Voice Communication in Noisy Environments in a Smart House Using Hybrid LMS plus ICA Algorithm
Identifikátory výsledku
Kód výsledku v 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>
Nalezeny alternativní kódy
RIV/61989100:27120/20:10248315
Výsledek na webu
<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>
Alternativní jazyky
Jazyk výsledku
angličtina
Název v původním jazyce
Voice Communication in Noisy Environments in a Smart House Using Hybrid LMS plus ICA Algorithm
Popis výsledku v původním jazyce
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.
Název v anglickém jazyce
Voice Communication in Noisy Environments in a Smart House Using Hybrid LMS plus ICA Algorithm
Popis výsledku anglicky
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.
Klasifikace
Druh
J<sub>imp</sub> - Článek v periodiku v databázi Web of Science
CEP obor
—
OECD FORD obor
20201 - Electrical and electronic engineering
Návaznosti výsledku
Projekt
<a href="/cs/project/EF17_049%2F0008425" target="_blank" >EF17_049/0008425: Platforma pro výzkum orientovaný na Průmysl 4.0 a robotiku v ostravské aglomeraci</a><br>
Návaznosti
P - Projekt vyzkumu a vyvoje financovany z verejnych zdroju (s odkazem do CEP)<br>S - Specificky vyzkum na vysokych skolach
Ostatní
Rok uplatnění
2020
Kód důvěrnosti údajů
S - Úplné a pravdivé údaje o projektu nepodléhají ochraně podle zvláštních právních předpisů
Údaje specifické pro druh výsledku
Název periodika
Sensors
ISSN
1424-3210
e-ISSN
—
Svazek periodika
20
Číslo periodika v rámci svazku
21
Stát vydavatele periodika
CH - Švýcarská konfederace
Počet stran výsledku
24
Strana od-do
—
Kód UT WoS článku
000593544200001
EID výsledku v databázi Scopus
—