Low-Latency f0 Estimation for the Finger Plucked Electric Bass Guitar Using the Absolute Difference Function

Audio-to-MIDI conversion can be used to allow digital musical control through an analog instrument. Audio-to-MIDI converters rely on fundamental frequency estimators that are usually restricted to a minimum delay of two fundamental periods. This delay is perceptible for the case of bass notes. In this dissertation, we propose a low-latency fundamental frequency estimation method that relies on specific characteristics of the electric bass guitar. By means of physical modeling and signal  acquisition, we show that the assumptions of this method are based on the generalization of all electric basses. We evaluated our method in a dataset with musical notes played by diverse bassists. Results show that our method outperforms the Yin method in low-latency settings, which indicates its suitability for low-latency audio-to-MIDI conversion of the electric bass sound

Low-Latency f0 Estimation for the Finger Plucked Electric Bass Guitar Using the Absolute Difference Function

Audio-to-MIDI conversion can be used to allow digital musical control through an analog instrument. Audio-to-MIDI converters rely on fundamental frequency estimators that are usually restricted to a minimum delay of two fundamental periods. This delay is perceptible for the case of bass notes. In this dissertation, we propose a low-latency fundamental frequency estimation method that relies on specific characteristics of the electric bass guitar. By means of physical modeling and signal  acquisition, we show that the assumptions of this method are based on the generalization of all electric basses. We evaluated our method in a dataset with musical notes played by diverse bassists. Results show that our method outperforms the Yin method in low-latency settings, which indicates its suitability for low-latency audio-to-MIDI conversion of the electric bass sound