We present two resource efficient frameworks for acoustic scene classification and acoustic event detection. In particular, we combine gated recurrent neural networks (GRNNs) and linear discriminant analysis (LDA) for efficiently classifying environmental sound scenes of the IEEE Detection and Classification of Acoustic Scenes and Events challenge (DCASE2016). Our system reaches an overall accu...

A two-stage classifier is used to improve the classification performance between normal and pathological voices. A primary classification between normal and pathological voices is achieved by the Gaussian mixture model (GMM) log-likelihood scores. For samples that do not meet the thresholds for normal or disordered voice in the GMM, the final decision is made by a higher-order statistics (HOS)-...

In this paper, we first introduce the use of Gaussian mixture models (GMM) for Chinese tone classification in continuous speech. Then, we explain how to integrate it with the HMM-based speech recognition system. Finally, we provide the tone classification accuracy of this probabilistic method which is tested with Chinese continuous speech database of national “863” project.

A two-way factorial experiment based on a randomized complete design (RCD) with four replications was used to compare four levels of N supply including control (N0), 60(N60), 120(N120) and 180(N180) mg N per Kg soil and four different water supply including 100(I100), 80(I80), 60(I60) and 40(I40) % FC on growth, water-use efficiency and mucilage yield of isabgol. Under I40, higher N addition le...

This study focuses on the detection of shouted speech in realistic noisy conditions. An automatic system based on modified mel frequency cepstral coefficient (MFCC) feature extraction and Gaussian mixture model (GMM) classification is developed. The performance of the automatic system is compared against human perception measured by a listening test. At moderate noise levels, the automatic syst...

knowledge of the relationship between two phenomena (inflation and unemployment) is crucial to any economic and political decision-making process. an investigation of this relationship helps economists and policy-makers to be aware of the economy’s performance. in the present research, new-keynesians’ philips hybrid curve has been derived by using the pricing models and the assumption of price ...

In this paper, we first introduce the use of Gaussian mixture models (GMM) for Chinese tone classification in continuous speech. Then, we explain how to integrate it with the HMM-based speech recognition system. Finally, we provide the tone classification accuracy of this probabilistic method which is tested with Chinese continuous speech database of national “863” project.

In this paper an attempt is made to automatically recognize the speaker’s accent among regional Swiss French accents from four different regions of Switzerland, i.e. Geneva (GE), Martigny (MA), Neuchâtel (NE) and Nyon (NY). To achieve this goal, we rely on a generative probabilistic framework for classification based on Gaussian mixture modelling (GMM). Two different GMM-based algorithms are in...

A fast forward feature selection algorithm is presented in this paper. It is based on a Gaussian mixture model (GMM) classifier. GMM are used for classifying hyperspectral images. The algorithm selects iteratively spectral features that maximizes an estimation of the classification rate. The estimation is done using the k-fold cross validation. In order to perform fast in terms of computing tim...

Automatic speaker recognition (ASR) has found immense applications in the industries like banking, security, forensics etc. for its advantages such as easy implementation, more secure, more user friendly. To have a good recognition rate is a pre-requisite for any ASR system which can be achieved by making an optimal choice among the available techniques for ASR. In this paper, different techniq...