English (United Kingdom)

https://curated-unify.zendy.io/wp-json/zendy-region/v1/featured_content/oa?rat=en

https://curated-unify.zendy.io/wp-json/zendy-region/v1/highlighted_journal/

Global: Zendy Plus annual

Presents the access of premium content as premium feature

Premium Content

Presents the keyphrase highlighting as premium feature

Keyphrase Highlighting

Presents the summarisation as premium feature

Summarisation

Insights

Presents the pdf analysis as premium feature

PDF Analysis

Presents the zaia usage as premium feature

ZAIA

Global: Zendy Tools annual

Global: Zendy Free Plan

Global: Zendy Tools monthly

Global: Zendy Plus monthly

XinTianYou, a folk song style from Shannxi province in China, is considered to be a precious traditional culture heritage. Research about XinTianYou is important to the overall Chinese folk music theory and is potentially quite useful for the culture preservation and applications. In this paper, we analyze the general characteristics of XinTianYou by using the pitch, rhythm features and the combination of these two features. First, we use the Gaussian Mixture Model (GMM) to cluster the XinTianYou audio based on pitch and rhythm respectively, and analyze the general characteristics of XinTianYou based on the clustering result. Second, we propose an improved Features Relative Contribution Algorithm (CFRCA) to com-pare the contributions of pitch and rhythm. Third, the probability of a song being XinTianYou can be estimated based on the GMM and the cosine similarity distance. The experimental results show that XinTianYou has large pitch span and large proportion of high pitch value (about 22%). Regarding the rhythm, we find that moderato is dominated while lento-moderato keep a similar ratio as moderato-allegro. The similarity between pitch features of all XinTianYou songs is more significant than rhythm features. Additionally, the average accuracy of XinTianYou recognition reaches 92.4% based on our metho

Based on Gaussian Mixture Model to Explore the General Characteristic and Make Recognition of XinTianYou