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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:

please click here.

 

 


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 [1].

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 [2]).       

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 [3].

 

Address:

Quality and Usability Labs

Technische Universität Berlin

Ernst-Reuter-Platz 7

D-10587 Berlin

Tel.:+49 (30) 8353-58227Fax: +49 (30) 8353-58409mailto:tim.polzehl@qu.tu-berlin.de [4]




Openings / Supervision

please refer to here [5].

Publications

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2010

Polzehl, Tim and Bunnell, Ht and Dou, Ying and Steidl, S. (2010). Emotion Identification for Evaluation of Synthesized Emotional Speech [14]. danieljamesperrycom, 3–6.

Link to original publication [15]

Polzehl, Tim and Metze, F. and Schmitt, A. (2010). Linguistic and Prosodic Emotion Recognition [16]. Deutsche Jahrestagung für Akustik (DAGA). DAGA, 1–2.


Polzehl, Tim and Möller, Sebastian and Metze, Florian (2010). Automatically Assessing Personality from Speech [17]. 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 [18]. Workshop on Spoken Language Technology (SLT). IEEE, 1–6.

Link to publication [19]

Polzehl, Tim and Schmitt, A. and Metze, F. (2010). Salient Features for Anger Recognition in German and English IVR Portals [20]. 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 [21]. SpeechProsody. University of Illionois, 1–6.


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 [22]. Advances in Speech Recognition. Springer US, 81–110.


Schmitt, A. and Polzehl, Tim and Minker, Wolfgang (2010). Modeling A-Priori Likelihoods for Angry User Turns with Hidden Markov Models [23]. SpeechProsody. University of Illionoise, 1–6.


Schmitt, A. and Polzehl, Tim and Minker, Wolfgang (2010). Facing Reality: Simulating Deployment of Anger - Recognition in IVR Systems [24]. Spoken Dialogue Systems for Ambient Environments - Lecture Notes in Computer Science. Springer, 23–48.


Schmitt, A. and Polzehl, Tim and Minker, Wolfgang and Liscombe, J. (2010). The Influence of the Utterance Length on the Recognition of Aged Voices [25]. Proceedings of the Seventh conference on International Language Resources and Evaluation (LREC'10). European Language Resources Association (ELRA), 1–6.


2009

Ketabdar, Hamed and Polzehl, Tim (2009). Fall and Emergency Detection with Mobile Phones [26]. Proceedings of the 11th International ACM SIGACCESS Conference on Computers and Accessibility (ASSETS'09). ACM New York, NY, USA textcopyright2009, 241–242.


Ketabdar, Hamed and Polzehl, Tim (2009). Tactile and Visual Alerts for Deaf People by Mobile Phones [27]. Proceedings of the 11th International ACM SIGACCESS Conference on Computers and Accessibility (ASSETS'09). ACM New York, NY, USA textcopyright2009, 253–254.


Ketabdar, Hamed and Polzehl, Tim (2009). Enhancing Security and Emergency Functionalities in Mobile Phones by Audio and Movement Analysis [28]. Proceedings of the 11th International Conference on Ubiquitous Computing (UBICOMP'09)


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 [29]. Proc. of International Conference on Affective Computing and Intelligent Interaction (ACII 2009). IEEE.

Link to original publication [30]

Burkhardt, Felix and Polzehl, Tim and Stegmann, Joachim and Metze, Florian and Huber, Richard (2009). Detecting Real Life Anger [31]. Proc. of International Conference on Acoustics, Speech, and Signal Processing (ICASSP 2009). IEEE, 4761–4764.


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