In this paper, we present a novel audio fingerprinting method based on N-grams, which can quickly identify a segment of audio even when the audio signals are seriously distorted. We make use of N peaks in spectrum to ...
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In this paper, we present a novel audio fingerprinting method based on N-grams, which can quickly identify a segment of audio even when the audio signals are seriously distorted. We make use of N peaks in spectrum to form the audio fingerprint, which accelerates the retrieval speed greatly. We take advantage of the initial robust peaks to calculate the similarity between candidates and the input audio, which improves the retrieval accuracy significantly. The effectiveness of the N-gram method was evaluated on a music database of 10,000 songs. Experimental results show that the proposed approach outperforms two state-of-the-art algorithms (Shazam and Philips Robust Hash) in both effectiveness (in terms of retrieval accuracy) and efficiency (in terms of average retrieval time).
A new method is presented to study the function projective lag synchronization(FPLS) of chaotic systems via adaptive-impulsive control. To achieve synchronization, suitable nonlinear adaptive-impulsive controllers are...
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A new method is presented to study the function projective lag synchronization(FPLS) of chaotic systems via adaptive-impulsive control. To achieve synchronization, suitable nonlinear adaptive-impulsive controllers are designed. Based on the Lyapunov stability theory and the impulsive control technology, some effective sufficient conditions are derived to ensure the drive system and the response system can be rapidly lag synchronized up to the given scaling function matrix. Numerical simulations are presented to verify the effectiveness and the feasibility of the analytical results.
The a priori signal-to-noise (SNR) is one of the most important parameters in the short-time spectrum estimation techniques in speech enhancement. A new and convenient algorithm to estimate the priori SNR is involved ...
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Employing pre-trained word embeddings as preliminary features in convolutional neural networks（CNN） for natural language processing（NLP） tasks has been proved to be of *** exploit this idea by taking advantage of ...
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ISBN:
(纸本)9781509012473
Employing pre-trained word embeddings as preliminary features in convolutional neural networks（CNN） for natural language processing（NLP） tasks has been proved to be of *** exploit this idea by taking advantage of different types of word embeddings at the same *** be specific,we extend CNN models to coordinate two lookup tables,which exploit semantic word embeddings and syntactic word embeddings at the same *** test our models on several review datasets and all results indicate the positive effect on sentiment *** understand the reason behind,we explore the difference of the two word embeddings and how they influence the CNN models.
In speech recognition, acoustic modeling always requires tremendous transcribed samples, and the transcription becomes intensively time-consuming and costly. In order to aid this labor-intensive process, Active Learni...
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In speech recognition, acoustic modeling always requires tremendous transcribed samples, and the transcription becomes intensively time-consuming and costly. In order to aid this labor-intensive process, Active Learning （AL） is adopted for speech recognition, where only the most informative training samples are selected for manual annotation. In this paper, we propose a novel active learning method for Chinese acoustic modeling, the methods for initial training set selection based on Kullback-Leibler Divergence （KLD） and sample evaluation based on multi-level confusion networks are proposed and adopted in our active learning system, respectively. Our experiments show that our proposed method can achieve satisfying performances.
In this paper, a non-linear adaptive control method based on SO(3) for the quadrotor attitude tracking is proposed. Distinct from other control methods on Euclidean space, the controller proposed is developed on SO(3)...
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The computation of the sensitivity of a Madaline’s output to its parameter perturbation is system- atically discussed. Firstly, according to the discrete feature of Adalines, a method based on discrete stochastic tec...
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The computation of the sensitivity of a Madaline’s output to its parameter perturbation is system- atically discussed. Firstly, according to the discrete feature of Adalines, a method based on discrete stochastic technique is proposed, which derives some analytical formulas for the computation of Adalines’ sensitivity. The method can theoretically solve some problems that are unsolvable by the existing methods based on continu- ous stochastic techniques, release some unpractical constraints, and make it available to theoretically analyze the approximation error of Adalines’ sensitivity. Secondly, on the basis of the sensitivity of Adalines and the structural characteristics of Madalines, a new selection strategy depending on a type of dedication degree for computing Madalines’ sensitivity is proposed, which is superior to current popular way of simply averaging in both precision and complexity. The proposed formulas and algorithm have the advantages of simplicity, low computational complexity, small approximation error, and high generality, as have been verified by a great amount of experimental simulations.
Besides their decorative purposes,vehicle manufacturer logos can provide rich information for vehicle verification and classification in many applications such as security and information ***,unlike the license plate,...
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Besides their decorative purposes,vehicle manufacturer logos can provide rich information for vehicle verification and classification in many applications such as security and information ***,unlike the license plate,which is designed for identification purposes,vehicle manufacturer logos are mainly designed for decorative purposes such that they might lack discriminative features ***,in practical applications,the vehicle manufacturer logos captured by a fixed camera vary in *** these reasons,detection and recognition of vehicle manufacturer logos are very challenging but crucial problems to *** this paper,based on preparatory works on logo localization and image segmentation,we propose a size-self-adaptive method to recognize vehicle manufacturer logos based on feature extraction and support vector machine(SVM)*** experimental results demonstrate that the proposed method is more effective and robust in dealing with the recognition problem of vehicle logos in different ***,it has a good performance both in preciseness and speed.
In this paper, we present a large scale off-line handwritten Chinese character database-HCL2000 which will be made public available for the research community. The database contains 3,755 frequently used simplified Ch...
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