5 accepted papers
Eulerian video magnification (EVM) has progressed to magnify subtle motions with a target frequency even under the presence of large motions of objects. However, existing EVM methods often fail to produce desirable results in real videos due to (1) mis-extracting subtle motions with a non-target fre…
This paper describes a novel end-to-end automatic speech recognition (ASR) method that takes into consideration long-range sequential context information beyond utterance boundaries. In spontaneous ASR tasks such as those for discourses and conversations, the input speech often comprises a series of…
This paper presents a novel emotion classification method for natural speech. One of the problems in the state-of-the-art method based on Deep Neural Network (DNN) is the paucity of the training data compared to model complexity. To solve this problem, this paper utilizes the ambiguous emotional utt…
Constructing deep neural network (DNN) acoustic models from limited training data is an important issue for the development of automatic speech recognition (ASR) applications that will be used in various application-specific acoustic environments. To this end, domain adaptation techniques that train…
Parallel phonetically aware deep neural networks (PPA-DNNs) and long short-term memory recurrent neural networks (PPA-LSTM-RNNs) to enhance frame-by-frame discriminative modeling of spoken language identification are proposed. This idea is inspired by traditional systems based on parallel phoneme re…