YoVDO

Real-Time Inference of Neural Networks: A Guide for DSP Engineers

Offered By: ADC - Audio Developer Conference via YouTube

Tags

Digital Signal Processing Courses Machine Learning Courses Neural Networks Courses TensorFlow Courses PyTorch Courses ONNX Runtime Courses

Course Description

Overview

Save Big on Coursera Plus. 7,000+ courses at $160 off. Limited Time Only!
Explore real-time inference of neural networks for DSP engineers in this 41-minute conference talk from the Audio Developer Conference 2023. Dive into the practical steps of implementing neural timbre transfer technology in audio plugins, focusing on maintaining real-time safety and balancing latency, performance, and stability. Compare three inference engines - libtorch, tensorflow-lite, and onnxruntime - to simplify decision-making for specific use cases. Learn about the inference pipeline, architecture, benchmarking, continuous signal flow, and convolution layers. Gain insights from the speakers' experiences in developing innovative audio processing solutions that combine DSP and AI technologies.

Syllabus

Introduction
Background
Deep Learning
Inference Engines
Inference Pipeline
Inference Architecture
Benchmarking
Continuous Signal Flow
Convolution Layers


Taught by

ADC - Audio Developer Conference

Related Courses

Fundamentals of Electrical Engineering
Rice University via Coursera
Digital Signal Processing
École Polytechnique Fédérale de Lausanne via Coursera
Fundamentals of Electrical Engineering Laboratory
Rice University via Coursera
Processamento Digital de Sinais - Amostragem
Universidade Estadual de Campinas via Coursera
Physics-Based Sound Synthesis for Games and Interactive Systems
Stanford University via Kadenze