Poster Abstract: Towards Speaker Identification on Resource-Constrained Embedded Devices

被引：0
|
作者：
Gallacher, Markus [1 ]
Boano, Carlo Alberto [1 ]
Sankar, M. S. Arun [2 ]
Roedig, Utz [2 ]
Lunardi, Willian T. [3 ]
Baddeley, Michael [3 ]
机构：
[1] Graz Univ Technol, Graz, Austria
[2] Univ Coll Cork, Cork, Ireland
[3] Technol Innovat Inst, Abu Dhabi, U Arab Emirates
来源：
PROCEEDINGS OF THE 21ST ACM CONFERENCE ON EMBEDDED NETWORKED SENSOR SYSTEMS, SENSYS 2023 | 2023年
基金：
爱尔兰科学基金会;
关键词：
Machine Learning; Speaker Identification; Embedded Systems;
D O I：
10.1145/3625687.3628387
中图分类号：
TP301 [理论、方法];
学科分类号：
081202 ;
摘要：
Voice is a convenient and popular way to interact with our digital world. Besides translating speech to text, it is also possible to identify speakers based on their voice profile. To date, speaker identification has predominantly been limited to high-performance computational platforms owing to the intricate nature of the underlying algorithms. In this work, we demonstrate that it is possible to reduce model complexity by the required factor of similar to 10, such that speaker identification can be made feasible for embedded devices with limited resources. We further describe and discuss novel use cases, such as voice-based presence detection and authentication, that become feasible on these class of devices.
引用
收藏
页码：518 / 519
页数：2
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