Audio noise reduction accelerator system and method based on RISC v custom instruction set expansion

Abstract

The invention discloses an audio noise reduction accelerator system and method based on RISC v custom instruction set expansion, and belongs to the technical field of integrated circuits. The system mainly comprises an E203_CORE, an NICE_CORE, a NICE_Interface, an E203_SOC, an audio coding and decoding WM8731 module, and an audio noise reduction FxLMS algorithm, wherein the E203_CORE is connected with the NICE_CORE through the NICE_Interface, the E203_CORE, the NICE_CORE and a related peripheral port form the E203_SOC together, the E203_SOC is connected with the audio coding and decoding WM8731 module, and the audio noise reduction FxLMS algorithm is downloaded into a core of the RISC v processor through software programming to run. Compared with a processor of an ARM instruction set architecture, the processor adopting an RISC v custom instruction set can accelerate a specific operation part in the audio noise reduction FxLMS algorithm; and the problems of area, power consumption, granularity and the like can be better optimized, and the flexibility and feasibility of the algorithm are improved.

Description

technical field [0001] The invention belongs to the technical field of integrated circuits, and in particular relates to an audio noise reduction accelerator system and method based on RISC V self-defined instruction set expansion. Background technique [0002] With the development of the economy and the continuous advancement of technology, there are more and more application scenarios for audio noise reduction systems, such as noise reduction in cars, noise reduction in gas stations, and earphone noise reduction. However, at present, passive noise reduction methods such as physically isolating noise sources are often adopted. The method of using active noise reduction to allow sound source signals to superimpose and cancel is often difficult to implement in hardware. It is difficult to use FPGA for hardware implementation of improved excellent algorithms. Therefore, it is adopted The software implementation will enable the improved algorithm to be realized, which will be a...

AI Technical Summary

Problems solved by technology

Such a method is often inflexible, and retraining is required for different noise sources. At the same time, such a method does not have the flexibility to adopt software and hardware co-pr...

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