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Researches indicate that electroencephalography (EEG) can be used to classify data of imagined speech. It can be further utilized to develop speech prosthesis and synthetic telepathy systems. The objective of this paper is to improve the classification performance in imagined speech by selecting the features that extract maximum discriminatory information from the data. The features extracted are...
Microblogging sites such as Twitter and Weibo are increasingly being used to enhance situational awareness during various natural and man-made disaster events such as floods, earthquakes, and bomb blasts. During any such event, thousands of microblogs (tweets) are posted in short intervals of time. Typically, only a small fraction of these tweets contribute to situational awareness, while the majority...
The analysis of various components of the Electroglottograph (EGG) signal, obtained after Ensemble Empirical Mode Decomposition (EEMD) is the primary objective of this paper. The ability of EEMD to detect intermittent high frequency data embedded in the data of lower frequency is exploited to segregate the Epoch locations and the Periodic nature of EGG signal. The dyadic filterbank property of EEMD...
The proposed identification system for mixed anuran vocalizations is to provide the public to easily consult online. The raw mixed anuran vocalization samples are first filtered by noise removal, high frequency compensation, and discrete wavelet transform techniques in order. An adaptive end-point detection segmentation algorithm is proposed to effectively separate the individual syllables from the...
The emerging background for automatic extracting collocations is generally stated in this article. That How to extracting collocations as well as the advantage and disadvantage of existing methods are particularized. The review and comment for domestic and international present research status are given. And the problem of existing technic and solving methods are discussed.
In this paper we design a system that adopts a novel approach for emotional classification from human dialogue based on text and speech context. Our main objective is to boost the accuracy of speech emotional classification by accounting for the features extracted from the spoken text. The proposed system concatenates text and speech features and feeds them as one input to the classifier. The work...
Extraction of bilingual audio and text data is crucial for designing Speech to Speech (S2S) systems. In this work, we propose an automatic method to segment multilingual audio streams from movies. In addition, the audio streams are aligned with the corresponding subtitles. We found that the proposed method gives 89% perfectly segmented bilingual audio and 6% partially segmented bilingual audio. In...
To improve the performance of call-reason analysis at contact centers, we introduce a novel method to extract call-reason segments from dialogs. It is based on the following two characteristics of contact center conversations; 1) customers state their requests at the beginning of the calls, 2) agents tend to use typical phrases at the end of the call-reason segments. Our proposal acquires these typical...
Ambulatory devices can be used to detect heart diseases and save lives in critical time. These devices are based on sound classification that usually adopts a suitable data mining algorithm. This paper investigates the performance of Support Vector Machine (SVM) and Gaussian Mixture Model (GMM) classifiers in classifying sound samples. SVM classifier makes use of a linearly separable hyperplane to...
The field of Text Mining has evolved over the past years to analyze textual resources. However, it can be used in several other applications. In this research, we are particularly interested in performing text mining techniques on audio materials after translating them into texts in order to detect the speakers' emotions. We describe our overall methodology and present our experimental results. In...
Automatic extraction of hypernym-hyponym pairs has been done in many researches. But none is described as an automatic method to incorporate the result to Word Net or on Word Net building. This paper proposes a method to automatically acquire hypernym-hyponym pairs for Word Net building by utilizing a monolingual dictionary and Lesk Word Sense Disambiguation or Lesk WSD to deliver tagged pairs. This...
In this work, we investigate sentiment mining of Arabic text at both the sentence level and the document level. Existing research in Arabic sentiment mining remains very limited. For sentence-level classification, we investigate two approaches. The first is a novel grammatical approach that employs the use of a general structure for the Arabic sentence. The second approach is based on the semantic...
It is an investigative purpose to acquire the event information in the municipality website and extraction information is converted into the XML form of the RDF model. There is a problem that the extraction performance is controlled by the structure of the HTML tag though there is Web-wrapper method that uses the HTML tag as an information extraction technique on the Web page. In this paper, we propose...
Spoken emotion recognition is an interesting and challenging subject. In this paper, a new feature extraction method based on local Fisher discriminant analysis (LFDA) is proposed for spoken emotion recognition. LFDA is used to extract the low-dimensional discriminant embedded feature data from high-dimensional emotional speech features on spoken emotion recognition tasks. The performance of LFDA...
The main objective of this paper is to explore the effectiveness of perceptual features for performing isolated digits and continuous speech recognition. The proposed perceptual features are captured and training models are developed by K-means clustering procedure. Speech recognition system is evaluated on clean and noisy test speeches and the experimental results reveal the performance of the proposed...
Automatic recognition of Dialog-act (DA) is one of the most important processes in understanding spontaneous dialog. Most existing studies have been working on how to use various classifying methods in DA recognition; meanwhile, less attention has been paid to feature selection specifically. This paper introduces several textual features for DA recognizing, and proposes a novel usage for sentence...
This paper presents the first work in the task of author profiling for Vietnamese blogs. This task is important in threat identification and marketing intelligence. We have developed a Vietnamese Blog Profiling framework to automatically predict age, gender, geographic origin and occupation of weblogs' authors purely based on language use. The experiments on the blogs corpus we collected show very...
The paper provides a novel approach to emotion recognition from facial expression and voice of subjects. The subjects are asked to manifest their emotional exposure in both facial expression and voice, while uttering a given sentence. Facial features including mouth-opening, eye-opening, eyebrow-constriction, and voice features including, first three formants: F1, F2, and F3, and respective powers...
This paper focuses on the emotional Chinese whispered speech. The auditory perception is to demonstrate that whispered speech can also carry emotional information as the voiced one do. The experiment carried on the single tonal whispered Mandarin shows that the falling-raising and falling tones could transfer feelings better than the high-level and raising ones. The accuracy of perception indicates...
Indian languages such as Hindi is phonetic in nature. The text-to-speech (TTS) system for Hindi, exploits the phonetic nature of Hindi. The algorithm developed by us involves analysis of a sentence in terms of words and then symbols involving combination of pure consonants and vowel technique. Wave files are being merged as per the requirement to generate the modified consonants influenced by matras,...
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