Minimising latency of pitch detection algorithms for live vocals on low-cost hardware

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

Verifying the distributed real-time network protocol RTnet using Uppaal

RTnet is a distributed real-time network protocol for fully-connected local area networks with a broadcast capability. It supports streaming real-time and non-realtime traffic and on-the-fly addition and removal of network nodes. This paper presents a formal analysis of RTnet using the model checker Uppaal. Besides normal protocol behaviour, the analysis focuses on the fault-handling properties of RTnet, in particular recovery after packet loss. Both qualitative and quantitative properties are presented, together with the verification results and conclusions about the robustness of RTnet

Particle swarm optimization with sequential niche technique for dynamic finite element model updating

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