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TU Berlin

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Dr. Tim Polzehl

Crowdsourcing Technology

  • High-quality data collection via crowdsourcing
  • Data management and data services via crowdsourcing (clean, index, verify, tag, label, translate, summarize, join, etc. )
  • Data synthesis und data generation via crowdsourcing
  • Subjective influences and bias normalization in crowdsourcing
  • Crowd-creation, crowd-voting, crowd-storming, crowd-testing applications
  • Crowdsourcing service for machine learning and BI
  • Crowdsourcing business and Business Logic
  • Complex automated workflows: combining human and artificial intelligence
  • Crowdsourcing with mobile devices
  • Real-time crowdsourcing
  • Skill-based crowdsourcing and verification of crowd-experts


Speech Technology

  • Automatic user classification
  • Automatic speaker characterization (age, gender, emotion, personality) 
  • Automatic speech recognition (ASR),
  • Prosody and voice gesture recognition
  • Prosodic voice print analysis, phonetic science
  • App development with speech functionalities (Android, iOS)


Text Classification, Natural Language Processing (NLP)  

  • Sentiment Analysis
  • Affective Analysis, Emotion
  • Personality und Lifestyle Detection from Social-Networks (Twitter, FB, G+, etc.)


Machine Learning and Artificial Intelligence  

  • Automated user modelling
  • Classification and prediction systems using linear and non-linear algorithms
  • Feature selection and reduction
  • Evaluation and verification methods


Running and Past Projects:

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Project Biography 

Tim Polzehl studied Science of Communication at Berlin's Technical University. Combining linguistic knowledge with signal processing skills he focused on speech interpretation and automatic data- and metadata extraction. He gathered experience within the field of machine learning as exercised when recognizing human speech utterances and classifying emotional expression subliminal in speech, the latter of which became his M.A. thesis. 

In 2008 Tim Polzehl started his position as PhD candidate in Telekom Innovation Laboratories (T-Labs) and the Quality and Usability Lab. He worked in both industrial and academic projects with focus on speech technology, App-Development, machine learning crowd sourcing solutions.

2011-2013 Tim was leading a R&D Project for Telekom Innovation Laboratories with Applications in the field of Intelligent Customer-Care Systems and Speech-Apps.

2012-2014 Tim was awarded with an BMBF funded Education program for future IT and Development Leadership involving SAP, Software AG, Scheer Group, Siemens, Holtzbrinck, Bosch, Datev and Deutsche Telekom AG, amongst highly ranked academic institution (Softwarecampus).       

2014 Tim was awarded the PhD for his work on automatic prediction of personality attributes from speech.

Since 2014 Tim has been working as a Postdoc at the Quality and Usability chair of TU-Berlin. At the same time Tim is driving the start-up activity applying the earlier  development of crowdsourcing solutions Crowdee.



Quality and Usability Labs

Technische Universität Berlin

Ernst-Reuter-Platz 7

D-10587 Berlin

Tel.:+49 (30) 8353-58227Fax: +49 (30) 8353-58409

Openings / Supervision

please refer to here.


Iskender, Neslihan and Polzehl, Tim (2021). An Empirical Analysis of an Internal Crowdsourcing Platform: IT Implications for Improving Employee Participation. Internal Crowdsourcing in Companies: Theoretical Foundations and Practical Applications. Springer International Publishing, 103–134.

Link to publication Link to original publication

Möller, Sebastian and Hinterleitner, Florian and Falk, Tiago H. and Polzehl, Tim (2010). Comparison of Approaches for Instrumentally Predicting the Quality of Text-To-Speech Systems. Proceedings of the 11th Annual Conference of the ISCA (Interspeech 2010). International Speech Communication Association (ISCA), 1–6.

Link to publication Link to original publication

Iskender, Neslihan and Polzehl, Tim and Möller, Sebastian (2021). Reliability of Human Evaluation for Text Summarization: Lessons Learned and Challenges Ahead. Proceedings of the Workshop on Human Evaluation of NLP Systems. Association for Computational Linguistics, 86–96.

Link to publication Link to original publication

Iskender, Neslihan and Polzehl, Tim and Möller, Sebastian (2021). Towards Hybrid Human-Machine Workflow for Natural Language Generation. Proceedings of the First Workshop on Bridging Human–Computer Interaction and Natural Language Processing. Association for Computational Linguistics, 1–7.

Link to publication Link to original publication

Wedel, Marco and Ulbrich, Hannah and Pohlisch, Jakob and Göll, Edgar and Uhl, André and Iskender, Neslihan and Polzehl, Tim and Schröter, Welf and Porth, Florian (2021). Internes Crowdsourcing in Unternehmen. Arbeit in der digitalisierten Welt: Praxisbeispiele und Gestaltungslösungen aus dem BMBF-Förderschwerpunkt. Springer Berlin Heidelberg, 335–349.

Link to publication Link to original publication

Black, Alan and Bunnell, H Timothy and Dou, Ying and Muthukumar, Prasanna Kumar and Perry, Daniel and Polzehl, Tim and Prahallad, Kishore and Vaughn, Callie and Steidl, S. (2012). ARTICULATORY FEATURES FOR EXPRESSIVE SPEECH SYNTHESIS. In Proc. ICASSP 2012. IEEE.

Link to original publication

Polzehl, Tim and Metze, F. and Schmitt, A. (2010). Linguistic and Prosodic Emotion Recognition. Deutsche Jahrestagung für Akustik (DAGA). DAGA, 1–2.

Polzehl, Tim and Möller, Sebastian and Metze, Florian (2010). Automatically Assessing Personality from Speech. Proc. of International Conference on Semantic Computing (ICSC 2010). IEEE, 1–6.

Polzehl, Tim and Möller, Sebastian and Metze, Florian (2010). Automatically Assessing Acoustic Manifestations of Personality in Speech. Workshop on Spoken Language Technology (SLT). IEEE, 1–6.

Link to publication

Polzehl, Tim and Schmitt, A. and Metze, F. (2010). Salient Features for Anger Recognition in German and English IVR Portals. Spoken Dialogue Systems Technology and Design. Springer, 81–110.

Polzehl, Tim and Schmitt, A. and Metze, F. (2010). Approaching Multi-Lingual Emotion Recognition from Speech - On Language Dependency of Acoustic/Prosodic Features for Anger Detection. SpeechProsody. University of Illionois, 1–6.

Polzehl, Tim (2006). Automatische Klassifizierung Emotionaler Sprechweisen. Tagungsband 1.Kongress Multimediatechnik

Burkhardt, Felix and Ballegooy, Markus van and Engelbrecht, Klaus-Peter and Polzehl, Tim and Stegmann, Joachim (2009). Emotion Detection in Dialog Systems: Applications, Strategies and Challenges. Proc. of International Conference on Affective Computing and Intelligent Interaction (ACII 2009). IEEE.

Link to original publication

Burkhardt, Felix and Polzehl, Tim and Stegmann, Joachim and Metze, Florian and Huber, Richard (2009). Detecting Real Life Anger. Proc. of International Conference on Acoustics, Speech, and Signal Processing (ICASSP 2009). IEEE, 4761–4764.

Schmitt, A. and Pieraccini, R. and Polzehl, Tim (2010). ``For Heaven's Sake, Gimme a Live Person!'' Designing Emotion-Detection Customer Care Voice Applications in Automated Call Centers. Advances in Speech Recognition. Springer US, 81–110.

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