sažetak izlaganja sa skupa
In this paper we describe a method for measuring variations in speech tempo from speech samples recorded from Croatian news channels, where the text of what was spoken is available through subtitles. For speech recognition we use a feed- forward neural network trained with about 150 seconds of speech. To extract word boundaries, we created a speech-to-text aligner capable of finding an acceptable match between text and sequence of phonemes classified by the neural network. The aligner takes into consideration certain categories of phonemes for which the neural network has higher accuracy. Preliminary experiments show average alignment miss of about one to three phonemes, depending on the speaker, the content, and recording quality.
speech recognition, text-to-speech alignment, speech tempo, neural network
Razvojem virtualizacijskih tehnologija raste kompleksnost IT sustava, dok korisnici istovremeno zahtijevaju brži pristup resursima, napredne integracije i jednostavnost korištenja. Jedno od ključnih rješenja za ove izazove primjena je…
Ovaj rad istražuje i uspoređuje mogućnosti prosljeđivanja grafičkih kartica na Hyper-V i KVM hipervizorima prema virtualnim strojevima, detaljno opisujući metode, postupke i razlike u arhitekturi koje utječu na…
The ever-growing usage and adaptation of HTTP/3 in web traffic leverages Quick UDP Internet Connections (QUIC) as a transport protocol. QUIC is widely recognized for reduced latency, enhanced…
