Zobrazeno 1 - 10
of 23
pro vyhledávání: '"Irit Opher"'
Publikováno v:
Computer Speech & Language. 45:411-436
Use of PLDA as a criterion to choose the best i-vectors for the new mean.Replacing the constant threshold for as the i-vector's neighborhood by the kNN which dramatically increased the stability of the system. This paper extends upon a previous work
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::76333b9768bdb9093144d92f32769e05
https://doi.org/10.1016/j.csl.2017.04.006
https://doi.org/10.1016/j.csl.2017.04.006
Autor:
Stav Naor, Ruth Aloni-Lavi, Noa Diamant, Irit Opher, Yermiyahu Hauptman, Itshak Lapidot, Yael Manor, Tanya Gurevich
Publikováno v:
INTERSPEECH
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::6714be5f1602abc3588a76470da94e07
https://doi.org/10.21437/interspeech.2019-2465
https://doi.org/10.21437/interspeech.2019-2465
Publikováno v:
Odyssey
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::8fbe187fe65bc3eabaf6f8b10504e663
https://doi.org/10.21437/odyssey.2018-17
https://doi.org/10.21437/odyssey.2018-17
Publikováno v:
Text, Speech, and Dialogue ISBN: 9783030007935
TSD
TSD
Prosody provides important information about intention and meaning, and carries clues regarding dialogue turns, phrase emphasis and even the physiological or emotional condition of the speaker. Prosody has been researched extensively by linguists and
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::8a8dcecb1bac325b3c427095138c26c6
https://doi.org/10.1007/978-3-030-00794-2_52
https://doi.org/10.1007/978-3-030-00794-2_52
Publikováno v:
2016 IEEE International Conference on the Science of Electrical Engineering (ICSEE).
This paper extends upon previous work using Mean Shift algorithm to perform speaker clustering on i-vectors generated from short speech segments. In this paper we examine the effectiveness of Spherical Normalization in the presence of different numbe
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::6de00a71e4d50ff22a5f782bc03e7a00
https://doi.org/10.1109/icsee.2016.7806108
https://doi.org/10.1109/icsee.2016.7806108
Publikováno v:
MLSP
In this study we address the problem of training a neural network for language identification using speech samples in the form of i-vectors. Our approach involves training a classifier and analyzing the obtained confusion matrix. We cluster the langu
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::b217a843f0eebd00685a963f67634be6
https://doi.org/10.1109/mlsp.2016.7738896
https://doi.org/10.1109/mlsp.2016.7738896
Publikováno v:
Odyssey
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::65a913d2e898fe10daeb22f18ea49149
https://doi.org/10.21437/odyssey.2016-59
https://doi.org/10.21437/odyssey.2016-59
Autor:
Ella Tetariy, Vered Aharonson, Irit Opher, Ruthi Alon-Lavi, Michal Gishri, Ami Moyal, Yossi Bar-Yosef
Publikováno v:
Artificial Intelligence Research. 5
Performing Phonetic Search Keyword Spotting (PS KWS) in new languages when language resources are scarce is an interesting and challenging task. In a previous paper we reported a methodology that enabled PS KWS under these conditions utilizing cross-
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::c54845d252825e3fc5b864722741793c
https://doi.org/10.5430/air.v5n2p24
https://doi.org/10.5430/air.v5n2p24
Publikováno v:
INTERSPEECH
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::51a8e6528fbd0df3ef506ef3878d49c9
https://doi.org/10.21437/interspeech.2015-102
https://doi.org/10.21437/interspeech.2015-102
Autor:
Ella Tetariy, Ruthi Alon-Lavi, Yossi Bar-Yosef, Vered Aharonson, Michal Gishri, Irit Opher, Ami Moyal, Vered Silber-Varod
Publikováno v:
Artificial Intelligence Research. 4
As automatic speech recognition-based applications become increasingly common in a wide variety of market segments, thereis a growing need to support more languages. However, for many languages, the language resources needed to train speechrecognitio
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::095507d9de045c887bc319d4da7222d3
https://doi.org/10.5430/air.v4n2p72
https://doi.org/10.5430/air.v4n2p72