset microphones and saved in 16kHz, 16-bit mono linear PCM FLAC format. Speech signal files are of two types: full dialogue session; and segmented speech signal, cut per speaker and roughly per turn. Transcripts were produced semi-automatically, using an automatic speech recognizer followed by manual correction. Seven types of annotation were performed manually using the Anvil tool: dialogue act annotations; discourse structure acts; contact management acts; task management dialogue acts; negotiation moves; rhetorical relations; and disfluencies in speech production. More information about the annotation process is included in the documentation." --LDC online catalog.
Format
Audio / Data Sets / Online
Language
English
Added to Catalog
September 21, 2020
Subjects
Genre/Form
Data sets.
Speech corpora.
Sound recordings.
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