Detection of abrupt changes: theory and application
Detection of abrupt changes: theory and application
Estimation of Boundaries between Speech Units Using Bayesian Changepoint Detectors
TSD '01 Proceedings of the 4th International Conference on Text, Speech and Dialogue
Improved detection of boundaries of phonemes in speech databases
BIEN '07 Proceedings of the fifth IASTED International Conference: biomedical engineering
PEAKS - A system for the automatic evaluation of voice and speech disorders
Speech Communication
Characterization of healthy and pathological voice through measures based on nonlinear dynamics
IEEE Transactions on Audio, Speech, and Language Processing
Opensmile: the munich versatile and fast open-source audio feature extractor
Proceedings of the international conference on Multimedia
Classification of Speech Dysfluencies Using LPC Based Parameterization Techniques
Journal of Medical Systems
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The accurate changepoint detection of different signal segments is a frequent challenge in a wide range of applications. With regard to speech utterances, the changepoints are related to significant spectral changes, mostly represented by the borders between two phonemes. The main aim of this study is to design a novel Bayesian autoregressive changepoint detector (BACD) and test its feasibility in the evaluation of fluency and articulatory disorders. The originality of the proposed method consists in its normalizing of a posteriori probability using Bayesian evidence and designing a recursive algorithm for reliable practice. For further evaluation of the BACD, we used data from (a) 118 people with various severity of stuttering to assess the extent of speech disfluency using a short reading passage, and (b) 24 patients with early Parkinson's disease and 22 healthy speakers for evaluation of articulation accuracy using fast syllable repetition. Subsequently, we designed two measures for each type of disorder. While speech disfluency has been related to greater distances between spectral changes, inaccurate dysarthric articulation has instead been associated with lower spectral changes. These findings have been confirmed by statistically significant differences, which were achieved in separating several degrees of disfluency and distinguishing healthy from parkinsonian speakers. In addition, a significant correlation was found between the automatic assessment of speech fluency and the judgment of human experts. In conclusion, the method proposed provides a cost-effective, easily applicable and freely available evaluation of speech disorders, as well as other areas requiring reliable techniques for changepoint detection. In a more modest scope, BACD may be used in diagnosis of disease severity, monitoring treatment, and support for therapist evaluation.