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Unsupervised phone segmentation means that the phone boundaries in an utterance can be detected without a prior knowledge about the text contents. Usually, a spectral change in the speech signal implies the existence of a phone boundary. In this paper, the Delta Spectral Function (DSF) is defined for each frame to represent the variation of band energy for a specific band. Then a number of bands that...
The reliable detection of salient acoustic-phonetic cues in speech signal plays an important role in speech recognition based on speech landmarks. Once speech landmarks are located, not only can phone recognition be performed, but other useful information can also be derived. This paper focuses on the detection of burst onset landmarks, which are crucial to the recognition of stop and affricate consonants...
This papers presents a weakly supervised method to simultaneously address object localization and recognition problems. Unlike prior work using exhaustive search methods such as sliding windows, we propose to learn category and image-specific visual words in image collections by extracting discriminating feature information via two different types of support vector machines: the standard L2-regularized...
We propose a novel method to address object localization in a weakly supervised framework. Unlike prior work using exhaustive search methods such as sliding windows, we advocate the use of visual attention maps which are constructed by class-specific visual words. Based on dense SIFT descriptors, these visual words are selected by support vector machines and feature ranking techniques. Therefore,...
Reliably detecting salient phonetic-acoustic cues plays an important role in speech recognition based on speech landmarks. Once these speech landmarks are located, not only phone recognition can be performed but some other useful information can be derived as well. This paper focuses on the topic of detecting burst onset landmark, an important phonetic characteristic in stops and affricates. The proposed...
The non-stationary behavior makes stops classification one of worthy examining subject in the speech community. Over several decades, many researchers have sorted out a list of acoustic properties that are useful to identify a stop. In this paper, we extract features that are sufficient to represent the important acoustic properties of stops, like statistic moments of the burst spectrum. In combining...
Sunspot number time series, as a multivariable, strong coupling and nonlinear time series, has encountered troubles to describe its changes rules with modeling method owing to great complexity of sunspot number change. The main aim of this study is to develop a novel prediction method, based on the Quantum Neural Networks, which is composed of some quantum neurons and traditional neurons based on...
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