Development and Evaluation of an Intelligent System for Calibrating Karaoke Lyrics Based on Fuzzy Petri Nets

In the home entertainment system, karaoke is a popular leisure facility in our daily life. Via the karaoke system, users can sing along with the lyrics based on the recordings of pop songs. However, a lot of karaoke systems can display lyrics semi-automatically. Traditionally, some lyrics are input manually and need to be synchronized with the tonal music stepwise, which is time-consuming. One of the famous musical phrase segmentation theories is a generative theory of tonal music, through which we have implemented a karaoke system in C# programming language. This intelligent system can automatically segment music phrases and use a high-level fuzzy Petri net model to calibrate the lyrics in pop songs. Fifty Chinese pop songs are selected to evaluate its performance. The experimental results have shown that the average calibration precision value (92.78%) and recall value (90.46%) are highly acceptable.