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Artificial Intelligence and Machine Learning
Boosting Audio Processing with High-Performance ML

November 9, 2022
9:00 AM Pacific (12:00 PM Eastern)


The worlds of audio DSP and machine learning have converged. OEMs are now leveraging machine learning (ML) processing to power improved sound and voice features for their products. Hearing aid manufacturers were among the first to implement ML to identify and reduce dynamic background noise. Consumer electronics OEMs are now adding ML to experiences like voice UIs, improving speaker identification and natural language processing.
The Audio Product Education Institute (APEI), an initiative of the Audio Engineering Society (AES), presents a webinar on the implementation of Machine Learning solutions using DSP Concept’s Audio Weaver in the new and exciting Alif Ensemble MCUs running Arm’s ML accelerated Ethos U55 architecture. This session, presented by APEI’s AI and ML education pillar, will help attendees gain a high-level overview of the exciting new audio processing possibilities leveraging these powerful new scalable microcontrollers, uniting highly integrated embedded processors with AI acceleration.
Despite the recognized benefits, machine learning presents deployment, form factor, power consumption, and processing bandwidth challenges for OEMs:
Tensorflow and Pytorch offer platforms for developers to build and train their machine learning models. Often when it comes to deployment however, ML processing ideally fits somewhere within the audio signal path. Audio Weaver, the development framework from DSP Concepts, simplifies adding ML processing to audio signal flows. Product makers can extract feature sets within Audio Weaver, then later tune and deploy in the same environment.
Form factor and power consumption
Portable and wearable audio devices like earbuds necessitate designs that are small in form factor and require minimal power consumption. Chip makers have responded to this challenge with new architectures that can accelerate processing for ML while maintaining a small footprint, like the Arm Ethos-U55. Arm’s ML processors, called microNPUs, are specifically designed to deliver increased processing capability in area-constrained embedded devices.
Processing bandwidth
Traditionally the high processing load required to drive ML algorithms necessitated additional DSP hardware or forced processing onto the cloud. Alif Semiconductor has introduced the Ensemble series of MCUs, which leverages the new ML-optimized Arm architecture, creating a platform up to 800x more efficient than previous generation designs. This allows OEMs to deploy powerful ML features wholly contained on embedded devices with high-speed connectivity, architected for power efficiency and long battery life.
DSP Concepts knows this challenges well from its experience to support developers creating new audio product designs with Audio Weaver. In this session, Josh Morris, Engineering Manager of ML Development for DSP Concepts will share that experience in dealing with those audio processing challenges, while Henrik Flodell from Alif Semiconductor will reveal how the company’s new Ensemble platform, the first implementation of the Arm Ethos-U55 microNPU + Cortex-M55 MCU, will help boost high computation and ML/AI capabilities.
Join DSP Concepts and Alif Semiconductor in this Audio Product Education Institute on November 9 for an overview and demonstration of these machine learning solutions. We will present an overview of machine learning and how it can be applied to audio. We’ll then demonstrate development and deployment of ML algorithms using Audio Weaver and profile those designs on hardware with the Alif Ensemble MCU powered by Arm Ethos-U55.
The webinar will be followed by a live Q&A sessions with all presenters.
Henrik Flodell

Director of Marketing at Alif Semiconductor, San Francisco, California, USA

Henrik Flodell is the Marketing Director at Alif Semiconductor. With 20+ years of experience in the embedded industry, Henrik started his career as a firmware developer for medical dataloggers in the early 90s, and has since managed development tools, embedded software deployment systems, hardware development platforms, marketing and business development teams, and participated in SoC product definitions for a wide range of embedded devices. He held those positions at leading semiconductor companies such as IAR Systems, NXP Semiconductors, Atmel Corporation and Renesas Electronics. At Alif, Henrik is responsible for the Ensemble product family, and Alifs rapidly growing partner Eco-System.

Josh Morris

ML Engineer at DSP Concepts, Nashville, Tennessee, USA

Josh Morris is the engineering manager of ML development at DSP Concepts. Josh got his start in ML working on automatic speech recognition (ASR) and natural language processing (NLP) for conduct surveillance in financial institutions. From there, he worked on applications ranging from embedded audio dynamic range control to optical character recognition (OCR). At DSP Concepts, he focuses on ML IP creation and the ML development experience in Audio Weaver. Audio Weaver is a cross-platform audio framework featuring a modular, drag-and-drop, real-time design environment that enables product development teams to rapidly create signal processing solutions for embedded environments.

Steve F. Willenborg

VP of Sales, Linkplay Technology, Campbell, California, USA

An international executive with a strong background in engineering and business development for multiple product market segments, Steve’s career spans for over 35 years, covering audio, consumer electronics and automotive. At Linkplay Technology, Steve is directly involved in supporting some of the largest corporations, cutting-edge companies and brands in the development of smart audio solutions, software/firmware development, and wireless audio, device cloud software and streaming content integration. Before Linkplay, Steve worked for NPD Development (Shenzhen, China), Scan Speak (Denmark) and Premier Sound Group (Shenzhen, China), all business units of Eastech Holding, managing global auto OEM product development, and operation teams located in China, Denmark, Singapore and the USA. Previously he worked with Materion Corporation, Tymphany Corporation, Zylux Acoustic, Harman International, and General Motors.