Zobrazeno 1 - 3
of 3
pro vyhledávání: '"Alex Escott"'
Autor:
Sashank Macha, Om Oza, Alex Escott, Francesco Calivá, Robbie Armitano, Santosh Kumar Cheekatmalla, Sree Hari Krishnan Parthasarathi, Yuzong Liu
Fixed-point (FXP) inference has proven suitable for embedded devices with limited computational resources, and yet model training is continually performed in floating-point (FLP). FXP training has not been fully explored and the non-trivial conversio
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::a456dca8a35606d8d56ae41d542490e3
Autor:
Lu Zeng, Sree Hari Krishnan Parthasarathi, Yuzong Liu, Alex Escott, Santosh Cheekatmalla, Nikko Strom, Shiv Vitaladevuni
Publikováno v:
Text, Speech, and Dialogue ISBN: 9783031162695
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::dd74b699908c508adc76dcec523db801
https://doi.org/10.1007/978-3-031-16270-1_30
https://doi.org/10.1007/978-3-031-16270-1_30
Autor:
Thibaud Senechal, Christin Jose, Alex Escott, Yuriy Mishchenko, Anish Shah, Shiv Naga Prasad Vitaladevuni
Publikováno v:
INTERSPEECH
Small footprint embedded devices require keyword spotters (KWS) with small model size and detection latency for enabling voice assistants. Such a keyword is often referred to as \textit{wake word} as it is used to wake up voice assistant enabled devi
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::6fcd98cefd942994e1953c3c5004df23
https://doi.org/10.21437/interspeech.2020-1491
https://doi.org/10.21437/interspeech.2020-1491
