COMBINING HMM-BASED MELODY EXTRACTION AND NMF-BASED SOFT MASKING FOR SEPARATING VOICE AND ACCOMPANIMENT FROM MONAURAL AUDIO
Acoustic Source Separation
Presented by: Yun Wang, Author(s): Yun Wang, Zhijian Ou, Tsinghua University, China
Modern monaural voice and accompaniment separation systems usually consist of two main modules: melody extraction and time-frequency masking. A main distinction between different separation systems lies in what approaches are used for the two modules. Popular techniques for melody extraction include hidden Markov models (HMMs) and non-negative matrix factorization (NMF), and masking includes hard and soft masking. This paper investigates the flaw of NMF-based melody extraction, and proposes the combination of HMM-based melody extraction (equipped with a newly-defined feature) and NMF-based soft masking. Evaluations on two publicly available databases show that the proposed system reaches state-of-the-art performance and outperforms several other combinations.