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We propose to use a feature representation obtained by pairwise learning in a low-resource language for query-by-example spoken term detection (QbE-STD). We assume that word pairs identified by humans are available in the low-resource target language. The word pairs are parameterized by a multi-lingual bottleneck feature (BNF) extractor that is trained using transcribed data in high-resource languages...
Recently, deep and/or recurrent neural networks (DNNs/RNNs) have been employed for voice conversion, and have significantly improved the performance of converted speech. However, DNNs/RNNs generally require a large amount of parallel training data (e.g., hundreds of utterances) from source and target speakers. It is expensive to collect such a large amount of data, and impossible in some applications,...
A large number of videos are generated and uploaded to video websites (like youku, youtube) every day and video websites play more and more important roles in human life. While bringing convenience, the big video data raise the difficulty of video summarization to allow users to browse a video easily. However, although there are many existing video summarization approaches, the key frames selected...
This brief develops a novel just-in-time (JIT) learning-based soft sensor for modeling of industrial processes. The recorded data is assumed to exhibit non-Gaussian signal components, which are extracted by a non-Gaussian regression (NGR) technique. Unlike previous work on JIT modeling which uses distance-based similarity measure for local modeling, this brief introduces a new similarity measure for...
This paper introduces a novel Just-In-Time (JIT) learning based soft sensor for modeling of non-Gaussian process. Most of JIT modeling uses distance based similarity measure for local modeling, which may be inappropriate for many industrial processes exhibiting non-Gaussian behaviors. Since most of industrial processes are non-Gaussian, a non-Gaussian regression (NGR) technique is used to extract...
In network intrusion detection systems, feature extraction plays an important role in a sense of improving classification performance and reducing the computational complexity. Principle Component Analysis and Independent Component Analysis are both common feature extraction methods currently. This paper proposed a novel feature extraction method for network intrusion detection and the core of this...
This paper presents the design of a decentralized storage scheme to support multi-dimensional range queries over sensor networks. We build a distributed k-d tree based index structure over sensor network, so as to efficiently map high dimensional event data to a two-dimensional space of sensors while preserving the proximity of events. We propose a dynamic programming based methodology to control...
The extension principle for n-ary operations is suitable for operations on different fuzzy numbers, while the unreasonable results will be concluded when it is used for operations on several fuzzy numbers with same fuzziness source. A concept called fuzziness source is proposed. Then, the unit fuzzy number is defined to simplify the operation. The operation rules are respectively constructed for fuzzy...
For evaluating the influence degree of insolation and pumping head-flow rate characteristic to photovoltaic (PV) pumping system, this paper carried out experiments, established mathematical models of system components, and simulated the system efficiency of PV pumping system with MATLAB/Simulink tools, some conclusions about system configuration optimizing were deduced at the end of this paper.
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