Automated Tools for Identifying Syllabic Landmark Clusters that Reflect Changes in Articulation (2011)

Suzanne Boyce, Harriet Fell, Lorin Wilde, Joel MacAuslan

We have developed a set of software tools to detect articulatory changes in the production of syllabic units based on acoustic landmark detection and classification. Results from the application of this automatic analysis system to studies of Parkinson’s Disease and Sleep Deprivation show the ability to detect subtle change. We are making these tools available as add-ons to systems such as Wavesurfer and R.

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