Auxiliary Function-Based Algorithm for Blind Extraction of a Moving Speaker

Kód výsledku v IS VaVaI

<a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F46747885%3A24220%2F22%3A00009081" target="_blank" >RIV/46747885:24220/22:00009081 - isvavai.cz</a>

Výsledek na webu

<a href="https://asmp-eurasipjournals.springeropen.com/track/pdf/10.1186/s13636-021-00231-6.pdf" target="_blank" >https://asmp-eurasipjournals.springeropen.com/track/pdf/10.1186/s13636-021-00231-6.pdf</a>

DOI - Digital Object Identifier

<a href="http://dx.doi.org/10.1186/s13636-021-00231-6" target="_blank" >10.1186/s13636-021-00231-6</a>

Jazyk výsledku

angličtina

Název v původním jazyce

Auxiliary Function-Based Algorithm for Blind Extraction of a Moving Speaker

Popis výsledku v původním jazyce

We propose a novel algorithm for Blind Source Extraction (BSE) of a moving acoustic source recorded by multiple microphones. The algorithm is based on Independent Vector Extraction (IVE) where the contrast function is optimized using the auxiliary function-based technique. The recently proposed Constant Separating Vector (CSV) mixing model is assumed, which allows for movements of the extracted source within the analyzed batch of recordings. We provide a practical explanation of how the CSV model works when extracting a moving acoustic source. Then, the proposed algorithm is experimentally verified on the task of blind extraction of a moving speaker. The algorithm is compared with state-of-the-art blind methods and with an adaptive BSE algorithm which processes data in a sequential manner. The results confirm that the proposed algorithm can extract the moving speaker better than the BSE methods based on the conventional mixing model and that it achieves improved extraction accuracy than the adaptive method.

Název v anglickém jazyce

Auxiliary Function-Based Algorithm for Blind Extraction of a Moving Speaker

Popis výsledku anglicky

We propose a novel algorithm for Blind Source Extraction (BSE) of a moving acoustic source recorded by multiple microphones. The algorithm is based on Independent Vector Extraction (IVE) where the contrast function is optimized using the auxiliary function-based technique. The recently proposed Constant Separating Vector (CSV) mixing model is assumed, which allows for movements of the extracted source within the analyzed batch of recordings. We provide a practical explanation of how the CSV model works when extracting a moving acoustic source. Then, the proposed algorithm is experimentally verified on the task of blind extraction of a moving speaker. The algorithm is compared with state-of-the-art blind methods and with an adaptive BSE algorithm which processes data in a sequential manner. The results confirm that the proposed algorithm can extract the moving speaker better than the BSE methods based on the conventional mixing model and that it achieves improved extraction accuracy than the adaptive method.

Druh

J_imp - Článek v periodiku v databázi Web of Science

CEP obor

—

OECD FORD obor

20201 - Electrical and electronic engineering

Projekt

Výsledek vznikl pri realizaci vícero projektů. Více informací v záložce Projekty.

Návaznosti

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

Rok uplatnění

2022

Kód důvěrnosti údajů

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

Název periodika

EURASIP JOURNAL ON AUDIO SPEECH AND MUSIC PROCESSING

ISSN

1687-4722

e-ISSN

—

Svazek periodika

2022

Číslo periodika v rámci svazku

1

Stát vydavatele periodika

DE - Spolková republika Německo

Počet stran výsledku

16

Strana od-do

—

Kód UT WoS článku

000738591200001

EID výsledku v databázi Scopus

2-s2.0-85122295670