EAGER: An Efficient Algorithm for Automated Transcription of Music, Vocalizations, and Arbitrary Sound Recordings

点击翻译按钮获取中文摘要

AbstractThis proposed EAGER project focuses on a new, robust and efficient technique to transcribe arbitrary sounds. It also extends in a novel and transformative fashion earlier work that developed a music search engine based on identifying aesthetic similarities. Automated transcription of musical sounds is still an open research area and one of exceptional importance. While some limited transcription techniques are available, they lack critical abilities, such as inability to transcribe polyphonic compositions or difficulties in distinguishing sounds produced by different sources. In addition, the frequency ranges are limited, thereby excluding a vast number of musical works. The approach proposed in this project involves an innovative audio-to-MIDI transcription algorithm, which handles polyphonic compositions, captures harmonic, vocal and percussive instrumentation, is very efficient and works with sounds beyond human produced musical compositions, such as bird songs and sub/ultrasonic animal vocalizations.