Due to the explosive growth of the web pages, centralized crawlers are no longer sufficient to run on the web efficiently. There are many distributed crawlers in wide use;however, none of them is suitable for template...
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Speaker adaptive test normalization (ATnorm) is the most effective approach of the widely used score normalization in text-flldependent speaker verification, which selects speaker adaptive impostor cohorts with an e...
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Speaker adaptive test normalization (ATnorm) is the most effective approach of the widely used score normalization in text-flldependent speaker verification, which selects speaker adaptive impostor cohorts with an extra development corpus in order to enhance the recognition performance. In this paper, an improved implementation of ATnorm that can offer overall significant advantages over the original ATnorm is presented. This method adopts a novel cross similarity measurement in speaker adaptive cohort model selection without an extra development corpus. It can achieve a comparable performance with the original ATnorm and reduce the computation complexity moderately. With the full use of the saved extra development corpus, the overall system performance can be improved significantly. The results are presented on NIST 2006 Speaker recognition Evaluation data corpora where it is shown that this method provides significant improvements in system performance, with relatively 14.4% gain on equal error rate (EER) and 14.6% gain on decision cost function (DCF) obtained as a whole.
Blog and microblog have become one of the most popular applications which individuals could be the message source. Therefore, interactivities between individuals have been largely enhanced in today's world. In ter...
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Traditional multi-class classification methods based on Fisher kernel combine generative models such as Gaussian mixture models(GMMs)of all the classes ***,the combination generates high dimensional feature vectors an...
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Traditional multi-class classification methods based on Fisher kernel combine generative models such as Gaussian mixture models(GMMs)of all the classes ***,the combination generates high dimensional feature vectors and leads to large *** this paper,a new classification method is *** method adopts an intelligent feature space selection strategy by clustering similar Gaussian mixtures in order to reduce the feature *** classification experiments show that the proposed method is more accurate and effective with less computation compared with traditional methods.
To solve the frame delay problem and match the previous frame,Plapous et al.[IEEE Transactions on Audio,Speech,and Language Processing,2006,14(6):2098–2108]introduced a novel approach called two-step noise reduction(...
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To solve the frame delay problem and match the previous frame,Plapous et al.[IEEE Transactions on Audio,Speech,and Language Processing,2006,14(6):2098–2108]introduced a novel approach called two-step noise reduction(TSNR)technique to improve the performance of the speech enhancement ***,TSNR approach results in spectral peaks of short duration and the broken spectral outlier,which degrade the spectral characteristics of the *** solve this problem,a cepstral smoothing step is added in order to remove these spectral peaks brought by TSNR *** analysis shows that the proposed approach can effectively smooth the spectral peaks and keep the spectral outlier so as to protect the speech *** results also show that the proposed approach can bring significant improvement compared to decision-directed(DD)and TSNR approaches,especially in non-stationary noisy environments.
Microblog is a large-scale information sharing platform where intensive communications are taking place through interactive user behaviors. Previous studies have analyzed and modeled a series of traditional communicat...
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Open relation extraction is the task to extract relational facts without pre-defined relation types from open-domain corpora. However, since there are some hard or semi-hard instances sharing similar context and entit...
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Zero-shot relation extraction aims to identify novel relations which cannot be observed at the training stage. However, it still faces some challenges since the unseen relations of instances are similar or the input s...
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Active Learning (AL) is designed to aid the labor-intensive process of training acoustic model for speech recognition. In AL, only the most informative training samples are selected for manual annotation. Thus, how to...
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Hot events detection in text streams has drawn increasing attention in recent sequential data mining works. Different from traditional TDT task which find all the real events' cluster, hot events detection only id...
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