ITS8040 - Natural Language and Speech Processing
We offer supervision of Master theses on topics that are related to our research.
Here is a selection of already supervised theses:
- Jörgen Valk, Tanel Alumäe (sup). Using Web Scraping for Building Spoken Language Identification Models. 2020.
- Hendrik Kivi, Tanel Alumäe (sup). Identification and Localization of Foreign Accent in Speech. 2020.
- Aivo Olev, Tanel Alumäe (sup). Web Application for Authoring Speech Transcriptions. 2019.
- Siim Kaspar Uustalu, Tanel Alumäe (sup). Automated Detection and Sentiment Analysis of Registered Entity Mentions in Estonian Language News Media. 2019. Nominated as one of the best MSc theses of the School of IT.
- Siim Talts, Tanel Alumäe (sup). Analysing Election Candidate Exposure in Broadcast Media Using Weakly Supervised Training. 2019.
- Leo Kristopher Piel, Tanel Alumäe (sup). Speech-based Identification of Children's Gender and Age with Neural Networks. 2018. Nominated as one of the best MSc theses of the School of IT.
- Margus Baumann, Tanel Alumäe (sup). Identification of Foreign Language Accent from Speech Using Neural Networks. 2018.
- Martin Talimets, Tanel Alumäe (sup). End-to-End Speech Recognition for Estonian. 2018.
- Martin Väljaots, Einar Meister (sup). Computer Aided Pronunciation Training Tool for Estonian. 2018.
- Roman Hrushchak, Einar Meister (sup). Visualization of Tongue and Lip Movements. 2018.
- Evgeniia Rykova, Einar Meister (sup). Perceptual and acoustic similarities between the voices of family members: an approach to synthesize a voice based on family-shared F0 characteristics. 2018.
- Thales Santos Ribeiro, Einar Meister (sup). Online Recording of Speech Corpora. 2018.
- Lasha Amashukeli, Einar Meister (sup). Online Perception Experiments. 2018
- Martin Karu, Tanel Alumäe (sup). Weakly Supervised Training of Speaker Identification Models. 2017. Best MSc thesis of the School of IT.
We are looking for talented and hardworking people to do their doctoral studies on topics that are related to our research.
All PhD students at our lab become a member of our team. You will be hired as an Early Stage Researcher, and will get a salary from the university, in addition to the doctoral scholarship. The full compensation depends on the person (better skills and better research output result in better salary), but the minimum is 1500 EUR (after taxes). This is actually about 25% more than the avarage salary in Estonia. Living costs in Estonia are significantly lower than in Western European countries.
We can admit new PhD students any time.
The proposed topics are described below. However, other topics in the field of speech recognition and speaker recognition are also possible (the exact topic can be determined based on the student and her/his interests and skills).
- Interest in scientific reasearch (and understanding about what reasearch is)
- Masters degree in computer science (or a related field)
- Good background in mathematics, statistics, probability theory and linear algebra
- Good background in some subfield of speech technology (e.g., speech recogniton, speaker recogniton)
- Knowledge of modern approaches in machine learning (incl. deep learning)
- Excellent programming skills (Python, C++, bash scripting)
- Experience with modern deep learning toolkits (Pytorch, Tensorflow)
- Excellent academic writing skills
- Some experience with the speech recognition toolkit Kaldi is a plus
- Previous academic or industry experience in speech or language processing is beneficial (but not strictly needed)
We have currently two open PhD positions:
Current PhD Students
- Martiv Verrev, supervisor Tanel Alumäe and Tanel Tammet. Knowledge extraction from natural language using both machine learning and common sense knowledge systems.
- Andrus Paats, supervisor Einar Meister and Ivo Fridolin. Development and implementation of voice recognition system in medicine for radiology.
Graduated Phd Students