TU Berlin

Quality and Usability LabRafael Zequeira Jiménez

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Rafael Zequeira Jiménez

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Research Topics

  • Speech Quality Assessment in Crowdsourcing  

 

Research Group

Next Generation Crowdsourcing

 

Biography

Rafael Zequeira Jiménez received a degree as Telecommunication Engineer (equivalent to Master of Science) from the University of Granada, Spain in 2014.

From 2013 to 2014 he studied at Technische Universität Berlin within the Erasmus program. At this time, he worked on his Master Thesis entitled: “Secure multi protocol system based on a Resource Model for the IoT and M2M services”. In December 2013, Rafael joined the SNET department of the Deutsche Telekom Innovation Laboratories (T-Labs), where he worked during 10 months as a student research assistant in the TRESOR project. In which he focused on designing and implementing REST APIs to communicate different components.

In June 2015 Rafael joined the Quality and Usability Lab department lead by Prof. Dr.-Ing. Sebastian Möller, to work as Research Assistant in the “Next Generation Crowdsourcing” group, specifically in the Crowdee project. Since 2016, he works towards his PhD in the topic: “Analysis of Crowdsourcing Micro-Tasks for Speech Quality Assessment”.

 

 

Contact

Twitter: @zequeiraj

e-mail:

 

 

Address

Quality and Usability Lab
TU Berlin
Ernst-Reuter-Platz 7
D-10587 Berlin, Germany

Tel:  +4930835358336​

Publications

Background Environment Characteristics of Crowd-Workers from German Speaking Countries Experimental Survey on User Environment Characteristics
Zitatschlüssel zequeirajimenez2019b
Autor Zequeira Jiménez, Rafael and Naderi, Babak and Möller, Sebastian
Buchtitel 2019 Eleventh International Conference on Quality of Multimedia Experience (QoMEX)
Seiten 1–3
Jahr 2019
ISSN 2372-7179
DOI 10.1109/QoMEX.2019.8743208
Monat jun
Verlag IEEE
Serie QoMEX 2019
Wie herausgegeben Poster
Zusammenfassung Crowdsourcing has been used extensively for gathering and annotating data cost efficiently. Nowadays, there are multiple platforms offering crowd-sourced workforce, still most of these users are from Asia or English speaking countries, and not so many native German speakers. Thus, there is a lack of information regarding the conditions in which German users execute tasks, neither about their habits when taking part in crowdsourcing campaigns. Which is of main importance to address properly user studies to German crowd-workers. This paper reports on a survey that investigated the environments' characteristics of users from German speaking countries. To this end, a study has been conducted in which users were asked to provide details about the surroundings in which they normally execute crowdsourcing tasks. Audio and visual data was collected per user which contributed to aggregate even more information on the users' input. We provide insights aimed at easing the decision making process when designing subjective user studies.
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