Deep learning for environmentally robust speech recognition: An overview of recent developments
Eliminating the negative effect of non-stationary environmental noise is a long-standing
research topic for automatic speech recognition but still remains an important challenge …
research topic for automatic speech recognition but still remains an important challenge …
[PDF][PDF] A review of deep learning research
R Mu, X Zeng - KSII Transactions on Internet and Information …, 2019 - koreascience.kr
With the advent of big data, deep learning technology has become an important research
direction in the field of machine learning, which has been widely applied in the image …
direction in the field of machine learning, which has been widely applied in the image …
[書籍][B] Automatic speech recognition
Automatic Speech Recognition (ASR), which is aimed to enable natural human–machine
interaction, has been an intensive research area for decades. Many core technologies, such …
interaction, has been an intensive research area for decades. Many core technologies, such …
Discriminatively trained recurrent neural networks for single-channel speech separation
This paper describes an in-depth investigation of training criteria, network architectures and
feature representations for regression-based single-channel speech separation with deep …
feature representations for regression-based single-channel speech separation with deep …
Deep learning reservoir porosity prediction based on multilayer long short-term memory network
The cost of obtaining a complete porosity value using traditional coring methods is relatively
high, and as the drilling depth increases, the difficulty of obtaining the porosity value also …
high, and as the drilling depth increases, the difficulty of obtaining the porosity value also …
Speech emotion recognition based on an improved brain emotion learning model
ZT Liu, Q **e, M Wu, WH Cao, Y Mei, JW Mao - Neurocomputing, 2018 - Elsevier
Human-robot emotional interaction has developed rapidly in recent years, in which speech
emotion recognition plays a significant role. In this paper, a speech emotion recognition …
emotion recognition plays a significant role. In this paper, a speech emotion recognition …
Multimodal affective dimension prediction using deep bidirectional long short-term memory recurrent neural networks
This paper presents our system design for the Audio-Visual Emotion Challenge (AV^+EC
2015). Besides the baseline features, we extract from audio the functionals on low-level …
2015). Besides the baseline features, we extract from audio the functionals on low-level …
A deep learning approach for aircraft trajectory prediction in terminal airspace
Current state-of-the-art trajectory methods do not perform well in the terminal airspace that
surrounds an airport due to its complex airspace structure and the frequently changing flight …
surrounds an airport due to its complex airspace structure and the frequently changing flight …
Context-sensitive learning for enhanced audiovisual emotion classification
Human emotional expression tends to evolve in a structured manner in the sense that
certain emotional evolution patterns, ie, anger to anger, are more probable than others, eg …
certain emotional evolution patterns, ie, anger to anger, are more probable than others, eg …
Deep long short-term memory adaptive beamforming networks for multichannel robust speech recognition
Far-field speech recognition in noisy and reverberant conditions remains a challenging
problem despite recent deep learning breakthroughs. This problem is commonly addressed …
problem despite recent deep learning breakthroughs. This problem is commonly addressed …