Yuan cosmos is a virtual world linked and created by scientific technological means, which mapped interacted with the real world, digital living space new social system. With increasing popularity of data acquisition production equipment, people are increasingly convenient to produce multimedia such as images, graphics, audio, video, animation, three-dimensional models. In addition rapid develo...

This thesis presents a method to investigate the extent to which articulatory based acoustic features can be exploited to reduce ambiguity in automatic speech recognition search. The method proposed is based on a lattice re-scoring paradigm implemented to integrate articulatory based features into automatic speech recognition systems. Time delay neural networks are trained as feature detectors ...

This paper addresses the problem of finding a subset of the acoustic feature space that best represents the phoneme set used in a speech recognition system. A maximum mutual information approach is presented for selecting acoustic features to be combined together to represent the distinctions among the phonemes. The overall phoneme recognition accuracy is slightly increased for the same length ...

Speech is the most natural mode of communication. This work emphasizes on recognizing different emotions from speech signal. There are two major sections in this project namely feature extraction from speech signal and give this features as input to classifier to recognize emotions. Emotional states of speaker are considered as namely angry, happy, sad and neutral. The testing section classifie...

Speech recognition is the process of converting speech signals into words. For acoustic modeling HMM-GMM is used for many years. For GMM, it requires assumptions near the data distribution for calculating probabilities. For removing this limitation, GMM is replaced by DNN in acoustic model. Deep neural networks are the feed forward neural networks having more than one or multiple layers of hidd...

Cluster analysis is the name for a group of multivariate techniques whose primary purpose is to group objects based on the characteristics they possess. Clustering has been applied in many contexts and by researchers in many disciplines. This reflects its broad appeal and usefulness as one of the steps in exploratory data analysis. In this thesis I explore cluster analysis as a means to investi...

This paper outlines our submissions to different music classification tasks for the Music Information Retrieval Evaluation eXchange (MIREX) 2009. We detail here three different algorithms tested in mood and genre classification tasks, and in classical composer identification. These algorithms are based on Support Vector Machines, Disjoint Principal Components Models, and RCA-kNN. The last one u...

Recognizing human emotions through vocal channel has gained increased attention recently. In this paper, we study how used features, and classifiers impact recognition accuracy of emotions present in speech. Four emotional states are considered for classification of emotions from speech in this work. For this aim, features are extracted from audio characteristics of emotional speech using Linea...

Using TI digits recognition experiments, we show that a combination of two dynamic speech features, Liftered Forward Masked (LFM) MFCC and 2-D cepstrum, can improve system robustness to additive Volvo noise while maintaining system performance comparable to standard MFCC features in clean conditions. Through experiments, we show that the information extracted by forward masking and by the 2D ce...

Heart failure (HF) is a devastating condition that impairs people’s lives and health. Because of the high morbidity mortality associated with HF, early detection becoming increasingly critical. Many studies have focused on field heart disease diagnosis based sound (HS), demonstrating feasibility signals in diagnosis. In this paper, we propose non-invasive method for HF deep learning (DL) networ...