Past research on the speech of apnoea patients has revealed that resonance anomalies are among the most distinguishing traits for these speakers. This paper presents an approach to characterize these peculiarities using GMMs and distance measures between distributions. We report the findings obtained with two analytical procedures, working with a purpose-designed speech database of both healthy and apnoea-suffering patients. First, we validate the database to guarantee that the models trained are able to describe the acoustic space in a way that may reveal differences between groups. Then we study abnormal nasalization in apnoea patients by considering vowels in nasal and non-nasal phonetic contexts. Our results confirm that there are differences between the groups, and that statistical modelling techniques can be used to describe this factor. Results further suggest that it would be possible to design an automatic classifier using such discriminative information.
Bibliographic reference. Blanco, José Luis / Fernández, Rubén / Pardo, David / Sigüenza, Álvaro / Hernández, Luis A. / Alcázar, José (2009): "Analyzing GMMs to characterize resonance anomalies in speakers suffering from apnoea", In INTERSPEECH-2009, 1459-1462.