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检索条件"主题词=Linear predictive coding"

共 2458 条记录，以下是461-470 订阅

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Optimizing Vowel Recognition in Thai Spoken Language using Reduced LPC Spectrum and Reduced Feature Set of Critical Band Intensities

Optimizing Vowel Recognition in Thai Spoken Language using R...

引用

International Symposium on Communications and Information Technologies (ISCIT)

作者： Nongnuch Suktangman Kham Khanthavivone Kraisin Songwatana Faculty of Engineering King Mongkut''s Institute of Technology Ladkrabang Bangkok Thailand Thailand

This paper presents an optimization for vowel recognition in Thai spoken language. Thai language consists of 18 unmixed vowels (a,aa,i,ii,omega,omegaomega,u,uu,e,ee,epsi,epsiepsi,o,oo, gamma,gammagamma,sigmav,sigmavsigmav); and 6 mixed vowels (ua,u:a:,ia,i:a:,omegaa,omega:a:). Previously we have proposed use a 3-stage decision-making process: using voice energy and polynomial regression for short and long vowels classification; identifying voice segment (frame) into basic vowels; and using decision rule for recognition on unmixed and mixed vowels. The optimization is done by reducing the order of LPC and choosing a reduced set of critical band intensities (CBI). With this, the percentage accuracy remains high while processing time is decreased by 85%. The experiment is carried out on voice samples from 3 male model, 3 female model, and 2 male and 2 female model, yielding an accuracy of 91.47, 94.98, and 91.72 percents respectively

关键词： Speech recognition Natural languages linear predictive coding Equations Speech analysis Polynomials Transfer functions Humans Power engineering and energy Decision making

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Improvement of Esophageal Speech using LPC and LF Model

Improvement of Esophageal Speech using LPC and LF Model

引用

International Conference on Biomedical and Pharmaceutical Engineering, ICBPE

作者： R. Sirichokswad P. Chanyagorn W. Charoensuk P. Boonpramuk N Kasemkosin H.H. Szu International Biomedical Engineering Programme Mahidol University Thailand Dept. Electrical Engineering Mahidol University Thailand Dept. of Control Systems and Instrumentation Engineering KMUTT Thailand Audiology and Speech Clinic Mahidol University Thailand Office of U.S. Naval Research Virginia USA

Esophageal speech is a restoration of speech communication in laryngectomized patient. Due to irregular pharyngoesophageal (PE) segment vibration and aerodynamic limitation, the esophageal phonation provides higher volatility of the fundamental frequency ( f 0 ) compared with laryngeal phonation. It is difficult to determine an accurate f 0 in esophageal speech. This paper focuses on algorithms for f 0 modification. linear predictive coding (LPC) and autocorrelation function are used to calculate the f 0 They are well performed in the normal case. However, the determination results of f 0 in esophageal speech are highly unstable without any modification of a conventional LPC technique. By proposing a smoothing technique, an accurate f 0 and pitch period in esophageal speech can be determined and used in LF model. Experimental results from 18 subjects suggest that average f 0 of esophageal phonation is lower than laryngeal phonation. The speech synthesized using this proposing technique produced better sound quality than un-processed esophageal speech.

关键词： Esophagus linear predictive coding Autocorrelation Speech synthesis Filters Smoothing methods Speech enhancement Speech analysis

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Analysis and Synthesis of Vowels Using Matlab

Analysis and Synthesis of Vowels Using Matlab

引用

IEEE International Conference on Automation, Quality and Testing, Robotics, AQTR

作者： Alina Nica Alexandru Caruntu Gavril Toderean Ovidiu Buza Department of Telecommunications Technical University of Cluj Napoca Cluj-Napoca Romania

We propose a software environment in Matlab, in order to extract the main features from the Romanian vowels and to synthesize the vowels. The used analysis techniques for the estimation of the parameters are: time domain analysis for energy and zero-crossing rate (ZCR), cepstral analysis for fundamental frequency and linear predictive coding (LPC) for formants. Also, to synthesize the vowels, we used the LPC method

关键词： Speech analysis Speech synthesis Signal analysis Cepstral analysis Signal synthesis linear predictive coding Spectrogram Feature extraction Frequency estimation Time domain analysis

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Dynamic Scaling of Encoded Speech Through the Direct Modification of Coded Parameters

Dynamic Scaling of Encoded Speech Through the Direct Modific...

引用

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

作者： R.A. Sukkar R. Younce Peng Zhang Tellabs Inc. Naperville IL USA

In new generation networks like 3G wireless and VoIP, a great deal of emphasis is put on transcoder-free operation (TrFO), where speech remains coded throughout the core network. Any network-based speech processing function must, therefore, operate on the coded parameters directly if the value of TrFO is to be realized. Many of these functions, like echo control, noise reduction, and gain control can be viewed as dynamic amplitude scaling of the speech signal. Given that an intermediate step of decoding/re-encoding is not an option, we present, in this paper, a method for dynamic scaling of speech in the coded-domain directly. We derive expressions for modifying the relevant coded parameters such that the resulting decoded speech would correspond to the desired scaled signal. Experimentally, we use the AMR 12.2 kbps coder, and show that the proposed method results in a signal whose level, as well as speech quality, closely matches the desired scaled signal

关键词： Decoding Noise reduction Speech processing Speech enhancement Gain control Telephone sets Signal processing Performance gain linear predictive coding Degradation

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Speech Stream Detection in Strong Noise based on linear Prediction

Speech Stream Detection in Strong Noise based on Linear Pred...

引用

IEEE Conference on Industrial Electronics and Applications (ICIEA)

作者： Rubo Zhang Tian Wu Xueyao Li Dong Xu College of Computer Science and Technology Harbin Engineering of Technology Harbin Heilongjiang China

The speech signal is usually mixed with a great deal of noise, and the noise weakens seriously the performance of the algorithms to detect speech signal. This paper presents a robust algorithm for speech signal detection in low SNR based on the linear prediction technology. The proposed approach firstly decreases noise by using linear predication residual, then decides whether speech signal is contained or not according to the coefficients statistics of LPC. The operation to speech component is only taken in prediction residual by enhancement, which produces little impairment to the formant of the speech. As most of the energy components of speech signals exist in the region between 300 Hz and 3000 Hz, only those LPC coefficients in this region are taken into account, which also reduces the influence from noise. Experiments show that it is particularly immunized for the proposed algorithm to the strong noise, especially in the white noise. At last, the performance of the algorithm is compared to the approach based on short-term energy in various noise condition, and quantified using the probability of correct classification. The results show that the proposed algorithm has an overall better performance than the referred approach, such as white noise and factory noise to low SNR

关键词： Speech enhancement Signal processing algorithms Signal detection Speech coding Speech processing linear predictive coding Detection algorithms Signal to noise ratio White noise Working environment noise

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Set-membership filtering strategies for multipulse coding

Set-membership filtering strategies for multipulse coding

引用

IEEE International Symposium on Circuits and Systems (ISCAS)

作者： D. Joachim R. Salmon J.R. Deller Electrical Engineering and Computer Science Tulane University USA Electrical and Computer Engineering Michigan State University USA

This paper describes a new class of multi-pulse coders based on bounded-error identification. Multi-pulse coders provide effective representations of speech signals by extracting linear prediction parameters and approximating the effect of excitation signals with strategic sparse impulse sequences. These sparse impulses can be derived according to a set-membership optimization set volume reduction strategy. The proposed method offers the added benefit of improved scalar quantization through the choice of coder parameters from a feasibility set

关键词： Filtering Speech analysis Speech coding Speech processing linear predictive coding Pulse generation predictive models Signal processing Quantization Approximation algorithms

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Adaptive Non-linear Prediction for Speech Signals in Mixture Noise Environments

Adaptive Non-Linear Prediction for Speech Signals in Mixture...

引用

IEEE International Symposium on Intelligent Signal Processing and Communication Systems (ISPACS)

作者： Hirobumi Tanaka Yuichiroh Ohhashi Tetsuya Shimamura Graduate School of Science and Engineering Saitama University Saitama Japan Derparment of Inforrmation and Computer Sciences Saitama University Saitama Japan

For robust prediction analysis for speech signals in impulsive noise environments, we had proposed the OSLMS with AS predictor in Y. Ohhashi et al. (2004). Assuming general noise environments, however, we cannot neglect background noises. Therefore, in this paper, we saddled properties of the LPC in a mixture noise environment which has a content of impulsive noises and white Gaussian noises, and prove that an adaptive predictor perform more effectively in the mixture noises which has white noises with low power than batch predictors. Furthermore, we conducted prediction experiments using 3 adaptive predictors including the OSLMS with AS in the mixture noise environments. As a result, She OSLMS with AS predictor provided good performance in mixture noise environments which has practical white noise power, too

关键词： Speech enhancement Working environment noise Gaussian noise linear predictive coding White noise Speech processing Sorting Signal processing Speech analysis Background noise

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Speaker Identification System Based on Multi-Classifier

Speaker Identification System Based on Multi-Classifier

引用

World Congress on Intelligent Control and Automation (WCICA)

作者： Bo Wang Yiqiong Xu Bicheng Li Department of Information Science Information and Engineering University Zhengzhou China

This paper presents a practical speaker recognition system based on multi-classifier structure. Multi-classifier structure overcomes the shortcomings of single classifier, such as low recognition rate, narrow application field and critical demand of environment. Additionally, multi-classifier provides a novel way of improvement of system performance. The involved classifiers include ANN (artificial neural networks), GMM (Gaussian mixed model), sub-band classifiers, etc. The input features of classifiers contain MFCC (mel frequency cepstrum coefficient), LPCC (linear prediction cepstrum coefficient). Multi-classifier confusion adopts CFM (classification figure of merit) principle as object function. In practical application, the recognition rate of the system achieves 94% in environment of super short wave (SNR 15db)

关键词： linear predictive coding Artificial neural networks Cepstrum Information science Speaker recognition System performance Mel frequency cepstral coefficient Intelligent control Automation

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Influence of the LPC Filter Upon the Perception of Breathiness and Vocal Effort

Influence of the LPC Filter Upon the Perception of Breathine...

引用

IEEE International Symposium on Signal Processing and Information Technology (ISSPIT)

作者： Karl I . Nordstrom Peter F. Driessen Glen A. Rutledge Department of Electrical and Computer Engineering University of Victoria Victoria Canada DB Research Limited Victoria Canada

According to the source-filter paradigm, the perception of breathiness and vocal effort should be primarily controlled by the glottal source and be little affected by the formant filter. This experiment investigates whether the formant filter estimated by linear prediction (LPC) can influence the perception of breathiness and vocal effort. The experiment starts with a pair of voice samples. One sample exhibits high effort and the other sample exhibits breathiness. LPC estimates a filter and residual for each sample. The influence of the residual is eliminated by providing both filters with the same artificial source during resynthesis. The synthesized samples differ only according to the difference between the two filters. Three pairs of samples were evaluated by seven people in listening tests. The results demonstrate that the LPC filters do influence the perception of breathiness and vocal effort. When a voice changes between breathiness and vocal effort, the spectral envelope changes. This change is captured by the LPC filter rather than the residual. A closer look at the LPC algorithm provides an explanation for this result

关键词： linear predictive coding Frequency Shape Pulse shaping methods Power harmonic filters Signal processing Information technology Information filtering Information filters Nonlinear filters

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Frame Change Ratio: A Measure to Model Short-Time Stationarity of Speech

Frame Change Ratio: A Measure to Model Short-Time Stationari...

引用

International Conference on Innovations in Information Technology

作者： M. Sarwar Ehsan Gernot Kubin Signal Processing and Speech Communication Laboratory Graz University of Technology Austria

ISBN: (纸本)1424406730;1424406749

In many applications such as speech coding and PLC (packet loss concealment) methods, short-time stationarity of speech is assumed. In this paper, we introduce a new measure to model the short-time stationarity of speech. The model is developed by using a large amount of speech data together with real speech codecs and PLC methods. Experiments show that a single parameter, the frame change ratio, can be used to model this characteristic. This parameter is independent of speech material, speaker gender, and loss rate. It provides generic characteristics of the deviation of speech from stationary behavior when evolving from one frame to the next

关键词： Programmable control Speech processing Speech coding Speech codecs Rate-distortion linear predictive coding Random processes Loss measurement Signal processing Oral communication

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