Quantifying how the spectral content of speech relates to changes in mental state may be crucial in building an objective speech-based depression classification system with clinical utility. This paper investigates the hypothesis that important depression based information can be captured within the covariance structure of a Gaussian Mixture Model (GMM) of recorded speech. Significant negative correlations found between a speaker’s average weighted variance - a GMM-based indicator of speaker variability - and their level of depression support this hypothesis. Further evidence is provided by the comparison of classification accuracies from seven different GMM-UBM systems, each formed by varying different parameter combinations during MAP adaption. This analysis shows that variance-only adaptation either outperforms or matches the de facto standard mean-only adaptation when classifying both the presence and severity of depression. This result is perhaps the first of its kind seen in GMM-UBM speech classification.
|Title of host publication||14th Annual Conference of the International Speech Communication Association (INTERSPEECH 2013): Speech in Life Sciences and Human Societies|
|Editors||Frederic Bimbot, Cecile Fougeron, Francois Pellegrino|
|Place of Publication||Lyon, France|
|Publisher||International Speech Communication Association|
|Number of pages||5|
|Publication status||Published - 2013|
|Event||14th Annual Conference of the International Speech Communication Association Interspeech 2013 - Lyon, Lyon, France|
Duration: 25 Aug 2013 → 29 Aug 2013
|Conference||14th Annual Conference of the International Speech Communication Association Interspeech 2013|
|Abbreviated title||INTERSPEECH 2013|
|Period||25/08/13 → 29/08/13|
Cummins, N., Epps, J., Sethu, V., Breakspear, M., & GOECKE, R. (2013). Modeling Spectral Variability for the Classification of Depressed Speech. In F. Bimbot, C. Fougeron, & F. Pellegrino (Eds.), 14th Annual Conference of the International Speech Communication Association (INTERSPEECH 2013): Speech in Life Sciences and Human Societies (Vol. 2, pp. 857-861). Lyon, France: International Speech Communication Association.