Abstract

System-on-Chip (SoC) Field Programmable Gate Arrays (FPGAs) are ideal for real-time signal processing due to their low, deterministic latency and high performance. To showcase the utility of our open FPGA computational platform for real-time audio signal processing and computational modeling, several applications have been implemented. We have ported the openMHA hearing aid software [1] to our platform to show that pre-existing audio processing software can be implemented in SoC FPGAs by making external audio interfaces show up as a sound card. To highlight the ability to perform real-time computational modeling on our performance platform, we are implementing a real-time version of Laurel Carney’s auditory-nerve model [2] running in its own custom accelerator in the FPGA fabric. To illustrate the ability to develop DSP algorithms in MathWork’s Simulink and then implement them in the FPGA fabric we have taken several algorithms from Issa Panahi’s group [3] to show both frame-based processing (noise reduction) and sample-based processing (dynamic range compression). Finally, we show that the platform can be used to visualize audio signals using a real-time spectrogram where FFTs are computed in the FPGA fabric. [1] www.openmha.org. [2] JASA 126, 2390–2412. [3] www.utdallas.edu/ssprl/hearing-aid-project/.

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