J
Jan Skoglund
Researcher at Google
Publications - 115
Citations - 2309
Jan Skoglund is an academic researcher from Google. The author has contributed to research in topics: Speech coding & Signal. The author has an hindex of 21, co-authored 108 publications receiving 1796 citations. Previous affiliations of Jan Skoglund include Chalmers University of Technology.
Papers
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Proceedings ArticleDOI
LPCNET: Improving Neural Speech Synthesis through Linear Prediction
Jean-Marc Valin,Jan Skoglund +1 more
TL;DR: This article proposed LPCNet, a WaveRNN variant that combines linear prediction with recurrent neural networks to improve the efficiency of speech synthesis, achieving high quality speech synthesis with a complexity under 3 GFLOPS.
Journal ArticleDOI
Vector quantization based on Gaussian mixture models
Per Hedelin,Jan Skoglund +1 more
TL;DR: It is found that an optimal single-stage VQ can operate at approximately 3 bits less than a state-of-the-art LSF-based 2-split VQ.
Proceedings ArticleDOI
Wavenet Based Low Rate Speech Coding
W. Bastiaan Kleijn,Felicia S. C. Lim,Alejandro Luebs,Jan Skoglund,Florian Stimberg,Quan Wang,Thomas C. Walters +6 more
TL;DR: In this article, a WaveNet generative speech model is used to generate high quality speech from the bit stream of a standard parametric coder operating at 2.4 kb/s.
Journal ArticleDOI
ViSQOL: an objective speech quality model
TL;DR: ViSQOL is shown to offer a useful alternative to POLQA in predicting speech quality in VoIP scenarios and has a wider application and robustness to conditions than PESQ or more trivial distance metrics.
Proceedings ArticleDOI
iLBC - a linear predictive coder with robustness to packet losses
Soren Vang Andersen,Willem Bastiaan Kleijn,Roar Hagen,J. Linden,Manohar N. Murthi,Jan Skoglund +5 more
TL;DR: This paper presents mean opinion scores for the iLBC codec and shows by means of signal examples how the nature of degradation in a predictive codec based on frame-independent long-term prediction differs from that of traditional CELP codecs.