Timed Probabilistic Automaton: A Bridge between Raven and Song Scope for Automatic Species Recognition

Raven and Song Scope are two state-of-the-art automated sound analysis tools based on machine learning techniques for environmental monitoring. Many research works have been conducted upon them, however, no or rare exploration mentions about the performance and comparison between them. This paper compares the tools from six aspects: theory, software interface, ease of use, detection targets, detection accuracy, and potential applications. Through deep exploration one critical gap is identified that there is a lack of approach to detect both syllables and call structures, since Raven only aims to detect syllables while Song Scope targets call structures. Therefore, a Timed Probabilistic Automata (TPA) system is proposed which separates syllables and clusters them into complex structures.