Machine Learning Based Speech Separation

Project Type: Master/Diploma Thesis
Project Status: Open

Short Description

Assume a single-channel multiple (two) speaker recording. Speech separation for such tasks can be formulated as classification or regression problem in the time-frequency domain. Recently, we used deep neural networks to accomplish this task. One task of this thesis is to extend the system by additionally integrating a phase cue. The system is evaluated on available data using commonly used performance measures such as PESQ etc.


  • Extend the available prototype system; include a phase sensitive features.
  • Test the system on available data set.
  • Implement these models in Theano
  • Empirical Verification of these algorithms


Your Profile/Requirements

The candidate should be interested in machine learning, speech processing, and neural networks. Excellent programming skills in C++, python etc. are required. Interested candidates are encouraged to ask for further information. Additionally, the supervision of own projects in one of the above mention fields is possible.


Franz Pernkopf ( or 0316/873 4436) and Pejman Mowlaee