Sentence examples for classification of voice from inspiring English sources

The classification of voice diseases has many applications in health, in diseases treatment, and in the design of new medical equipment for helping doctors in diagnosing pathologies related to the voice.

The proposed two-stage classifier is more accurate than the MFCC-based GMM and HOS methods alone and shows potential for the classification of voices in the clinic.

When testing the technique in a three-class classification problem of voice data, a statistically significant improvement in classification accuracy was obtained if compared to parallel committees.

In this paper, we propose a novel methodology for automatic pattern classification of pathological voices.

More examples of voice classification have been described in our previous work [ 1] which attempted to classify voice data by using hierarchical time-series clustering methods.

Inspired by the financial analysis of stock market, residual and volatility are firstly imported in the application field of voice classification.

The results showed that SFX is able to achieve a higher accuracy in the classification models for the four types of voice data.

The prosodic parameters were primarily determined from the F0 contour therefore, the voicing classification of the analyzed frame must be performed first.

The variation of a non-Gaussian signal which is produced by vibration of the vocal folds can be an important clue for the classification of pathological and normal voices.

For the classification of audio signals, we employ the standard method of voice activity detection based on the zero crossing rate (ZCR) and energy [25].

That shows the potential computational difficulty in classification between voices of different emotions.