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This spoken dialogue corpus contains interactions captured from the CMU Let's Go (LG) System by Carnegie Mellon University in 2006 and 2007. It is based on raw log-files from the LG system.
The corpus has been parameterized and annotated by the Dialogue Systems Group at Ulm University, Germany.
See license.txt for legal issues.
To cite the corpus, please use the following two publications: [Schmitt2012] A. Schmitt, S. Ultes and W. Minker A Parameterized and Annotated Spoken Dialog Corpus of the CMU Let's Go Bus Information System International Conference on Language Resources and Evaluation (LREC), Istanbul, Turkey, pp. 3369--3373, May 2012
[Ultes2015] S. Ultes, A. Schmitt, M. J. Platero Sánchez and W. Minker Analysis of an Extended Interaction Quality Corpus International Workshop On Spoken Dialogue Systems (IWSDS), Busan, Korea, January 2015 submitted
References:
[Esenazi2008] Maxine Eskenazi, Alan W Black, Antoine Raux, and Brian Langner Let’s Go Lab: a platform for evaluation of spoken dialog systems with real world users in: Proceedings of Interspeech 2008 Conference, Brisbane, Australia
[Schmitt2011] Alexander Schmitt, Benjamin Schatz and Wolfgang Minker, MODELING AND PREDICTING QUALITY IN SPOKEN HUMAN-COMPUTER INTERACTION, in: Proceedings of the SIGDIAL 2011 Conference, Association for Computational Linguistics, 2011
[Schmitt2009] A. Schmitt, T. Heinroth and J. Liscombe On NoMatchs, NoInputs and BargeIns: Do Non-Acoustic Features Support Anger Detection? Proceedings of the SIGDIAL 2009 Conference, Association for Computational Linguistics, London, UK, pp. 128--131, 2009
license.txt -> license file
readme.md -> this file
interaction_parameters.pdf -> Description of interaction parameters
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|---- audio -> wav files with user utterances and full recordings
|
|---- corpus
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|---- csv -> CSV-files with interactions.csv, acoustics.csv and calls.csv
|---- mysql -> mysql dump
The corpus comes with both, MySQL-database dumps and CSV files.
The mysql-dump can be imported right away in any MySQL database. CSV files can be imported e.g. in Excel, Matlab, R, Weka, SPSS and other SQL databases than mysql.
interactions.csv/interactions-Table: each line contains a system-user exchange, parameterized with 53 interaction parameters
Prompt, Utterance, ASRRecognitionStatus, #ASRSuccess, (#)ASRSuccess, %ASRSuccess, #TimeOutPrompts, (#)TimeOutPrompts, %TimeOutPrompts, #ASRRejections, (#)ASRRejections, %ASRRejections, #TimeOuts_ASRRej, (#)TimeOuts_ASRRej, %TimeOuts_ASRRej, Barged-In?, #Barge-Ins, (#)Barge-Ins, %Barge-Ins, ASRConfidence, MeanASRConfidence, (Mean)ASRConfidence, UTD, ExMo, Modality, UnExMo?, #UnExMo, (#)UnExMo, %UnExMo, WPUT, WPST, SemanticParse, HelpRequest?, #HelpRequests, (#)HelpRequest, %HelpRequest, Activity, ActivityType, DD, RoleIndex, RoleName, RePrompt?, #RePrompts, (#)RePrompts, %RePrompts, LoopName, #Exchanges, #SystemTurns, #UserTurns, #SystemQuestions, (#)SystemQuestions, SystemDialogueAct, UserDialogueAct
as described by [Schmitt et al., 2011]
Use callid to join with call-Table
Furthermore, the file contains EmotionalState annotations and Interaction Quality annotations, see below. For interaction quality please refer to [Schmitt et al., 2011]
calls.csv/calls-Table: each line contains information affecting the entire call. Primary key: callid
The file contains gender, age and dialogue outcome annotations that can be used as target variable to predict task completion.
acoustics.csv/acoustics-Table: each line contains basic acoustic and prosodic features extracted on the full utterance. Extraction has been done with the Praat software; see [Schmitt2009] for details.
Number of Calls with IQ Annotations from all Raters: 401 Number of Exchanges with IQ Annotations from all Raters: 9,638
Annotation Scheme:
Number of Calls with Emotion Annotations: 302Number of Raters for Emotion Annotation: 1
Annotation Scheme: friendly, neutral, slightly angry, angry, very angry
Check this dataset in Dagshub
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