The Infona portal uses cookies, i.e. strings of text saved by a browser on the user's device. The portal can access those files and use them to remember the user's data, such as their chosen settings (screen view, interface language, etc.), or their login data. By using the Infona portal the user accepts automatic saving and using this information for portal operation purposes. More information on the subject can be found in the Privacy Policy and Terms of Service. By closing this window the user confirms that they have read the information on cookie usage, and they accept the privacy policy and the way cookies are used by the portal. You can change the cookie settings in your browser.
Word segmentation is the first step in Chinese natural language processing, and the error caused by word segmentation can be transmitted to the whole system. In order to reduce the impact of word segmentation and improve the overall performance of Chinese short text classification system, we propose a hybrid model of character-level and word-level features based on recurrent neural network (RNN) with...
There are several papers about pseudo dynamic methods used in signature authentication. Recently, the gray scale features local binary pattern(LBP) originate from texture analysis has been widely used in signature verification system with advantage of robustness to illumination change. The major problem of LBP is its sensitivity to noise, hence many solutions has been applied to solve this problem...
Because traditional prediction algorithm can not accurately forecast long-term electricity load, chaos SVM prediction algorithm was introduced and some of its characteristics were discussed. The kernel function was chosen under the guidance of the geometric information. The experiment shows that the algorithm is more accurate and effective than the others.
In this paper, we propose a discriminative method for the acoustic feature based language recognizer, which is a modification of the polynomial expansion in generalized linear discriminant sequence (GLDS) kernel. It is inspired by the Gaussian mixture model-support vector machine (GMM-SVM) system which has been successfully used in both speaker and language recognition. Because of the restriction...
With the fast development of high-speed network and digital video recording technologies, broadcast video has been playing a more and more important role in our daily life. In this paper, we propose a novel news story segmentation scheme which can segment broadcast video into story units with multi-modal information fusion (MMIF) strategy. Compared with traditional methods, the proposed scheme extracts...
In this paper we first introduce four kinds of modification of Symmetric Scoring [1] which produce likelihood ratios that do not need to be explicitly normalized, i.e. T-norm, Z-norm. To solve the numerical problem caused by large covariance matrix calculation, we propose three solutions and present the result for each of them according to different modifications. Then we introduce a new kernel function...
In the task of mispronunciation detection, the cross-speaker degradation and some other confusing nuisances are the challenging problems demanding prompt solution. In this paper, we will attempt to remove the non-pronunciation variations in the GLDS-SVM expansion space by using nuisance attribute projection strategy, in order to increase the separating capacity between different phoneme instances...
The bearingless permanent magnet synchronous motor is a strong-coupled nonlinear system. To solve the difficult problem of precise decoupling control, the theory and method of direct torque control of traditional permanent magnet synchronous motor are applied to the torque control of a bearingless permanent magnet synchronous motor in the paper. With the reference of direct torque control of traditional...
In this paper we propose a Round Trip Translation (RTT) based approach to sentence-level confidence estimation (CE) for spoken language translation without the assistant of reference translations generated by human. A number of novel RTT based features are introduced to reflect the quality of spoken language translation in more detail. After combing various kinds of features together, support vector...
This paper presents experiments using several vector space models in Automated Essay Scoring (AES). Firstly, we compare four different Vector Space Models (VSM) which are the Word-based Vector Space Model (W-VSM), the Weight Adapted Word-based Vector Space Model (WAW-VSM), the Latent Semantic-based Vector Space Model (LS-VSM) and the Sequence Latent Semantic-based Vector Space Model (SLS-VSM). The...
In this paper, we propose a novel discriminant analysis method, called Minimal Distance Maximization (MDM). In contrast to the traditional LDA, which actually maximizes the average divergence among classes, MDM attempts to find a low-dimensional subspace that maximizes the minimal (worst-case) divergence among classes. This ``minimal" setting solves the problem caused by the ``average" setting...
Automatic stress detection is important for both speech understanding and natural speech synthesis. In this paper, we develop hierarchical model based boosting classification and regression tree (CART) to detect Mandarin stress by using acoustic evidence and text information. When comparing with previous proposed method at the same training and test sets, there are 2.52% and 1.09% absolute accuracy...
In this paper, a novel image forensics method is proposed to detect manual blurred edges from a tampered image. Firstly, the image edges are analyzed by using non-subsampled contourlet transform. Then the differences between the normal edge and the blurred edge are extracted by researching phase congruency and prediction-error image. After that, the features are used to train the SVM, by which the...
In this study, we combine the Mandarin characteristics with Mandarin acoustic attribute and text information and use hierarchical model based ensemble machine learning to predict Mandarin pitch accent. Our model could make the best of advantages of prosody hierarchical structure and ensemble machine learning. When comparing our model with classification and regression tree (CART), support vector machine...
Automatic assessment of word stress error is an integral part for oral language grading system. However, problems that the property of vowels depends on its context information and the data sparseness of different vowel class are yet to be solved. This paper shall briefly introduce a hybrid method consisting of both traditional prosodic features and proposed context dependent strategies. In classification...
This paper presents a new approach that uses linguistic knowledge and pronunciation space for automatic detection of typical phone-level errors made by non-native speakers of mandarin. Firstly, linguistic knowledge of common learner mistakes is embedded in the calculation of log-posterior probability and the revised log-posterior probability (RLPP) is regarded as the measure of mispronunciation; secondly,...
Mispronunciation detection is an important component in computer assisted language learning (CALL) system. In this work, we introduce an efficient GLDS-SVM based detection method, which is successfully used in language and speaker identification systems, and combine it with traditional methods. The main ideas include: extended MFCC features with normalized formant trajectory information, and then...
In this paper we propose a scheme using image quality metrics and multi-class support vector machine to identify steganographic domains. Firstly, we classify stegnographic domains into four, i.e. spatial domain, DCT domain, DWT domain and ICA domain. Then we analyze total 26 image quality measures summarized by Ismail Avcibas and choose eight sensitive features based on the analysis of variance technique...
Support Vector Machines have merged as a pattern classifier and have been shown to be successful in some tasks in the realm of speech processing. This paper explores the issues involved in applying SVMs to asymmetrical situations, namely. beavy sample ratio bias between different classes and different costs for different types of misclassification error. We also present our revisions on the SMO algorithm...
How to extract more identity-related information from speech signal is a crucial problem in the research of speaker authentication. In this paper, we present a novel framework for combining Speaker Verification (SV) System with Verbal Information Verification (VIV) System by proposing the nonstandard-SVM method. The scheme of nonstandard-SVMs makes it possible to adjust the tradeoff between False...
Set the date range to filter the displayed results. You can set a starting date, ending date or both. You can enter the dates manually or choose them from the calendar.