Artificial intelligence (AI) has achieved remarkable breakthroughs in a wide range of fields,
ranging from speech processing, image classification to drug discovery. This is driven by the …

A huge amount of research has been done in the field of speech signal processing in recent
years. In particular, there has been increasing interest in the automatic speech recognition …

Music information retrieval (MIR) has witnessed rapid advances in various tasks like musical
similarity, music genre classification (MGC), etc. MGC and audio tagging are approached …

Speech emotion recognition (SER) is a challenging task that requires to learn suitable
features for achieving good performance. The development of deep learning techniques …

Abstract Generative Adversarial Networks (GANs) are a powerful class of generative models
in the deep learning community. Current practice on large-scale GAN training utilizes large …

Speech recognition is a natural language processing task that involves the computerized
transcription of spoken language in real time. Numerous studies have been conducted on …

Data privacy and protection is a crucial issue for any automatic speech recognition (ASR)
service provider when dealing with clients. In this paper, we investigate federated acoustic …

As deep learning models are usually massive and complex, distributed learning is essential
for increasing training efficiency. Moreover, in many real-world application scenarios like …

A new penalty-free neural network method, PFNN-2, is presented for solving partial
differential equations, which is a subsequent improvement of our previously proposed PFNN …

Physical rehabilitation techniques during the treatment of clinical pathology are one of the
most challenging areas for the medical structure, patients, and families. In large and …