A Singing Voice/Music Separation Method Based on Non-negative Tensor Factorization and Repeat Pattern Extraction
In this paper, a novel singing voice/music separation method is proposed based on the non-negative tensor factorization (NTF) and repeat pattern extraction technique (REPET) to separate the mixture into an audio signal and a background music. Our system consists of three stages. Firstly, we use the NTF to decompose the mixture into different components, and similarity detection is applied to distinguish the components from each other, in order to classify the components into two classes as the voice including voice/periodic music and the block music/voice; next we utilize the REPET to extract the background music one step further for the two classes, and the final background music is estimated by adding the two backgrounds together, the left is added together as the singing voice; finally the music spectrum and the voice spectrum are filtered by harmonic filter and percussive filter respectively. To improve the performance further, wiener filter is used to separate the voice and music. Our method can improve the separation performance compared with the other state-of-the-art methods on the MIR-1K dataset.
KeywordsNTF REPET Source Separation Median Filter Unsupervised Signal Processing
Unable to display preview. Download preview PDF.
- 2.Diamantaras, K.I., Papadimitriou, T.: Blind separation of three binary sources from one nonlinear mixture. Machine Learning for Signal Processing (2010)Google Scholar
- 3.Diamantaras, K.I., Papadimitriou, T., Vranou, G.: Blind separation of multiple binary sources from one nonlinear Mixture. In: IEEE International Conference on Acoustics, Speech and Signal Processing (2011)Google Scholar
- 4.Diamantaras, K.I., Papadimitriou, T.: Separating two binary sources from a single nonlinear mixture. In: IEEE International Conference on Acoustics Speech and Signal Processing (2010)Google Scholar
- 6.Song, J., Ma, X., Zhang, Y.: Binary source separation layer by layer for one sensor. In: IEEE International Conference on Intelligent Control and Information Processing (2014)Google Scholar
- 7.Wang, C.K., Lyu, R.Y., Chiang, Y.C.: An automatic singing transcription system with multilingual singing lyric recognizer and robust melody tracker. In: European Conference on Speech Communication and Technology (2003)Google Scholar
- 9.Zhang, T.: System and method for automatic singer identification. Research Disclosure (2003)Google Scholar
- 11.Rafii, Z., Pardo, B.: Music/Voice Separation Using the Similarity Matrix. In: ISMIR (2012)Google Scholar
- 16.Huang, P.-S., Chen, S.D., Smaragdis, P., Hasegawa-Johnson, M.: Singing-voice separation from monaural recordings using robust principal component analysis. In: IEEE International Conference on Acoustics, Speech and Signal Processing (2012)Google Scholar
- 17.Fitzgerald, D.: Harmonic/percussive separation using median filtering. In: 13th International Conference on Digital Audio Effects (2010)Google Scholar
- 18.Rafii, Z., Germain, F., Sun, D.L.: Combining Modeling of Singing Voice and Background Music For Automatic Separation of Musical Mixtures. In: ISMIR (2013)Google Scholar
- 20.BSS Eval toolbox, http://bass-db.gforge.inria.fr/bss_eval/
<SimplePara><Emphasis Type="Bold">Open Access</Emphasis> This chapter is licensed under the terms of the Creative Commons Attribution-NonCommercial 2.5 International License (http://creativecommons.org/licenses/by-nc/2.5/), which permits any noncommercial use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license and indicate if changes were made. </SimplePara> <SimplePara>The images or other third party material in this chapter are included in the chapter's Creative Commons license, unless indicated otherwise in a credit line to the material. If material is not included in the chapter's Creative Commons license and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder.</SimplePara>