Automatic Transcription of Polyphonic Vocal Music

Automatic Transcription of Polyphonic Vocal Music

Blog Article

This paper presents a method for automatic music transcription applied to audio recordings of a cappella performances with multiple singers.We propose a system for multi-pitch detection and voice assignment that integrates an acoustic and a music language model.The acoustic model performs spectrogram decomposition, extending probabilistic latent component analysis (PLCA) using a six-dimensional dictionary with pre-extracted log-spectral templates.

The music language model performs voice separation and assignment using hidden Markov models that apply musicological 3ag/5ag Fuses assumptions.By integrating the two models, the system is able to detect multiple concurrent pitches in polyphonic vocal music and assign each detected pitch to a specific voice type such as soprano, alto, tenor or bass (SATB).We compare our system against multiple baselines, achieving state-of-the-art results for both multi-pitch detection and voice assignment on a dataset of Bach chorales and another Ball - Shoes TPU - Womens of barbershop quartets.

We also present an additional evaluation of our system using varied pitch tolerance levels to investigate its performance at 20-cent pitch resolution.