Voice pathology detection based eon short-term jitter estimations in running speech.

In this paper, we investigate the use of jitter estimation over short time intervals (short-term jitter) for voice pathology detection in the case of running or continuous speech. Short-term jitter estimations are provided by the spectral jitter estimator (SJE), which is based on a mathematical description of the jitter phenomenon. The SJE has been shown to be robust against errors in pitch period estimations, which makes it a good candidate for measuring jitter in continuous speech. On two large databases of sustained vowel recordings from healthy and pathological voices, we suggest a threshold for the SJE for pathology detection based on cross-database validation. Applying that to a database of continuous speech (reading text) from normophonic and dysphonic speakers, a second threshold and new features are suggested for monitoring jitter in continuous speech. Detection performance of the suggested thresholds and features was evaluated using receiver operating characteristic curves and their discriminative efficiency between healthy and pathological voices was judged using the area under the curve index. In terms of area under the curve, the suggested features for reading text provide a discrimination score of about 95%, while the second threshold provides a classification rate of 87.8%. Furthermore, estimated short-term jitter values from reading text were found to confirm the studies showing a decrease of jitter with increasing fundamental frequencies, and the more frequent presence of high jitter values in the case of pathological voices as time increases.