Humming type music retrieval method and system based on note modeling

Abstract

The invention belongs to the technical field of computer application and provides a humming type music retrieval method and system based on note modeling. According to the humming type music retrieval method and system based on note modeling, modeling and parameter training are conducted on standard notes according to the Gaussian hybrid model technology, similarity calculation is conducted between a note resolved from a humming voice and a duration time sequence of the note and the standard notes of all key melodies in a base and the duration time sequences of the standard notes, and an optimal result is obtained. The humming type music retrieval method and system based on note modeling have the outstanding advantages that adding of new models and parameter training do not need to be conducted when new songs are added into a song library, and the popularization and application prospect is broad.

Description

technical field [0001] The invention belongs to the field of computer application technology, and in particular relates to a humming music retrieval method and system based on musical note modeling. Singing melody recognition. Background technique [0002] In recent years, the rapid rise of cloud computing and intelligent embedded software and hardware technology has further promoted the development of digital entertainment applications, and music entertainment services are increasingly approaching people's lives. On the one hand, using technologies such as virtualization and cloud storage on the cloud computing platform can establish a song library, deploy a music service system, and provide high-performance music search and download services on the Internet and mobile networks. On the other hand, the rapid development of embedded microprocessors such as ARM, OMAP, PXA, and Adreno, and the introduction of embedded operating systems such as Android, iOS, and Windows phone8 ...

AI Technical Summary

Problems solved by technology

The template matching dynamic programming algorithm represented by DTW can effectively solve the matching problem caused by the different lengths of humming songs and standard templates, and the engineering implementation is relatively simple. However, the disadvantage is that algorithms such as DTW need to use no error The standard song templates, the parameters of these templates are extracted in advance through MIDI original music or professional-level song corpus, and the recognition is matched with the voice of people humming

The disadvantage is that this method needs to add a melody model and sample training for new songs. In engineering, it needs to maintain the model parameter library. It is easy to implement music retrieval services on the Internet, but the application in embedded systems are greatly restricted

[0006] One of the characteristics of the HMM melody modeling method is that there is no requirement for the user's singing level, and it is easy for most people to use. However, when new songs are added to the song collection, it needs to be collected and trained to create a corresponding melody model in order to maintain a good performance. The recognition effect brings the workload of maintaining the model parameter library, which will bring inconvenience to the application work

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