Project 11: Lexical decoding of speech using sub-phonemic features
New: Michele Gubian’s website containing information and tutorials on Functional Data Analysis
This project addresses the lexical coding and decoding of FPD by means of probabilistic subphonemic feature representations that are automatically derived from the speech signal. Subphonemic feature vectors for each 10 millisecond interval in the unfolding speech signal provide an excellent window on the fine phonetic detail across many acoustic and articulatory dimensions. The main aim is to improve computational modelling of HSP by using key techniques from ASR. The starting point will be existing models of ASR and HSP, such as the conventional HMM-based ASR models (Nijmegen), exemplar-based models (Leuven & Sheffield), and the ASR-based model of HSP called SpeM (Nijmegen).
Working on this project: » Dr Louis ten Bosch » Dr Helmer Strik » Prof Roger Moore » Dr Odette Scharenborg » Dr Michele Gubian
