Analysis of impact of emotions on target speech extraction and speech separation
Identifikátory výsledku
Kód výsledku v IS VaVaI
<a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F00216305%3A26230%2F22%3APU146144" target="_blank" >RIV/00216305:26230/22:PU146144 - isvavai.cz</a>
Výsledek na webu
<a href="https://ieeexplore.ieee.org/stamp/stamp.jsp?arnumber=9914718" target="_blank" >https://ieeexplore.ieee.org/stamp/stamp.jsp?arnumber=9914718</a>
DOI - Digital Object Identifier
<a href="http://dx.doi.org/10.1109/IWAENC53105.2022.9914718" target="_blank" >10.1109/IWAENC53105.2022.9914718</a>
Alternativní jazyky
Jazyk výsledku
angličtina
Název v původním jazyce
Analysis of impact of emotions on target speech extraction and speech separation
Popis výsledku v původním jazyce
Recently, the performance of blind speech separation (BSS) and target speech extraction (TSE) has greatly progressed. Most works, however, focus on relatively well-controlled conditions using, e.g., read speech. The performance may degrade in more realistic situations. One of the factors causing such degradation may be intrinsic speaker variability, such as emotions, occurring commonly in realistic speech. In this paper, we investigate the influence of emotions on TSE and BSS. We create a new test dataset of emotional mixtures for the evaluation of TSE and BSS. This dataset combines LibriSpeech and Ryerson Audio-Visual Database of Emotional Speech and Song (RAVDESS). Through controlled experiments, we can analyze the impact of different emotions on the performance of BSS and TSE.We observe that BSS is relatively robust to emotions, while TSE, which requires identifying and extracting the speech of a target speaker, is much more sensitive to emotions. On comparative speaker verification experiments we show that identifying the target speaker may be particularly challenging when dealing with emotional speech. Using our findings, we outline potential future directions that could improve the robustness of BSS and TSE systems toward emotional speech.
Název v anglickém jazyce
Analysis of impact of emotions on target speech extraction and speech separation
Popis výsledku anglicky
Recently, the performance of blind speech separation (BSS) and target speech extraction (TSE) has greatly progressed. Most works, however, focus on relatively well-controlled conditions using, e.g., read speech. The performance may degrade in more realistic situations. One of the factors causing such degradation may be intrinsic speaker variability, such as emotions, occurring commonly in realistic speech. In this paper, we investigate the influence of emotions on TSE and BSS. We create a new test dataset of emotional mixtures for the evaluation of TSE and BSS. This dataset combines LibriSpeech and Ryerson Audio-Visual Database of Emotional Speech and Song (RAVDESS). Through controlled experiments, we can analyze the impact of different emotions on the performance of BSS and TSE.We observe that BSS is relatively robust to emotions, while TSE, which requires identifying and extracting the speech of a target speaker, is much more sensitive to emotions. On comparative speaker verification experiments we show that identifying the target speaker may be particularly challenging when dealing with emotional speech. Using our findings, we outline potential future directions that could improve the robustness of BSS and TSE systems toward emotional speech.
Klasifikace
Druh
D - Stať ve sborníku
CEP obor
—
OECD FORD obor
10201 - Computer sciences, information science, bioinformathics (hardware development to be 2.2, social aspect to be 5.8)
Návaznosti výsledku
Projekt
<a href="/cs/project/LTAIN19087" target="_blank" >LTAIN19087: Multi-lingualita v řečových technologiích</a><br>
Návaznosti
P - Projekt vyzkumu a vyvoje financovany z verejnych zdroju (s odkazem do CEP)
Ostatní
Rok uplatnění
2022
Kód důvěrnosti údajů
S - Úplné a pravdivé údaje o projektu nepodléhají ochraně podle zvláštních právních předpisů
Údaje specifické pro druh výsledku
Název statě ve sborníku
Proceedings of The 17th International Workshop on Acoustic Signal Enhancement (IWAENC 2022)
ISBN
978-1-6654-6867-1
ISSN
—
e-ISSN
—
Počet stran výsledku
5
Strana od-do
1-5
Název nakladatele
IEEE Signal Processing Society
Místo vydání
Bamberg
Místo konání akce
Bamberg
Datum konání akce
5. 9. 2022
Typ akce podle státní příslušnosti
WRD - Celosvětová akce
Kód UT WoS článku
—