School of Computer and Information Engineering Details Findings in Pattern Recog nition and Artificial Intelligence (Speech Fatigue Recognition Under Small Sampl es Based On Generative Adversarial Networks and Blstm)
School of Computer and Information Engineering Details Findings in Pattern Recog nition and Artificial Intelligence (Speech Fatigue Recognition Under Small Sampl es Based On Generative Adversarial Networks and Blstm)
By a News Reporter-Staff News Editor at Robotics & Machine Learning DailyNews Daily News – New research on Machine Learning - Pat tern Recognition and Artificial Intelligenceis the subject of a report. Accordi ng to news reporting out of Nantong, People’s Republic of China, byNewsRx edito rs, research stated, “To address the issue of low accuracy in speech fatigue rec ognition(SFR) under small samples, a method for small-sample SFR based on gener ative adversarial networks(GANs) is proposed. First, we enable the generator an d discriminator to adversarially train and learn thefeatures of the samples, an d use the generator to generate high-quality simulated samples to expand ourdat aset.”
Key words
Nantong/People’s Republic of China/Asi a/Pattern Recognition and Artificial Intelligence/Machine Learning/School of Computer and Information Engineering
NETL
NSTL