Voice Communication in Noisy Environments in a Smart House Using Hybrid LMS plus ICA Algorithm

Result code in IS VaVaI

<a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F61989100%3A27240%2F20%3A10248315" target="_blank" >RIV/61989100:27240/20:10248315 - isvavai.cz</a>

Alternative codes found

RIV/61989100:27120/20:10248315

Result on the web

<a href="https://www.mdpi.com/1424-8220/20/21/6022" target="_blank" >https://www.mdpi.com/1424-8220/20/21/6022</a>

DOI - Digital Object Identifier

<a href="http://dx.doi.org/10.3390/s20216022" target="_blank" >10.3390/s20216022</a>

Result language

angličtina

Original language name

Voice Communication in Noisy Environments in a Smart House Using Hybrid LMS plus ICA Algorithm

Original language description

This publication describes an innovative approach to voice control of operational and technical functions in a real Smart Home (SH) environment, where, for voice control within SH, it is necessary to provide robust technological systems for building automation and for technology visualization, software for recognition of individual voice commands, and a robust system for additive noise canceling. The KNX technology for building automation is used and described in the article. The LabVIEW SW tool is used for visualization, data connectivity to the speech recognizer, connection to the sound card, and the actual mathematical calculations within additive noise canceling. For the actual recognition of commands, the SW tool for recognition within the Microsoft Windows OS is used. In the article, the least mean squares algorithm (LMS) and independent component analysis (ICA) are used for additive noise canceling from the speech signal measured in a real SH environment. Within the proposed experiments, the success rate of voice command recognition for different types of additive interference (television, vacuum cleaner, washing machine, dishwasher, and fan) in the real SH environment was compared. The recognition success rate was greater than 95% for the selected experiments.

Czech name

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Czech description

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Type

J_imp - Article in a specialist periodical, which is included in the Web of Science database

CEP classification

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OECD FORD branch

20201 - Electrical and electronic engineering

Project

<a href="/en/project/EF17_049%2F0008425" target="_blank" >EF17_049/0008425: A Research Platform focused on Industry 4.0 and Robotics in Ostrava Agglomeration</a><br>

Continuities

P - Projekt vyzkumu a vyvoje financovany z verejnych zdroju (s odkazem do CEP)<br>S - Specificky vyzkum na vysokych skolach

Publication year

2020

Confidentiality

S - Úplné a pravdivé údaje o projektu nepodléhají ochraně podle zvláštních právních předpisů

Name of the periodical

Sensors

ISSN

1424-3210

e-ISSN

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Volume of the periodical

20

Issue of the periodical within the volume

21

Country of publishing house

CH - SWITZERLAND

Number of pages

24

Pages from-to

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UT code for WoS article

000593544200001

EID of the result in the Scopus database

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