TOWARD AUTOMATIC SOUND SOURCE RECOGNITION: IDENTIFYING MUSICAL INSTRUMENTS
Keith D. Martin · 1998
One of the broad goals of research in computational auditory scene analysis (CASA) is to create computer systems that can learn to recognize sound sources in a complex auditory environment. In this paper, a set of acoustic features is proposed that relate to the physical properties of sound-producing objects. In particular, a set of orchestral musical instrument sounds is presented as representative of the class of sounds produced by quasi-periodic excitation of resonant structures, acoustic properties of this class are considered, and the log-lag correlogram is presented as a signal representation that codes many of the proposed features. Specific examples are given of features extracted from vio- lin, trumpet, and flute tones. Extensions to Ellis's prediction -driven CASA framework are proposed in the form of a hierarchy of sound-source models represented by frames. It is suggested that the goal of building an artificial system for sound source recognition in complex mixtures may be ...