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With the increasing stress in working and studying, mental health becomes a major problem in the current social research. Generally, researchers can analyze psychological health states by using social perception behavior. The speech signal is an important research direction in this domain. It objectively assesses the mental health of social groups through the extraction and fusion of speech features...
To reduce data-storage costs and enhance high accuracy of industrial process fault detection, a data driven fault diagnosis method is proposed based on diffusion maps and hidden Markov model. Firstly, the correlation dimension of sample data is calculated. Secondly, the high-dimensional eigenvectors are extracted into low-dimensional manifold space by diffusion maps. Finally, the low-dimensional eigenvectors...
In this paper, the multidimensional phonological feature structure of Arabic is investigated. Our goal is to assess the performance of statistical and connectionist approaches in performing the complex mappings between distinctive phonetic features (DPF) and associated acoustic cues. The present study explores the mapping between 29 phonological voicing, place, and manner features and Mel-frequency...
Generative models of 3D human motion are often restricted to a small number of activities and can therefore not generalize well to novel movements or applications. In this work we propose a deep learning framework for human motion capture data that learns a generic representation from a large corpus of motion capture data and generalizes well to new, unseen, motions. Using an encoding-decoding network...
In this paper, we made the emotion recognition for Romanian language using EMO-IIT database with seven emotions (joy, sadness, fury, neutral tone, anxiety, disgust and boredom). Compared to our previous studies we introduced two new emotions: disgust and boredom and a new set of sentences in order to express better the emotional states. The best recognition rate of emotions is around 75% and was obtained...
In this article, we propose an automatic method for the detection and extraction of the tumor on mammogram images. Most methods of detection of a tumor require the extraction of a large number of texture features from multiple calculations. The study first examines a technique of preprocessing images to obtain the Otsu thresholding method to eliminate items that do not belong in. After performing...
Background music plays an important role in making user-generated video more colorful and attractive. One of current research on automatic background music recommendation is the correlation-based approach in which the correlation model between visual and music features is discovered from training data and is utilized to recommend background music for query video. While existing correlation-based approaches...
Recent trends and also statistics show that the hashing concept has been gaining importance because its application lies in the area of authentication, retrieval and recognition. The proposed hashing method CCQ-CSLBP (Compressed CSLBP with Correlation Coefficient) for authentication utilized correlation coefficient as a weight factor in CSLBP. CSLBP is a texture operator, whose performance is better...
The term gender identification deals with finding out the gender of a person from his or her voice. Gender identification has been implemented in several Automatic Speaker Recognition (ASR) systems and has proved to be of great significance. The use of gender identification in today's technology makes it easier for user authentication and identification in high security systems. In this paper, we...
With the increase of multi media technology and internet there is a rapid growth in storing and retrieving of documents. Government has taken several methods for documents to scan and stored digitally for future use. Even though the documents are available in the digital format, but it is very difficult to search for a single word or phrase. Traditional optical character recognition techniques (OCR)...
Recently CCTV-based behavior recognition have gained considerable attention in the transportation surveillance systems to identify normalities, such as traffic jams, accidents, and dangerous driving. An improved method is presented in this paper for the traffic behavior surveillance system by discovering more highly specific features based on the trajectory information. The multiple sparse feature...
We have developed flexible, active, multiplexed recording devices for high resolution recording over large, clinically relevant areas in the brain. While this technology has enabled a much higher-resolution view of the electrical activity of the brain, the analytical methods to process, categorize and respond to the huge volumes of data produced by these devices have not yet been developed. In our...
In general we categorize all malicious codes that potentially can harm a single or network of computers into malware groups. With great progress in enhancing virus development kit and various kind of malware appeared today, and increasing in number of web networks users, malwares spreading out rapidly in all aspect of computers systems. The main approach for finding and detecting malware today, is...
With the ubiquitous Internet applications brought by widespread popularity of smart device, an exhaustive understanding of user behavior is becoming essential for Internet Service Providers (ISPs) to implement network management and resource optimization. Existing researches on mobile user behavior principally focus on studying people's application interests and mobility properties, especially characterizing...
Network intrusions may illicitly retrieve data/information, or prevent legitimate access. Reliable detection of network intrusions is an important problem, misclassification of an intrusion is an issue in and of itself reducing overall accuracy of detection. A variety of potential methods exist to develop an improved system to perform classification more accurately. Feature selection is one potential...
E-commerce business is becoming more and more popular as the number of customers shopping online is increasing every day. Companies ask their customers to review products and services offered by them over their websites. For the big companies, the number of reviews could be in the thousands. So it is almost impossible for any company to read these reviews manually and find out whether customers liked...
Speech and hand gestures form a composite communicative signal that boosts the naturalness and affectiveness of the communication. We present a multimodal framework for joint analysis of continuous affect, speech prosody and hand gestures towards automatic synthesis of realistic hand gestures from spontaneous speech using the hidden semi-Markov models (HSMMs). To the best of our knowledge, this is...
This paper presents a system for automatic bird identification, which uses audio input. The experiments have been conducted on three groups of birds, which were created basing finishing on classification, the system is fully automated. The main problem in automatic bird recognition (ABR) is the choice of proper features and classifiers. Identification has been made using two classifiers-kNN (k Nearest...
Onset detection is the foundation and key to high-level audio processing like music retrieval and transcription. Research shows that the detection algorithm is associated with instrument category, and high accuracy can be achieved in instrument recognition studies. Thus the adaptive detection system based on instrument recognition was proposed in this paper. The system uses HMM classifier to identify...
Analysis and recognition of auditory scenes play an important role in content-based multimedia processing and context-aware applications. In this paper, we propose an auditory scene recognition scheme that integrates the analysis of the audio data of scene with LDA topic model to discover latent structures (i.e. contextual correlations) of audio words, and generation of intermediate contextual descriptions...
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