PESQ scores in seen noise sources for IRM training-target.
PESQ scores in seen noise sources for IRM training-target.
Amil Daraz (9667034) +3 more
core +1 more source
Performance comparison of TIMIT and MusicBrainz datasets with respect to STOI and PESQ for noisy signal and proposed algorithm.
Tabassam Nawaz (4984502) +4 more
core +1 more source
The Influence Of Online Service Quality (PESQ) On Customer Trust (E-Trust) On The Shopee Indonesia E-Commerce Platform [PDF]
This research explores the broad impact of digital technology, especially the internet, on the trade sector in Indonesia. A significant transformation can be seen in the shift from conventional trading to electronic commerce or e-commerce, which is ...
Lumban Gaol, Elzius Fransiscus +3 more
core
Tests of a new concept - Diamond-CVD Burs
UNESP,FO,S JOSE CAMPOS,SP,BRAZILINST NACL PESQ ESP,SAO PAULO,BRAZILUNESP,FO,S JOSE CAMPOS,SP ...
Valera, M. C. +5 more
core
Gastrointestinal helminths in calves and cows in an organic milk production system [PDF]
The main aim of this study was to determine the distribution of populations of gastrointestinal helminths in lactating crossbred cows and calves during the grazing season in an organic milk production system.
Soares, João Paulo Guimarães +14 more
core +1 more source
Extension of ITU-T recommendation P.862 PESQ towards measuring speech intelligibility with vocoders
ITU-T recommendation P.862 PESQ was developed for assessing speech quality. The basic idea in PESQ is to compare a reference speech signal with the degraded signal through a psycho-acoustic model and a model of human quality comparison (cognitive model).
Wijngaarden, S.J. van +2 more
core
Improvement of PESQ based on UVS classification and syllable stability detection
Hearing perception is different to speech segment, especially to unvoiced, voiced and silence (UVS) and it is also affected by the stability of frame distortions in each syllable.
Huang, S., Liu, Y., Wang, J.
core +1 more source
Predicting the Quality of Synthesized and Natural Speech Impaired by Packet Loss and Coding Using PESQ and P.563 Models [PDF]
This paper investigates the impact of independent and dependent losses and coding on speech quality predictions provided by PESQ (also known as ITU-T P.862) and P.563 models, when both naturally-produced and synthesized speech are used. Two synthesized
Počta, P. +3 more
core +1 more source
Options for Performing DNN-Based Causal Speech Denoising Using the U-Net Architecture
Speech enhancement technology seeks to improve the quality and intelligibility of speech signals degraded by noise, particularly in telephone communications.
Hwai-Tsu Hu, Tung-Tsun Lee
doaj +1 more source
Comparison of the PESQ and STOI values against competing DL methods.
Comparison of the PESQ and STOI values against competing DL methods.
Amil Daraz (9667034) +3 more
core +1 more source

