A novel MIR approach based on dynamic thresholds segmentation and weighted synthesis matching

In the pattern recognition field, MIR is receiving more and more attention. To improve the accuracy of MIR system, a novel automatic algorithm based on dynamic thresholds note segmentation and weighted synthesis matching is presented. First dynamic steps are set for amplitude difference, get dynamic thresholds to segment notes and improve segmentation veracity. Then music scores are transformed into frequency templates by standard frequency and the input signal pitch is normalized to enhance the accuracy. To improve the adaptability and the robustness, traditional approximate string matching algorithm and DTW (Dynamic Time Warping) algorithm are synthesized. At last, the simulation results are provided to show the validity of the algorithm.