Metalogue Multi-Issue Bargaining Dialogue

Item Name: Metalogue Multi-Issue Bargaining Dialogue
Author(s): Volha Petukhova, Andrei Malchanau, Youssef Oualil, Dietrich Klakow, Christopher Stevens, Harmen de Weerd, Niels Taatgen
LDC Catalog No.: LDC2017S11
ISBN: 1-58563-805-6
ISLRN: 217-906-813-531-9
Release Date: July 18, 2017
Member Year(s): 2017
DCMI Type(s): Sound, Text
Sample Type: pcm
Sample Rate: 16000
Data Source(s): microphone conversation
Application(s): speech recognition, spoken dialogue modeling, language modeling
Language(s): English
Language ID(s): eng
License(s): LDC User Agreement for Non-Members
Online Documentation: LDC2017S11 Documents
Licensing Instructions: Subscription & Standard Members, and Non-Members
Citation: Petukhova, Volha, et al. Metalogue Multi-Issue Bargaining Dialogue LDC2017S11. Web Download. Philadelphia: Linguistic Data Consortium, 2017.

Introduction

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.

Data

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.

All text is presented in UTF-8 as either plain text or XML.

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