Abstract

A pitch estimation device was proposed for live vocals to output appropriate pitch data through the musical instrument digital interface (MIDI). The intention was to ideally achieve unnoticeable latency while maintaining estimation accuracy. The projected target platform was low-cost, standalone hardware based around a microcontroller such as the Microchip PIC series. This study investigated, optimised and compared the performance of suitable algorithms for this application. Performance was determined by two key factors: accuracy and latency. Many papers have been published over the past six decades assessing and comparing the accuracy of pitch detection algorithms on various signals, including vocals. However, very little information is available concerning the latency of pitch detection algorithms and methods with which this can be minimised. Real-time audio introduces a further latency challenge that is sparsely studied, minimising the length of sampled audio required by the algorithms in order to reduce overall total latency. Thorough testing was undertaken in order to determine the best-performing algorithm and optimal parameter combination. Software modifications were implemented to facilitate accurate, repeatable, automated testing in order to build a comprehensive set of results encompassing a wide range of test conditions. The results revealed that the infinite-peak-clipping autocorrelation function (IACF) performed better than the other autocorrelation functions tested and also identified ideal parameter values or value ranges to provide the optimal latency/accuracy balance. Although the results were encouraging, testing highlighted some fundamental issues with vocal pitch detection. Potential solutions are proposed for further development.

Highlights

  • This work aimed to identify the most suitable pitch detection algorithm to implement in a standalone vocal pitch detection system for use with a live audio signal

  • The results revealed that the infinite-peak-clipping autocorrelation function (IACF) performed better than the other autocorrelation functions tested and identified ideal parameter values or value ranges to provide the optimal latency/accuracy balance

  • These studies have largely focused on the accuracy of pitch estimation, with very little attention given to latency and methods to improve this

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Summary

Introduction

This work aimed to identify the most suitable pitch detection algorithm to implement in a standalone vocal pitch detection system for use with a live (as opposed to prerecorded) audio signal. With a sufficiently low latency, this could find application in live music, allowing musicians to drive synthesisers by voice. Such a device must undertake real-time analysis of incoming audio, with minimal (ideally, completely imperceptible) delay between note onset and MIDI transmission. Many studies have already been conducted in the area of pitch detection, and extensive information is readily available. These studies have largely focused on the accuracy of pitch estimation, with very little attention given to latency and methods to improve this. Causes of latency The causes of latency fall into two categories. Derrien (2014) describes these as algorithmic delay and computational delay

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