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Realistic Procedural Sound Synthesis of Bird Song Using Particle Swarm Optimization

We present a synthesis algorithm for approximating bird song using particle swarm optimization to match real bird recordings. Frequency and amplitude envelope curves are first extracted from a bird recording. Further analysis identifies the presence of even and odd harmonics. A particle swarm algorithm is then used to find cubic Bezier curves which emulate the envelopes. These curves are applied to modulate a sine oscillator and its harmonics. The synthesized syllable can then be repeated to generate the sound. Thirty-six bird sounds have been emulated this way, and a real-time web-based demonstrator is available, with user control of all parameters. Objective evaluation showed that the synthesized bird sounds captured most audio features of the recordings.

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