Sound event detection with binary neural networks on tightly power-constrained IoT devices
Gianmarco Cerutti, Renzo Andri, Lukas Cavigelli, Elisabetta Farella, Michele Magno, Luca Benini
Abstract
Sound event detection (SED) is a hot topic in consumer and smart city applications. Existing approaches based on deep neural networks (DNNs) are very effective, but highly demanding in terms of memory, power, and throughput when targeting ultra-low power always-on devices.
Topics & Concepts
Computer scienceEvent (particle physics)Artificial neural networkInternet of ThingsThroughputBinary numberArtificial intelligenceDeep neural networksReal-time computingPower (physics)Sound (geography)Home automationDeep learningMusic and Audio ProcessingSpeech and Audio ProcessingMusic Technology and Sound Studies