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This work seeks to improve upon the accuracy of birdsong analysis based species recognition. We intend to accomplish this by creating a more effective bird syllable segmentation algorithms (MIRS), Support Vector machine based classifiers are used to train the features of IRS and MIRS. The experimental results show the effectiveness of the proposed algorithm.
Detecting the banknote serial number is an important task in business transaction. In this paper, we propose a new banknote number recognition method. The preprocessing of each banknote image is used to locate position of the banknote number image. Each number image is divided into non-overlapping partitions and the average gray value of each partition is used as feature vector for recognition. The...
Even if the progress of Hidden Markov Models (HMM) is huge, those models lack a discriminatory ability especially on speech recognition. In order to ameliorate the results of recognition systems, we apply Support Vectors Machine (SVM) as an estimator of posterior probabilities since they are characterized by a high predictive power and discrimination. Moreover, they are based on a structural risk...
Automatic speech recognition analysis has been an active part in computer science for more than two decades. In general, to detect an emotion, long continuous signal is needed. Relative amplitude reduces bias of glottal mutation of speech wave amplitude and obtains a normalized measure without concern of information from being distinct in feature. Nonverbal communication plays crucial role in human-human...
In this paper, a novel approach for contour based 2D shape recognition is proposed, using a class of information theoretic kernels recently introduced. This kind of kernels, based on a non-extensive generalization of the classical Shannon information theory, are defined on probability measures. In the proposed approach, chain code representations are first extracted from the contours; then n-gram...
In this paper, we describe an application of speaker verification using Romanian vowels as speaker's models in case of a small Romanian language database. Vowels models are obtained with continuous HMMs using re-training of the vowels models for every speaker. Afterwards the models are classified with the powerful technique named SVM.
This study assesses the recently proposed data-driven background dataset refinement technique for speaker verification using alternate SVM feature sets to the GMM supervector features for which it was originally designed. The performance improvements brought about in each trialled SVM configuration demonstrate the versatility of background dataset refinement. This work also extends on the originally...
Over the last years significant effort has been made to improve the performance of speech recognition. The Fisher Kernel has been suggested as good ways to combine and underlying generative model in the feature space and discriminant classifiers such as SVMs. Chinese name speech patterns are difficult to be classified especially when they are similar in pronunciation. Continuous density hidden Markov...
In this study, we present a representation based on a new 3D search technique for volumetric human poses which is then used to recognize actions in three dimensional video sequences. We generate a set of cylinder like 3D kernels in various sizes and orientations. These kernels are searched over 3D volumes to find high response regions. The distribution of these responses are then used to represent...
In the noisy environment, the performance of speech recognition system may become worse to some extent. In order to solve this problem, this paper used the zero-crossings with peak amplitudes (ZCPA) features as speech feature parameters, which are based on human hearings property. The extraction method of ZCPA features is that calculating the unward zero-crossing rate of speech signal gets frequency...
Gene Recognition is one of the important problems in bioinformatics, including a lot of classic experiments, theory and arithmetic research. The E. coli K12 whole genome sequence and gene mark files from GeneBank were analyzed for later gene prediction. First the gene four distribution types were analyzed. Then the non-coding samples were generated from intervals between the discrete genes and the...
A method is described for classifying near-infrared spectroscopy (NIRS) signals measured for motor imagery and/or execution using the left or right hand. The measurement time intervals and the signal channels are used as features. The signals are discriminated using a support vector machine. Experiments demonstrated that this method has a higher generalization capability than a previous method for...
We propose a new method for the detection of evoked potentials that combines a generative model and a discriminative classifier. The method is a variant of the support vector machine (SVM), which uses the Fisher kernel. The kernel function is derived from a generative statistical model known as mixed effects model (MEM). Instead of arbitrarily selecting the Gaussian kernel for the SVM, we exploit...
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...
To improve the generalization ability of the machine learning and solve the problem that recognition rates of the speech recognition system become worse in the noisy environment, a modified Gaussian kernel function which may pay attention to the similar degree between sample space and feature space is proposed. In this paper, used the modified Gaussian kernel support vector machine to a speech recognition...
Part of speech (POS) tagging is the task of labeling each word in a sentence with its appropriate syntactic category called part of speech. POS tagging is a very important preprocessing task for language processing activities. This paper reports about task of POS tagging for Bengali using support vector machine (SVM). The POS tagger has been developed using a tagset of 26 POS tags, defined for the...
Conventional approaches to automatic image annotation usually suffer from two problems: (1) They cannot guarantee a good semantic coherence of the annotated words for each image, as they treat each word independently without considering the inherent semantic coherence among the words; (2) They heavily rely on visual similarity for judging semantic similarity. To address the above issues, we propose...
In pattern recognition, support vector machines (SVM) as a discriminative classifier and Gaussian mixture model as a generative model classifier are two most popular techniques. Current state-of-the-art systems try to combine them together for achieving more power of classification and improving the performance of the recognition systems. Most of recent works focus on probabilistic SVM/GMM hybrid...
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