Summary of the paper
| Title | Speech Data Corpus for Verbal Intelligence Estimation |
|---|---|
| Authors | Kseniya Zablotskaya, Steffen Walter and Wolfgang Minker |
| Abstract | The goal of our research is the development of algorithms for automatic estimation of a person's verbal intelligence based on the analysis of transcribed spoken utterances. In this paper we present the corpus of German native speakers' monologues and dialogues about the same topics collected at the University of Ulm, Germany. The monologues were descriptions of two short films; the dialogues were discussions about problems of German education. The data corpus contains the verbal intelligence quotients of each speaker, which were measured with the Hamburg Wechsler Intelligence Test for Adults. In this paper we describe our corpus, why we decided to create it, and how it was collected. We also describe some approaches which can be applied to the transcribed spoken utterances for extraction of different features which could have a correlation with a person's verbal intelligence. The data corpus consists of 71 monologues and 30 dialogues (about 10 hours of audio data). |
| Topics | Corpus (creation, annotation, etc.), Information Extraction, Information Retrieval, Speech resource/database |
Full paper |
Speech Data Corpus for Verbal Intelligence Estimation |
Slides |
Speech Data Corpus for Verbal Intelligence Estimation |
| Bibtex | @InProceedings{ZABLOTSKAYA10.663, author = {Kseniya Zablotskaya and Steffen Walter and Wolfgang Minker}, title = {Speech Data Corpus for Verbal Intelligence Estimation}, booktitle = {Proceedings of the Seventh International Conference on Language Resources and Evaluation (LREC'10)}, year = {2010}, month = {may}, date = {19-21}, address = {Valletta, Malta}, editor = {Nicoletta Calzolari (Conference Chair) and Khalid Choukri and Bente Maegaard and Joseph Mariani and Jan Odijk and Stelios Piperidis and Mike Rosner and Daniel Tapias}, publisher = {European Language Resources Association (ELRA)}, isbn = {2-9517408-6-7}, language = {english} } |