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检索条件"主题词=Linear Predictive coding"

共 2458 条记录，以下是231-240 订阅

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Glottal closure instant detection using Lines of Maximum Amplitudes (LOMA) of thewavelet transform

Glottal closure instant detection using Lines of Maximum Amp...

引用

International Conference on Acoustics, Speech, and Signal Processing (ICASSP)

作者： Nicolas Sturmel Christophe d'Alessandro Francois Rigaud LIMSI/CNRS ORSAY CEDEX FRANCE

The Lines Of Maximum Amplitude (LOMA) of the wavelet transform are used for glottal closure instant detection. Following Kadambe & al. (1992), the wavelet transform modulus maxima can be used for singularity detection. The LOMA method extends this idea. All the lines chaining maxima of a wavelet transform across scales are built. Then a back-tracking procedure allows for selection of the optimal line for each pitch period, the top of which indicates the GCI. The LOMA method is then evaluated by comparing its results to the DYPSA (Naylor & al.) algorithm, with the option of using inverse filtering as preprocessing. The LOMA method compares favorably to DYPSA, particularly on accuracy. One of the advantage of the LOMA method is its ability to deal with variations in the glottal source parameters.

关键词： Wavelet transforms linear predictive coding Speech analysis Filtering algorithms Speech processing Speech synthesis Frequency synthesizers Nonlinear filters Delay Robustness

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Improvement of Delayed Decision coding for LSF Difference Quantization

Improvement of Delayed Decision Coding for LSF Difference Qu...

引用

International Conference on Natural Computation (ICNC)

作者： Zhe Ji Xuan Wei Huijuan Cui Kun Tang State Key Laboratory on Microwave and Digital Communications Department of Electronic Engineering Tsinghua University Beijing China

ISBN: (纸本)9781424445424

The line spectrum frequencies (LSFs) are significant parameters which characterize the spectrum of the speech. The differential quantization of LSFs has been proven to provide better performance which exploits the intraframe correlation between adjacent LSFs, and the delayed decision coding of LSF differences (LSFDs) has been developed to obtain globally optimal quantization. In this paper, we improve the delayed decision quantization of LSFDs by using the conditional codebooks. Test results show that the algorithm proposed can perform transparent quantization of LSFs with 28 bits/frame.

关键词： Delay Quantization linear predictive coding Testing Degradation Polynomials Digital communication Frequency Speech coding Performance evaluation

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Speech based watermarking for digital images

Speech based watermarking for digital images

引用

IEEE Region 10 International Conference TENCON

作者： Vandana S. Inamdar Priti. P. Rege Aarti Bang Department of Computer Engineering and IT College of Engineering Pune India Department of Electronics Vishwakarma Institute of Information Technology Pune India

This paper presents a novel scheme of watermarking of digital images for copyright protection and authentication. In this paper we proposed a method of embedding owner's speech signal. Speech being a biometric data, the watermark signal in this method is expected to be more meaningful and has closer correlation with copyright holder. The main issue of concern here is the capacity because the speech data has large number of samples. linear predictive coding is used to encode the audio data. Here, speech samples are imperceptibly inserted using spread spectrum technique into the mid frequency band of wavelet transform of image which makes it robust to lossy compression. Applications for such a speech-hiding scheme include copy protection, authentication and covert communication.

关键词： Speech Watermarking Digital images Authentication Copyright protection Bioinformatics linear predictive coding Spread spectrum communication Frequency Wavelet transforms

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On the performance of ITU-T G.723.1 and AMR-NB codecs for large vocabulary distributed speech recognition in Brazilian Portuguese

On the performance of ITU-T G.723.1 and AMR-NB codecs for la...

引用

International Conference on the Applications of Digital Information and Web Technologies (ICADIWT)

作者： Vladimir Fabregas Surigue de Alencar Abraham Alcaim CETUC Catholic University of Rio de Janeiro Rio de Janeiro Brazil

In this paper, we present the accuracy for large vocabulary distributed continuous speech recognition systems over ITU-T G.723.1 and AMRNB speech codecs. Experiments were conducted using LPC and LSF-derived speech rec... 详细信息

关键词： Vocabulary Speech recognition linear predictive coding Interpolation Decoding Speech codecs Automatic speech recognition Feature extraction IP networks GSM

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Multipoint Equalization of Digital Car Audio Systems

Multipoint Equalization of Digital Car Audio Systems

引用

International Symposium on Image and Signal Processing and Analysis

作者： S. Cecchi L. Palestini P. Peretti F. Piazza A. Carini Universita Politecnica delle Marche DIBET - A3Lab Via Brecce Bianche Universita' di Urbino STI Piazza della Repubblica

ISBN: (纸本)9781424456499

In this paper a novel approach for automotive sound system enhancement based on multipoint equalization is presented. Beginning from well known techniques applied to room equalization issues, a frequency domain algorithm that combines fractional octave smoothing of measured impulse responses (IRs) in multiple locations is developed. The IRs are calculated using well positioned microphones inside a car taking into account the properties of the environment. Several results are presented considering different methods to combine the IRs and confirming the validity of the approach in comparison with single point equalization.

关键词： Audio systems Filters Loudspeakers Automotive engineering linear predictive coding Frequency measurement Adaptive equalizers Clustering algorithms Frequency domain analysis Smoothing methods

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Design of a modified one-against-all SVM classifier

Design of a modified one-against-all SVM classifier

引用

IEEE International Conference on Systems, Man and Cybernetics

作者： J. Manikandan B. Venkataramani Department of ECE National Institute of Technology Tiruchirappalli India

Support Vector Machine (SVM) is one of the state-of-the-art tools for linear and nonlinear pattern classification. One of the design issues in SVM classifier is reducing the number of support vectors without compromising the classification accuracy. In this paper, a novel technique which requires only a subset of the support vectors is proposed. The subset is obtained by including only those support vectors for which Lagrange multiplier is greater than a threshold. In order to find the subset which yields the highest classification accuracy with the least number of support vectors in the subset, the recognition performance corresponding to subsets with different threshold values are to be evaluated and compared. The proposed technique is applied for SVM based isolated digit recognition system and is studied using speaker dependent as well as multispeaker dependent TI46 database of isolated digits. Two feature extraction techniques, one using LPC and another using MFCC are applied to the speech from the above database and the features are mapped using SOFM. This in turn is used by the SVM classifier to evaluate the recognition accuracy. The proposed technique is applied to one-against-all (OAA) scheme and is denoted as modified one-against-all (M-OAA) approach in this paper. Based on this study, it is found that for MFCC feature input, the proposed M-OAA based SVM classifier approach results in reduction of support vectors by a factor of 1.86 to 18.3 with no compromise in recognition accuracy. For LPC feature input, the M-OAA based SVM classifier results in reduction of support vectors by a factor of 1.59 to 2.52 without any compromise in recognition accuracy for some cases and with a maximum of 1% degradation in recognition accuracy for some cases. The proposed approach is also applicable for other schemes such as half-against-half (HAH) and directed acyclic graphs (DAG) based SVM classifiers as well as for any other classification problem such as face recognition,

关键词： Support vector machines Support vector machine classification Spatial databases linear predictive coding Mel frequency cepstral coefficient Pattern classification Lagrangian functions Feature extraction Speech Degradation

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Efficient Construction of Multiple Geometrical Alignments for the Comparison of Protein Binding Sites

Efficient Construction of Multiple Geometrical Alignments fo...

引用

International Conference on Intelligent Systems Design and Applications (ISDA)

作者： Thomas Fober Gerhard Klebe Eyke Hüllermeier Department of Mathematics & Computer Science Philipps-Universität Marburg Marburg Germany Department of Pharmaceutical Chemistry Philipps-Universität Marburg Marburg Germany

We proceed from a method for protein structure comparison in which information about the geometry and physico-chemical properties of such structures are represented in the form of labeled point clouds, that is, a set of labeled points in three-dimensional Euclidean space. Two point clouds are then compared by computing an optimal spatial superposition. This approach has recently been introduced in the literature and was shown to produce very good similarity scores. It does not, however, establish an alignment in the sense of a one-to-one correspondence between the basic units of two or more protein structures. From a biological point of view, alignments of this kind are of great interest, as they offer important information about evolution, heredity, and the mutual correspondence between molecular constituents. In this paper, we therefore developed a method for computing pairwise or multiple alignments of protein structures on the basis of labeled point cloud superpositions.

关键词： Biology computing Three-dimensional displays Quantum computing linear predictive coding Evolution (biology) Protein engineering Intelligent systems Intelligent structures Application software

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Limited Speech Recognition for Controlling Movement of Mobile Robot Implemented on ATmega162 Microcontroller

Limited Speech Recognition for Controlling Movement of Mobil...

引用

International Conference on Computer and Automation Engineering, ICCAE

作者： Dhanny Wijaya Thiang Electrical Engineering Department Petra Christian University Siwalankerto Surabaya Indonesia

This paper describes about speech recognition implemented on ATmega162 microcontroller. The word (voice command) in a speech signal is applied for controlling movement of a mobile robot. The mobile robot will move according to the voice command in the speech signal. There are five commands, which are Indonesian language, used to control the movement of mobile robot. They are ldquomajurdquo, ldquomundurrdquo, ldquokirirdquo, ldquokananrdquo, and ldquostoprdquo used to command the mobile robot to move forward, move backward, turn left, turn right and stop respectively. The methods used in this research are linear predictive coding (LPC) and Hidden Markov Model (HMM). LPC is used to extract word data from a speech signal. HMM is used to recognize the word pattern data, which are extracted from a speech signal. Sampling rate of the speech signal is 8 kHz and the speech signal is sampled for 0.5 seconds. Experiments were done in several variations of observation symbol number and number of sample. The experimental results show that the highest recognition rate that can be achieved by the system is 87%. The mobile robot can move in accordance with the voice command that is given to the robot.

关键词： linear predictive coding Speech recognition Mobile robots Microcontrollers Hidden Markov models Robotics and automation Data mining Automatic speech recognition Speech coding Speech analysis

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Bangla Speech Recognition System Using LPC and ANN

Bangla Speech Recognition System Using LPC and ANN

引用

International Conference on Advances in Pattern Recognition (ICAPR)

作者： Anup Kumar Paul Dipankar Das Md. Mustafa Kamal Dhaka City College Dhaka Dhaka District BD Department of Information and Communication Engineering University of Rajshahi Rajshahi Bangladesh

This paper presents the Bangla speech recognition system. Bangla speech recognition system is divided mainly into two major parts. The first part is speech signal processing and the second part is speech pattern recognition technique. The speech processing stage consists of speech starting and end point detection, windowing, filtering, calculating the linear predictive coding (LPC) and cepstral coefficients and finally constructing the codebook by vector quantization. The second part consists of pattern recognition system using artificial neural network (ANN). Speech signals are recorded using an audio wave recorder in the normal room environment. The recorded speech signal is passed through the speech starting and end-point detection algorithm to detect the presence of the speech signal and remove the silence and pauses portions of the signals. The resulting signal is then filtered for the removal of unwanted background noise from the speech signals. The filtered signal is then windowed ensuring half frame overlap. After windowing, the speech signal is then subjected to calculate the LPC coefficient and cepstral coefficient. The feature extractor uses a standard LPC cepstrum coder, which converts the incoming speech signal into LPC cepstrum feature space. The self organizing map (SOM) neural network makes each variable length LPC trajectory of an isolated word into a fixed length LPC trajectory and thereby making the fixed length feature vector, to be fed into to the recognizer. The structures of the neural network is designed with multi layer perceptron approach and tested with 3, 4, 5 hidden layers using the Transfer functions of Tanh Sigmoid for the Bangla speech recognition system. Comparison among different structures of neural networks conducted here for a better understanding of the problem and its possible solutions.

关键词： Speech recognition linear predictive coding Speech processing Artificial neural networks Neural networks Pattern recognition Cepstral analysis Cepstrum Trajectory Signal processing

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Technologies for speech and audio coding

Technologies for speech and audio coding

引用

IEEE International Symposium on Consumer Electronics (ISCE)

作者： Takehiro Moriya NTT Communication Science Laboratories Nippon Telegraph and Telephone Corporation Atsugi Japan

This paper reviews some important technologies for speech and audio coding, contrasting time domain and frequency domain processing. These technologies have contributed to the standardization activities in ITU-T and ISO/IEC MPEG, respectively. It is interesting that the standardization targets for speech and audio have started to converge recently. The MPEG USAC (Unified Speech and Audio coding) scheme, which is being actively developed, may make use of most of the important technologies for speech and audio that have been developed so far.

关键词： Speech coding Audio coding Frequency domain analysis Standardization Speech processing Narrowband Bit rate Delay Bandwidth linear predictive coding

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