Research On Query-By-Humming Technology

Query by humming is an effective content-based music retrieval. It is a natural and convenient music retrieval method and it has great value in many application areas. Query by humming is a hot research topic at home and abroad in recent years. This paper studies the establishment of a database of MIDI, humming feature extraction and melody matching algorithm.In the establishment of the database, this paper used the MIDI format as data sources that music melody is extracted from. MIDI music theme extraction algorithm is used on the basis of MIDI music's format and verified by the experiment. Although the experimental results show that the performance of the algorithm can be, but in order to achieve the best results, the paper eventually choices the artificial monitor way and receives the theme's tracks of each first MIDI by manual tagging.In the Feature Extraction, a two-layer neural network for humming feature extraction is proposed for note segmentation and note recognition. The first-layer BP network is used to divide the humming data into the independent notes; the second-layer RBF network is used to receive the MIDI pitch of the independent note. The experimental results show that this method can extract the humming features with high accuracy, and it is suitable to the query by humming system.In the Melody matching algorithm, using the scalability of time and the translational of pitch in the notes sequence of the melody, first, two melodies are extended linearly to the same length in the time frame and aligns the notes whose onset are close in a certain time range. Then, the two melodies of same length are compared to the gap between the pitch at each time point, after the similarity of melody is studied in the rhythm. Finally, the paper gives the matching scores by considering the similarity both the rhythm and pitch and the pieces of the highest score will be retrieved as a result.