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This paper proposes a hybrid speaker diarization system. The main body is a variational Bayes — hidden Markov model (VB-HMM) speaker diarization system. The VB-HMM speaker diarization system avoids making premature hard decision and takes advantages of soft speaker information in an iterative way. Thus, it outperforms most of mainstream speaker diarization systems. Unfortunately, this system is sensitive...
Gesture recognition is an important research area in video analysis and computer vision. Gesture recognition systems include several advantages, such as the interaction with machines without needing additional external devices. Moreover, gesture recognition involves many challenges, as the distribution of a specific gesture largely varies depending on viewpoints due to its multiple joint structures...
Deep Neural Networks (DNN) are the dominant technique widely used in English and Chinese speech recognition currently. However, Tibetan speech recognition research starts late and mainly uses Hidden Markov Model (HMM). In this paper, We show a better method of replacing Gaussian Mixture Models (GMM) by DNN to Tibetan Lhasa dialect speech recognition system. The system contains seven layers of features...
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...
Building a human-computer interactive parachute simulator is an efficient way to avoid the high risk and high cost of field parachute training. In this paper, a novel dynamic recognition and simulation approach of parachute training is developed. Firstly we process the skeletal data acquired by Kinect and enforce the indication of the trainees' parachute posture, where principle component analysis...
Acoustic Event Detection plays an important role for computational acoustic scene analysis. Although we would face with a sound overlapping problem in a real situation, conventional methods do not consider the problem enough. In this paper, we propose a new overlapped acoustic event detection technique combined a source separation technique of Non-negative Matrix Factorization with shared basis vectors...
Human activity recognition through posture identification is increasingly used for medical, surveillance and entertainment applications. This paper proposes a ubiquitous solution to activity recognition through the use of tri-axial accelerometers of smartphones. Use of smartphones for activity recognition poses new challenges such as variation in hardware configuration and usage behavior like where...
The monitoring of a cutting tool is needed for the prediction of impending faults and estimating its Remaining Useful Life (RUL). Implementing a robust Prognostic and Health Management (PHM) system for a high speed milling CNC cutter remains a challenge for various industries to reach improved quality, reduced downtime, increased system safety and lower production costs. The purpose of the present...
The elderly people living alone or life of a patient face distress situations particularly in case of falling and becoming unable to ask for help. Fall in elderly people may result in head injury, broken hips, and bones that need immediate hospitalization to lower the mortality risk. During the last decade, several technological solutions were presented for early fall detection but most of them have...
Human action recognition in video is highly challenging due to the substantial variations in motion performance, recording settings and inter-personal differences. Most current research focuses on the extraction of effective features and the design of suitable classifiers. Conversely, in this paper we tackle this problem by a dissimilarity-based approach where classification is performed in terms...
The gene structure is consist of intron, exons, promoter, start codon, stop codon, etc. for the eukaryotic organism. The boundary between intron and exon is splice site. There is the need for accurate algorithms to be used in the splice sites identification and more attention was paid during past few years. This proposed system, Splice Hybrid have three layered architecture — in this layer2nd orderMM...
Representation of data is very important in case of machine learning. Better the representation, the classifiers will give better results. Contractive autoencoders are used to learn the representation of data which are robust to small changes in the input. This paper uses contractive autoencoder and SVM classifier for handwritten Devanagari numerals recognition. The accuracy obtained using CAE+SVM...
With the development of science and technology, computer technology is increasingly updated, and multimedia search technology has been widely used. For music retrieval, textbased retrieval technology can't meet the diversified retrieval needs. Humming retrieval is through matching the input audio and the audio in the database to match the audio. It's a more convenient way to retrieve music. In this...
With the extensive application of machine learning algorithms in bioinformatics, more and more computer researchers are beginning to focus on this field. Polyadenylation of messenger RNA (mRNA) is one of the key steps of gene expression in eukaryotes, polyadenylation site marks the end of transcription, it is of great significance to explore prediction of the site of gene sequences encoding gene....
Heart hemodynamic status and detection of a cardiovascular disease can be evaluated by analyzing and visualizing the heart waveform through graphs called the Phonocardiogram (PCG). The normal sounds of the heart generate signals that are in the audible frequency range of the human ear. Due to the significance of cardiac auscultation for recognizing pathological cardiac status, there has been special...
Mobility impaired individuals need the wheelchair to support their independent life, so monitor activities performed on the wheelchair can provide significant insights on their general health status. Activity recognition related to healthy people is a well established research area; however, only few works addressed this problem for wheelchair users. This paper proposes a novel approach based on dynamic...
Sentiment analysis is able to automatically extract valuable customer information from large amount of unstructured text data to support decision making in manufacturing applications such as product design and demand planning. One of the key issues of sentiment analysis is the high dimensionality of data, which can be effectively solved by feature selection. Existing feature selection techniques compute...
Recently, various technologies related to the 4th Industrial Revolution (cloud, Big Data, Internet of Things, artificial intelligence, etc.) have become issues and deep learning has become a favorite technique for big data and the studies using related techniques have been conducted on astronomy, physics, Science, and statistical analysis. The literature published by the researchers is increasingly...
We address the problem of continuous laughter detection over audio-facial input streams obtained from naturalistic dyadic conversations. We first present meticulous annotation of laughters, cross-talks and environmental noise in an audio-facial database with explicit 3D facial mocap data. Using this annotated database, we rigorously investigate the utility of facial information, head movement and...
With the increase of the scale and complexity of the industrial process, the requirements for process safety and reliability are further improved. In order to detect the equipment failure accurately and timely, a fault detection method based on continuous hidden Markov model (CHMM) is proposed. The principal component analysis (PCA) method is used to extract the characteristic data of the process...
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