Speaker Diarization and Recognition for RadioPlays with SpeechBrain
- Master Thesis
- Announcement date
- 13 Aug 2021
- Research Areas
Radio plays have long been analyzed in literature studies based soley on the written author script. This has change recently to analyzing the interpretation of the play. Speech technology can provide tools for literature scientists to automatically transcribe the audio recording and do further analysis to gain insight into the character of the play. The aim of this thesis is to do speech diarization (i.e. who spoke when) for later recognition of the the spoken text.
SpeechBrain is a new speech recognition framework that was released in 2021. It is written in Python and uses PyTorch as its machine learning backend.
- Implementation of the speaker diarization and recognition for radioplays with SpeechBrain (Python).
- Detailed evaluation of the algorithm(s).
- Motivation and interest in the topic.
- Solid Background in Speech Processing, ideally you completed some of our speech communication courses
- Experience with either Python.
Martin Hagmüller (firstname.lastname@example.org or 0316-873 4377)