@article{(Open Science Index):https://publications.waset.org/pdf/10006407, title = {An Approach for Vocal Register Recognition Based on Spectral Analysis of Singing}, author = {Aleksandra Zysk and Pawel Badura}, country = {}, institution = {}, abstract = {Recognizing and controlling vocal registers during singing is a difficult task for beginner vocalist. It requires among others identifying which part of natural resonators is being used when a sound propagates through the body. Thus, an application has been designed allowing for sound recording, automatic vocal register recognition (VRR), and a graphical user interface providing real-time visualization of the signal and recognition results. Six spectral features are determined for each time frame and passed to the support vector machine classifier yielding a binary decision on the head or chest register assignment of the segment. The classification training and testing data have been recorded by ten professional female singers (soprano, aged 19-29) performing sounds for both chest and head register. The classification accuracy exceeded 93% in each of various validation schemes. Apart from a hard two-class clustering, the support vector classifier returns also information on the distance between particular feature vector and the discrimination hyperplane in a feature space. Such an information reflects the level of certainty of the vocal register classification in a fuzzy way. Thus, the designed recognition and training application is able to assess and visualize the continuous trend in singing in a user-friendly graphical mode providing an easy way to control the vocal emission.}, journal = {International Journal of Cognitive and Language Sciences}, volume = {11}, number = {2}, year = {2017}, pages = {207 - 212}, ee = {https://publications.waset.org/pdf/10006407}, url = {https://publications.waset.org/vol/122}, bibsource = {https://publications.waset.org/}, issn = {eISSN: 1307-6892}, publisher = {World Academy of Science, Engineering and Technology}, index = {Open Science Index 122, 2017}, }