Spatial source subtraction based on incomplete measurements of relative transfer function

Kód výsledku v IS VaVaI

RIV/46747885:24220/15:#0003443 - isvavai.cz

Výsledek na webu

http://www.scopus.com/record/display.uri?eid=2-s2.0-84955503287&origin=resultslist&sort=plf-f&src=s&st1=Spatial+Source+Subtraction+Based+on+Incomplete+Measurements+of+Relative+Transfer+Function&st2=&sid=EB31C0B4EC3785F0957732B2F309

DOI - Digital Object Identifier

10.1109/TASLP.2015.2425213

Jazyk výsledku

angličtina

Název v původním jazyce

Spatial source subtraction based on incomplete measurements of relative transfer function

Popis výsledku v původním jazyce

Relative impulse responses between microphones are usually long and dense due to the reverberant acoustic environment. Estimating them from short and noisy recordings poses a long-standing challenge of audio signal processing. In this paper, we apply a novel strategy based on ideas of compressed sensing. Relative transfer function (RTF) corresponding to the relative impulse response can often be estimated accurately from noisy data but only for certain frequencies. This means that often only an incomplete measurement of the RTF is available. A complete RTF estimate can be obtained through finding its sparsest representation in the time-domain: that is, through computing the sparsest among the corresponding relative impulse responses. Based on this approach, we propose to estimate the RTF from noisy data in three steps. First, the RTF is estimated using any conventional method such as the nonstationarity-based estimator by Gannot et al. or through blind source separation. Second, freque

Název v anglickém jazyce

Spatial source subtraction based on incomplete measurements of relative transfer function

Popis výsledku anglicky

Relative impulse responses between microphones are usually long and dense due to the reverberant acoustic environment. Estimating them from short and noisy recordings poses a long-standing challenge of audio signal processing. In this paper, we apply a novel strategy based on ideas of compressed sensing. Relative transfer function (RTF) corresponding to the relative impulse response can often be estimated accurately from noisy data but only for certain frequencies. This means that often only an incomplete measurement of the RTF is available. A complete RTF estimate can be obtained through finding its sparsest representation in the time-domain: that is, through computing the sparsest among the corresponding relative impulse responses. Based on this approach, we propose to estimate the RTF from noisy data in three steps. First, the RTF is estimated using any conventional method such as the nonstationarity-based estimator by Gannot et al. or through blind source separation. Second, freque

Druh

J_x - Nezařazeno - Článek v odborném periodiku (Jimp, Jsc a Jost)

CEP obor

JC - Počítačový hardware a software

OECD FORD obor

—

Projekt

GA14-11898S: Zlepšování řečového signálu pomocí částečně slepých metod za použití pole mikrofonů

Návaznosti

P - Projekt vyzkumu a vyvoje financovany z verejnych zdroju (s odkazem do CEP)

Rok uplatnění

2015

Kód důvěrnosti údajů

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

Název periodika

IEEE-ACM TRANSACTIONS ON AUDIO SPEECH AND LANGUAGE PROCESSING

ISSN

2329-9290

e-ISSN

—

Svazek periodika

Volume 23

Číslo periodika v rámci svazku

Issue 8

Stát vydavatele periodika

US - Spojené státy americké

Počet stran výsledku

13

Strana od-do

1335-1347

Kód UT WoS článku

000356006200008

EID výsledku v databázi Scopus

2-s2.0-84955503287