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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.