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Automatic Speech Attribute Transcription (ASAT), an ITR project sponsored under the NSF grant (IIS-04-27113), and Spoken Information Retrieval by Knowledge Utilization in Statistical Speech Processing (SIRKUS), a project funded by the VERDIKT programme at the Research Council of Norway, are two research projects carried out at Georgia Institute of Technology and at Norwegian University of Science...
Many studies have tried to search useful information on the Internet by meaningful terms or words. The performance of these approaches is often affected by the accuracy of unknown word extraction and POS tagging, while the accuracy is affected by the size of training corpora and the characteristics of language. This work proposes and develops a method that concentrates on tagging the POS of Chinese...
In this paper, we compare the experimental results for Tamil online handwritten character recognition using HMM and Statistical Dynamic Time Warping (SDTW) as classifiers. HMM was used for a 156-class problem. Different feature sets and values for the HMM states & mixtures were tried and the best combination was found to be 16 states & 14 mixtures, giving an accuracy of 85%. The features used...
Transcription of music is the process of generating a symbolic representation such as a score sheet or a MIDI file from an audio recording of a piece of music. A statistical machine learning approach for detecting note onsets in polyphonic piano music is presented. An area from the spectrogram of the sound is concatenated into one feature vector. A cascade of boosted classifiers is used for dimensionality...
This paper presents a novel method for learning classes of temporal sequences using a bag-of-features approach. We define a temporal sequence as a bag of temporal features and show how this representation can be used for the recognition and segmentation of temporal events. A codebook of temporal descriptors, representing the local temporal texture, is automatically constructed from a set of sample...
This paper proposes a new radical-based approach for online handwritten chinese character recognition. The approach is novel in three respects: statistical classification of radicals, over-segmentation of characters into candidate radicals, and lexicon-driven recognition of characters. Currently, we have applied the approach to Chinese characters of left-right structure and are extending to other...
Word sense tagging is one of the difficult points in the field of natural language processing. This paper has studied Chinese word sense tagging with the hidden Markov model (HMM) based on semantic case amelioration in order to make use of statistical methods. Firstly,word sense tagging to the real text for application was carried on the HowNet, which is a kind of repository and regards the concept,...
Port state control (PSC) inspection is the most important mechanism to ensure world marine safe. Recently, some SVM-based risk assessment systems have been presented in the world. They estimate the risk of each candidate ship based on its generic factors and history inspection factors to select high-risk one before conducting on-board PSC inspection. However, how to improve the performance of the...
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