Automatic Recognition of Pelung and Canary Bird Sounds Using Machine Learning and Signal Enhancement - Agustika, Dyah Kurniawati; Kadarisman, Nur; Sumarna, Sumarna; Purwanto, Agus (Fakultas Matematika dan Ilmu Pengetahuan Alam, Univetsitas Tanjungpura, 2025)
Bird sound classification is a valuable tool in ecological monitoring and species identification, particularly for non-invasive assessment in natural environments. However, challenges such as limited labeled data and environmental noise often reduce the reliability of classification models. This study presents a lightweight bird sound classification pipeline that integrates signal preprocessing, audio augmentation, and machine learning to address these issues. Two bird species with distinct vocal characteristics, Pelung (a crossbreed involving Bangkok chickens) and Canary (Serinus canaria), were used as case subjects. A total of 40 original 2-second audio clips were extracted from longer field recordings, then processed through frame-based energy attenuation, bandpass filtering (1