Event-Driven Continuous-Time Feature ...
Document type :
Communication dans un congrès avec actes
Title :
Event-Driven Continuous-Time Feature Extraction for Ultra Low-Power Audio Keyword Spotting
Author(s) :
Mourrane, S. [Auteur]
STMicroelectronics
Larras, Benoit [Auteur]
Institut d’Électronique, de Microélectronique et de Nanotechnologie - UMR 8520 [IEMN]
Microélectronique Silicium - IEMN [MICROELEC SI - IEMN]
Cathelin, A. [Auteur]
STMicroelectronics [Crolles] [ST-CROLLES]
Frappe, Antoine [Auteur]
Institut d’Électronique, de Microélectronique et de Nanotechnologie - UMR 8520 [IEMN]
Microélectronique Silicium - IEMN [MICROELEC SI - IEMN]
STMicroelectronics
Larras, Benoit [Auteur]
Institut d’Électronique, de Microélectronique et de Nanotechnologie - UMR 8520 [IEMN]
Microélectronique Silicium - IEMN [MICROELEC SI - IEMN]
Cathelin, A. [Auteur]
STMicroelectronics [Crolles] [ST-CROLLES]
Frappe, Antoine [Auteur]
Institut d’Électronique, de Microélectronique et de Nanotechnologie - UMR 8520 [IEMN]
Microélectronique Silicium - IEMN [MICROELEC SI - IEMN]
Conference title :
3rd IEEE International Conference on Artificial Intelligence Circuits and Systems, AICAS 2021
City :
Washington DC, DC
Country :
Etats-Unis d'Amérique
Start date of the conference :
2021-06-06
Book title :
2021 IEEE 3rd International Conference on Artificial Intelligence Circuits and Systems (AICAS)
Publisher :
Institute of Electrical and Electronics Engineers Inc.
Publication date :
2021
English keyword(s) :
Audio acoustics
Continuous time systems
Convolutional neural networks
Digital control systems
Digital signal processing
Discrete time control systems
Extraction
MATLAB
Complete system
Continuous-time digital signal processing
Discrete - time systems
Feature extractor
Keyword spotting
Recognition accuracy
Sound detection
Ultra low power
Feature extraction
Continuous time systems
Convolutional neural networks
Digital control systems
Digital signal processing
Discrete time control systems
Extraction
MATLAB
Complete system
Continuous-time digital signal processing
Discrete - time systems
Feature extractor
Keyword spotting
Recognition accuracy
Sound detection
Ultra low power
Feature extraction
HAL domain(s) :
Sciences de l'ingénieur [physics]
English abstract : [en]
In the context of autonomous keyword spotting and sound detection, this paper proposes a low power feature extraction unit generating spectrograms that represent a unique signature allowing the classification of audio ...
Show more >In the context of autonomous keyword spotting and sound detection, this paper proposes a low power feature extraction unit generating spectrograms that represent a unique signature allowing the classification of audio signals. This system is composed of a continuous-Time digital signal processing feature extractor combined with a convolutional neural network engine. The study evaluates the hardware requirements to implement the feature extraction unit using an advanced CMOS process. Furthermore, a simulation of the complete system using Matlab® reveals that the recognition accuracy remains higher than 90% while offering a power consumption 4000X lower than a conventional discrete time system.Show less >
Show more >In the context of autonomous keyword spotting and sound detection, this paper proposes a low power feature extraction unit generating spectrograms that represent a unique signature allowing the classification of audio signals. This system is composed of a continuous-Time digital signal processing feature extractor combined with a convolutional neural network engine. The study evaluates the hardware requirements to implement the feature extraction unit using an advanced CMOS process. Furthermore, a simulation of the complete system using Matlab® reveals that the recognition accuracy remains higher than 90% while offering a power consumption 4000X lower than a conventional discrete time system.Show less >
Language :
Anglais
Peer reviewed article :
Oui
Audience :
Internationale
Popular science :
Non
Source :
Files
- https://hal.archives-ouvertes.fr/hal-03362267/document
- Open access
- Access the document
- https://hal.archives-ouvertes.fr/hal-03362267/document
- Open access
- Access the document
- document
- Open access
- Access the document
- Event-Driven%20Continuous-Time%20Feature%20Extraction%20for%20Ultra%20Low-Power%20Audio%20Keyword%20Spotting_accepted.pdf
- Open access
- Access the document
- document
- Open access
- Access the document