Independent Vector Analysis Exploiting Pre-Learned Banks of Relative Transfer Functions for Assumed Target’s Positions

Kód výsledku v IS VaVaI

<a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F46747885%3A24220%2F18%3A00006131" target="_blank" >RIV/46747885:24220/18:00006131 - isvavai.cz</a>

Výsledek na webu

<a href="https://asap.ite.tul.cz/wp-content/uploads/sites/3/2018/05/LVA2018SIVA.pdf" target="_blank" >https://asap.ite.tul.cz/wp-content/uploads/sites/3/2018/05/LVA2018SIVA.pdf</a>

DOI - Digital Object Identifier

<a href="http://dx.doi.org/10.1007/978-3-319-93764-9_26" target="_blank" >10.1007/978-3-319-93764-9_26</a>

Jazyk výsledku

angličtina

Název v původním jazyce

Independent Vector Analysis Exploiting Pre-Learned Banks of Relative Transfer Functions for Assumed Target’s Positions

Popis výsledku v původním jazyce

On-line frequency-domain blind separation of audio sources performed through Independent Vector Analysis (IVA) suffers from the problem of determining the order of the separated outputs. In this work,we apply a supervised IVA based on pilot components obtained using a bank of Relative Transfer Functions (RTF). The bank is assumed to be available for potential positions of a target speaker within a confined area. In every frame, the most suitable RTF is selected from the bank based on a criterion. The pilot components are obtained as pre-separated target and interference, respectively, through the Minimum-Power Distortionless Beamforming and Null Beamforming. The supervised IVA is tested in a real-world scenario with various levels of up-to-dateness of the bank. We show that the global permutation problem is resolved even when the bank contains only pure delay filters. The Signal-to-Interference Ratio in separated signals is mostly better than that achieved by the pre-separation, unless the bank contains very precise RTFs.

Název v anglickém jazyce

Independent Vector Analysis Exploiting Pre-Learned Banks of Relative Transfer Functions for Assumed Target’s Positions

Popis výsledku anglicky

On-line frequency-domain blind separation of audio sources performed through Independent Vector Analysis (IVA) suffers from the problem of determining the order of the separated outputs. In this work,we apply a supervised IVA based on pilot components obtained using a bank of Relative Transfer Functions (RTF). The bank is assumed to be available for potential positions of a target speaker within a confined area. In every frame, the most suitable RTF is selected from the bank based on a criterion. The pilot components are obtained as pre-separated target and interference, respectively, through the Minimum-Power Distortionless Beamforming and Null Beamforming. The supervised IVA is tested in a real-world scenario with various levels of up-to-dateness of the bank. We show that the global permutation problem is resolved even when the bank contains only pure delay filters. The Signal-to-Interference Ratio in separated signals is mostly better than that achieved by the pre-separation, unless the bank contains very precise RTFs.

Druh

D - Stať ve sborníku

CEP obor

—

OECD FORD obor

10102 - Applied mathematics

Projekt

<a href="/cs/project/GA17-00902S" target="_blank" >GA17-00902S: Pokročilé metody slepé separace podprostorů</a><br>

Návaznosti

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

Rok uplatnění

2018

Kód důvěrnosti údajů

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

Název statě ve sborníku

Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) - The 14th International Conference on Latent Variable Analysis and Signal Separation (LVA/ICA 2018)

ISBN

9783319937632

ISSN

03029743

e-ISSN

—

Počet stran výsledku

10

Strana od-do

270-279

Název nakladatele

—

Místo vydání

—

Místo konání akce

Guildford, UK

Datum konání akce

1. 1. 2018

Typ akce podle státní příslušnosti

WRD - Celosvětová akce

Kód UT WoS článku

—