direkt zum Inhalt springen

direkt zum Hauptnavigationsmenü

Sie sind hier

TU Berlin

Page Content

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

<< previous [6]

2009

Metze, Florian and Polzehl, Tim and Wagner, Michael (2009). Fusion of Acoustic and Linguistic Speech Features for Emotion Detection [13]. Proc. of International Conference on Semantic Computing (ICSC 2009). IEEE.


Polzehl, Tim and Schmitt, alexander and Metze, Florian (2009). Comparing Features for Acoustic Anger Classification in German and English IVR Systems [14]. Proc. of International Workshop of Spoken Dialogue Systems (IWSDS 2009). University of Ulm.


Polzehl, Tim and Sundaram, Shiva and Ketabdar, Hamed and Wagner, Michael and Metze, Florian (2009). Emotion Classification in Children's Speech Using Fusion of Acoustic and Linguistic Features [15]. Proceedings of the Annual Conference of the International Speech Communication Association (Interspeech 2009). ISCA, 340–343.


Schuller, B. and Metze, F. and Steidl, S. and Batliner, A. and Eyben, F. and Polzehl, Tim (2009). Late Fusion of Individual Engines for Imrpoved Recognition of Negative Emotion in Speech � Learning vs. Democratic Vote [16]. International Conference on Acoustics, Speech and Signal Processing (ICASSP). IEEE.


2008

Polzehl, Tim and Metze, Florian (2008). Using prosodic features to prioritize voice messages [17].


2006

Polzehl, Tim (2006). Automatische Klassifizierung Emotionaler Sprechweisen [18]. Tagungsband 1.Kongress Multimediatechnik


<< previous [19]
------ Links: ------

Zusatzinformationen / Extras

Quick Access:

Schnellnavigation zur Seite über Nummerneingabe

Auxiliary Functions

Copyright TU Berlin 2008