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检索条件"主题词=Linear Predictive coding"

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Formant estimation of whispered speech based on spectral segmentation

Formant estimation of whispered speech based on spectral seg...

引用

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

作者： Gong Chenghui Zhao Heming Lu Gang Liu Jianxin School of Electronics and Information Engineering Soochow University Suzhou China

Whispered speech, without vocal cord vibration and always in low SNR, is more difficult both in its analysis and recognition. Thus its formant estimation becomes prominent in each field. The proposed algorithm is based on spectral segmentation. The complete spectrum is segmented into K segments, each of which contains a single formant. Here, improved dynamic programming and selective LP (linear predictive) methods are used. The former offers segment boundaries, and the latter leads to the parameters of formant frequency and its bandwidth as well. For whispered speech, the gain of vocal tract transfer function is also important. The tests are carried on Chinese whispered vowels, and the proposed algorithm is proved to be efficient. In low SNR, the segment based LP method is obviously superior to the conventional LPC and LSP

关键词： linear predictive coding Speech analysis Speech processing Dynamic programming Bandwidth Frequency estimation Wiener filter Signal processing Speech recognition Signal processing algorithms

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An Algorithm for Formant Estimation of Whispered Speech

An Algorithm for Formant Estimation of Whispered Speech

引用

International Conference on Signal Processing Proceedings (ICSP)

作者： Gong Chenghui Zhao Heming Lu Gang Liu Jianxin Institute of Electronics Engineering Soochow University Suzhou China

Whispered speech, always in low SRN, is more difficult in its formant estimation. This paper proposes an algorithm for formant estimation of whispered speech. It includes three subroutines: calculation of the autocorrelation function (ACF) of whispered speech, segmentation of the ACF spectrum to get the coefficients of the inverse-filter, inverse-filter control (IFC) of the ACF spectrum and calculation of the formant frequencies. The tests are carried on Chinese whispered vowels, and the proposed algorithm is proved to be efficient. Especially in low SNR, it is superior to conventional methods for formant estimation of whispered speech

关键词： Speech enhancement Frequency estimation White noise Autocorrelation linear predictive coding Algorithms Filters Signal to noise ratio Delay effects Testing

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A New Transform with Extended Product to Exploit Different Scale Redundance

A New Transform with Extended Product to Exploit Different S...

引用

International Conference on Innovative Computing, Information and Control (ICICIC)

作者： Zhiyuan Zhang Yao Zhao Institute of Information Science Beijing Jiaotong University Beijing China

Fractal image coding (FIC) can exploit redundance at different scale in spatial domain. But there is no scheme presented to exploit the different scale redundance in frequency domain. In this paper, we extend the H product defined by Kou et al. Using the extended product, a new transform is constructed to exploit redundance at different scale in frequency domain. Meanwhile, a quantization method is proposed for the new transform. At last a new coder is constructed based on the new transform and quantization method. Experimental results suggest that the coder based on our transform can achieve better decoded image quality than FIC and JPEG, and the coding time of our coder is shorter than FIC

关键词： Frequency domain analysis Image coding Discrete cosine transforms Quantization Fractals Image storage linear predictive coding Information science Decoding Image quality

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Field Mixed Acoustic identification hybrid Systems Based on ICA and Improved GCA

Field Mixed Acoustic identification hybrid Systems Based on ...

引用

International Conference on Information and Automation (ICIA)

作者： Yaobo Li Zhiliang Ren Gong Chen Shengliang Hu Department of Weaponry Engineering Naval University of Engineering Wuhan China Department of Electronic Information Engineering Institute Communications Engineering of PLA University Nanjing China Electronic Engineering College Naval University of Engineering Wuhan China

With independent component analysis (ICA) to realize the blind separation from mixed acoustic objects, an identification method based on improved gray correlation analysis (IGCA) is proposed through extracting linear prediction coefficient (LPC) feature. It is revealed that LPC is consistently better than wavelet energy feature, ICA is efficient algorithm to estimate the unknown signal level and IGCA which gets over the shortcomings of GCA model may reflect the difference and similarity of the influences of factors or characteristics effectively. The validity of the new systems is verified via examples in mixed acoustic objects identification system

关键词： Independent component analysis linear predictive coding predictive models Acoustic noise Higher order statistics Data mining Degradation Acoustic waves Biological system modeling Feature extraction

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LPC-VQ based Hidden Markov Models for Similarity Searching in DNA Sequences

LPC-VQ based Hidden Markov Models for Similarity Searching i...

引用

IEEE International Conference on Systems, Man and Cybernetics

作者： Tuan D. Pham Hong Yan Bioinformatics Applications Research Center School of Information Technology James Cook University Townsville QLD Australia Department of Electronic Engineering City University of Hong Kong Kowloon Hong Kong China School of Electrical and Information Engineering University of Sydney NSW Australia

Given a newly found gene of some particular genome and a database of sequences whose functions have been known, it must be very helpful if we can search through the database and identify those that are similar to the particular new sequence. The search results may help us to understand the functional role, regulation, and expression of the new gene by the inference from the similar database sequences. This is the task of any methods developed for biological database searching. In this paper we present a new application of the theories of linear predictive coding, vector quantization, and hidden Markov models to address the problem of DNA sequence similarity search where there is no need for sequence alignment. The proposed approach has been tested and compared with some existing methods against real DNA and genomic datasets. The experimental results demonstrate its potential use for such purpose.

关键词： Hidden Markov models DNA Sequences Databases Bioinformatics linear predictive coding Genomics Vector quantization Dynamic programming Cybernetics

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Improving Lpc Spectral Envelope Extraction Of Voiced Speech By True-Envelope Estimation

Improving Lpc Spectral Envelope Extraction Of Voiced Speech ...

引用

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

作者： F. Villavicencio A. Robel X. Rodet Analysis-Synthesis team I. R. C. A. M. Paris France

n this work we address the problem of all pole spectral envelope estimation for speech signals. The currently widely used all pole spectral envelope model suffers from well-known systematic errors and more severely from model order mismatch. We will propose a procedure to first establish a band limited interpolation of the observed spectrum using a recently rediscovered true envelope estimator and then using the band limited envelope to derive an all pole envelope model named TE-LPC . The band-limited envelope that is used to derive the all pole envelope model reduces the problem of the unknown all pole model order. For the experimental investigation we propose a new perceptually motivated residual spectral peak flatness measure. The experimental results demonstrate that the proposed method significantly increases the spectral flatness for the perceptually especially important low order harmonics of voiced utterances

关键词： linear predictive coding Power harmonic filters Interpolation Speech analysis Signal analysis Data mining Speech coding Production systems Polynomials Frequency

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Recognition of 24 Thai spoken Vowels Using the coefficients of 3rdOrder Polynomial Regression on the Voice Energy and Spectrum of LPC on the Bark Scale

Recognition of 24 Thai spoken Vowels Using the coefficients ...

引用

International Symposium on Wireless Pervasive Computing (ISWPC)

作者： K. Songwatana S. Sriratanapaprat P. Kultap K. Sittiprasert N. Suktangman Faculty of Engineering King Mongkut''s Institute of Technology Ladkrabang Bangkok Thailand

This paper presents a vowel recognition for Thai spoken language. The Thai language consists of 9 short unmixed vowels (a, i,ω,u, o, e, ε, γ, [unk]); 9 long unmixed vowels (aa, ii, ωω, uu, oo, ee, £ εε, γγ, [unk][unk]); 3 short mixed vowels (ia, ωa, ua); and 3 long mixed vowels (i:a:, ω:a:, u:a:). We proposed uses 3-stage decision making: step 1 distinguishes long and short vowels using coefficients of third order polynomial regression of signal energy as features set and 5-NN as classification method; step 2 classifies each voice segment (frame) into 9 basic vowels using 18 critical band intensities as feature set and 9-NN as classification method; finally step 3 decides whether each frame contains mixed or unmixed vowel via thresholding method. This solution is different from the conventional speech recognition mainly because decision making in this method is done for each frame, while conventional speech recognition chooses the best decision for a sequence of frames forming a word or a sentence. Evaluation is done by applying the algorithm to 3024 voice samples of male and female subjects. Each step of the algorithm is evaluated successively.

关键词： Speech recognition Polynomials linear predictive coding Equations Decision making Signal processing Natural languages Lungs Humans Ear

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Using a Vocal Tract Length Related Parameter for Speaker Recognition

Using a Vocal Tract Length Related Parameter for Speaker Rec...

引用

IEEE Odyssey, The Speaker and Language Recognition Workshop

作者： Stephan Grashey Christian GeiBler Siemens AG Corporate Technology Munich Germany

The use of a parameter related to the vocal tract length of humans is investigated for a speaker recognition system. This parameter is a warping factor for the frequency spectrum and it was determined from a vocal tract length normalization module of an automatic speech recognizer. A decision fusion approach WHS used to combine the output of the stand-alone speaker verification with a separate classifier for the warping factor. The fused system exhibits a relative improvement of 23% compared to the stand-alone system

关键词： Speaker recognition Mel frequency cepstral coefficient Cepstral analysis Automatic speech recognition Finite impulse response filter Feature extraction linear predictive coding Humans Forensics Discrete cosine transforms

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A New Algorithm for Calculating LSP Parameters of Speech Signal

A New Algorithm for Calculating LSP Parameters of Speech Sig...

引用

International Conference on Signal Processing Proceedings (ICSP)

作者： Juanjuan Li Yibiao Yu Xianyi Rui School of Electronic and Information Engineering Soochow University Suzhou China

Line spectrum pairs (LSP) representation of linear predictive coding coefficients is widely used in speech coding, speech recognition and other domains due to its desirable interpolation and quantization properties. Several methods proposed for calculating LSP parameters have been complicated by high computation complexity. This paper proposed an effective and efficient algorithm APF using Aitken iterative method and polynomial synthesis division. LSP parameters were estimated by obtaining a root of N-order nonlinear equation by Aitken iterative method at first, then decreasing degrees with polynomial synthesis division, and finally calculating quartic equation using Ferrari's solution. Theoretic analysis and experiment results show that the proposed algorithm has not only high precision but also low calculation complexity

关键词： Iterative algorithms Iterative methods Polynomials Nonlinear equations linear predictive coding Speech coding Speech recognition Interpolation Quantization Speech synthesis

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F0 estimation of noisy speech based on complex speech analysis

F0 estimation of noisy speech based on complex speech analys...

引用

IEEE Digital Signal Processing Workshop

作者： Tatsuhiko Kinjo Keiichi Funaki Graduate School of Science and Engineering University of Ryukyus Okinawa Japan Computing & Networking Center University of Ryukyus Okinawa Japan

ISBN: (纸本)1424405343

This paper proposes a novel robust fundamental frequency (F0) estimation algorithm based on complex-valued speech analysis for an analytic speech signal. Since analytic signal provides spectra only over positive frequencies, spectra can be accurately estimated in low frequencies. Consequently, it is considered that F0 estimation using the residual signal extracted by complex-valued speech analysis can perform better for F0 estimation than that for the residual signal extracted by conventional real-valued LPC analysis. In this paper, the autocorrelation function weighted by AMDF is adopted for the F0 estimation criterion and four signals; speech signal, analytic speech signal, LPC residual and complex LPC residual, are evaluated for the F0 estimation. Speech signals used in the experiments were corrupted by adding white Gaussian noise whose noise levels are 10, 5, 0, -5 [dB]. The experimental results demonstrate that the proposed algorithm based on complex speech analysis can perform better than other methods in an extremely noisy environment

关键词： Speech analysis Frequency estimation Signal analysis linear predictive coding Low-frequency noise Robustness Algorithm design and analysis Performance analysis Autocorrelation Speech enhancement

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