Special Issue Article Open Access

An Efficient Extraction of Vocal Portion from Music Accompaniment Using Trend Estimation

Abstract

Speech and music are the most basic means of human communication. As technology advances and increasingly sophisticated tools become available to extract human speech from a noisy background. But the task of extracting a singing voice from a musical background, composed of many musical instruments is a challenging one as both the signals have very high coherence and correlation. Separating singing voice from music accompaniment is very useful in many applications, such as lyrics recognition and alignment, singer identification, and music information retrieval. This paper describes, a trend estimation algorithm to detect the pitch ranges of a singing voice in each time frame. The detected trend substantially reduces the difficulty of singing pitch detection by removing a large number of wrong pitch candidates either produced by musical instruments or the overtones of the singing voice. Qualitative results show that the system performs the separation task successfully.

Aisvarya V, Suganthy M

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