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检索条件"主题词=Linear Predictive coding"

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Formant distortion after codecs for Arabic

Formant distortion after codecs for Arabic

引用

International Symposium on Communications Control and Signal Processing (ISCCSP)

作者： Amr Nabil Mohamed Hesham Faculty of Engineering Engineering Mathematics and Physics Department Cairo University Giza Egypt

In this work, we present results on the effect of wellknown mixed excitation linear prediction (MELP) and code-excited linear prediction (CELP) coders on the formants of Arabic sounds. The study shows, firstly, the spectral distortion of different Arabic phonemes due to mentioned coders. It was found that MELP1200 coder results in largest distortion. The coders effect on vowel formants are then investigated. The experiments show that the first formant of a vowel, on the average, suffers a frequency shift in the order of 50 Hz from its original value. Also, the amplitude distortion of the vowel formants due to Melp1200 coder was the highest, compared to the distortion of the other coders. Vowel formants have a shift which may exceed one critical band below or above its reference value.

关键词： Codecs Bit rate Speech analysis linear predictive coding Frequency Speech coding Power engineering and energy Mathematics Physics Process control

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ESTIMATION OF FRAME INDEPENDENT AND ENHANCEMENT COMPONENTS FOR SPEECH COMMUNICATION OVER PACKET NETWORKS

ESTIMATION OF FRAME INDEPENDENT AND ENHANCEMENT COMPONENTS F...

引用

IEEE International Conference on Acoustics, Speech, and Signal Processing

作者： Daniele Giacobello Manohar N. Murthi Mads Graesboll Christensen Soren Holdt Jensen Marc Moonen Dept. of Electronic Systems Aalborg Universitet Aalborg Denmark Dept. of Electrical and Computer Engineering University of Miami USA Dept. of Electrical Engineering Katholieke Universiteit Leuven Leuven Belgium

ISBN: (纸本)9781424442959

In this paper, we describe a new approach to cope with packet loss in speech coders. The idea is to split the information present in each speech packet into two components, one to independently decode the given speech frame and one to enhance it by exploiting inter-frame dependencies. The scheme is based on sparse linear prediction and a redefinition of the analysis-by-synthesis process. We present Mean Opinion Scores for the presented coder with different degrees of packet loss and show that it performs similarly to frame dependent coders for low packet loss probability and similarly to frame independent coders for high packet loss probability. We also present ideas on how to make the coder work synergistically with the channel loss estimate.

关键词： Speech coding Voice over IP (VoIP) linear predictive coding analysis-by-synthesis linear Prediction coding speech coding Packet loss ENCODER Packet switched networks Packet FRAMES linear prediction loss probability redefinition Speech Frame

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Adapting entropy constrained coding of spectral envelope for fixed-rate coding in AMR speech codec

Adapting entropy constrained coding of spectral envelope for...

引用

Proceedings of the International Convention MIPRO

作者： T. Tadić D. Petrinović Research & Development Center Ericsson Nikola Tesla d.d. Zagreb Croatia Faculty of Electrical Engineering University of Zagreb Zagreb Croatia

The Adaptive Multirate (AMR) speech codec operates in 8 different fixed-rate modes. In every mode, it uses a specified number of bits to quantize and encode the current speech frame. It encodes the spectral envelope by means of Line Spectral Frequencies (LSF) parameters, by using the constrained resolution (CR) fixed-rate Split Matrix Quantization (SMQ) and Split Vector Quantization (SVQ) methods. However, by using the Gaussian Mixture Model (GMM) based transform coding technique, the quantization of the spectral envelope can be significantly improved in the spectral distortion (SD) sense. This technique involves adaptive decorrelation of the LSF vectors by applying an orthogonal linear transformation combined with an ordinary scalar quantization of the decorrelated vector's components. We apply uniform scalar quantization followed by entropy constrained (EC) coding as it appears to be generally more efficient than non-uniform scalar quantizers. This paper describes the techniques used to adapt the entropy coded variable bit-rate output bit strings to the AMR codec modes using fixed-rate output bit strings. In order to constrain the length of the code, we use variable quantization step size and vector truncation techniques. Their application aspects are thoroughly investigated and described in this paper.

关键词： Speech codecs Decorrelation Frequency Transform coding Nonlinear distortion Bit rate Entropy coding Vector quantization Speech coding linear predictive coding

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A Discrete Wavelet Transform Based Approach to Hindi Speech Recognition

A Discrete Wavelet Transform Based Approach to Hindi Speech ...

引用

International Conference on Signal Acquisition and Processing, ICSAP

作者： Shivesh Ranjan Electronics and Communication Engineering Manipal Institute of Technology Manipal India

ISBN: (纸本)9781424457243;9780769539607

In this paper, we propose a new scheme for recognition of isolated words in Hindi Language speech, based on the Discrete Wavelet Transform. We first compute the Discrete Wavelet Transform coefficients of the speech signal. Then, linear predictive coding Coefficients of the Discrete Wavelet Transform coefficients are calculated. Our scheme then uses K Means Algorithm on the obtained linear predictive coding Coefficients to form a Vector Quantized codebook. Recognition of a spoken Hindi word is carried out by first calculating its Discrete Wavelet Transform Coefficients, followed by linear predictive coding Coefficient calculation of these Discrete Wavelet Transform Coefficients, and then deciding in favor of the Hindi word whose corresponding centroid (in the Vector Quantized codebook) gives a minimum squared Euclidean distance error with respect to the word under test.

关键词： Discrete wavelet transforms Speech recognition Multiresolution analysis linear predictive coding Testing Speech analysis Databases Natural languages Vectors Wavelet analysis

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OBJECTIVE QUALITY ASSESSMENT OF SPEECH ENHANCEMENT ALGORITHMS USING BOOTSTRAP-BASED MULTIPLE HYPOTHESES TESTS

OBJECTIVE QUALITY ASSESSMENT OF SPEECH ENHANCEMENT ALGORITHM...

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IEEE International Conference on Acoustics, Speech, and Signal Processing

作者： Zhihua Lu Philipp Heidenreich Abdelhak M. Zoubir Signal Processing Group Technische Universitat Darmstadt Merckstrasse 25 Darmstadt 64283 Germany

ISBN: (纸本)9781424442959

In this paper bootstrap resampling techniques are applied to assess speech quality and thereby evaluate performance of distinct speech enhancement algorithms, under the assumption that the speech segments can be approximated by an autoregressive model. A bootstrap-based multiple hypotheses testing procedure is constructed to test a distance measure based on linear predictive coding, which is the log-likelihood ratio distance. It is shown that the multiple hypotheses test results correlate well with conventional numerical distance measures, which suggests the applicability of the proposed procedure in assessment of speech quality as well as speech enhancement algorithms.

关键词： Bootstrap speech signal processing linear predictive coding multiple hypothesis testing linear Prediction coding bootstrapping Hypothesis testing distance measurement Speech Voice Signal Quality assessment Speech enhancement

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Low-Complexity PARCOR Coefficient Quantizer and Prediction Order Estimator for G.711.0 (Lossless Speech coding)

Low-Complexity PARCOR Coefficient Quantizer and Prediction O...

引用

Data Compression Conference (DCC)

作者： Yutaka Kamamoto Takehiro Moriya Noboru Harada NTT Communication Science Laboratories Nippon Telegraph and Telephone Corporation Atsugi Kanagawa Japan

ISBN: (纸本)9781424464258;9780769539942

This paper presents two low-complexity tools used for the new ITU-T recommendation G.711.0, which is the standard for lossless compression of G.711 (A-law/Mu-law logarithmic PCM) speech data. One is an algorithm for quantizing the PARCOR/reflection coefficients and the other is an estimation method for the optimal prediction order. Both tools are based on a criterion that minimizes the entropy of the prediction residual signals and can be implemented in a fixed-point low-complexity algorithm. G.711.0 with the developed practical tools will be widely used everywhere because it can losslessly reduce the data rate of G.711, the prevailing speech-coding technology.

关键词： Speech coding Phase change materials Entropy Signal processing Reflection Pulse modulation Codecs Quantization linear predictive coding Decoding

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LOW-COMPLEXITY PARCOR COEFFICIENT QUANTIZER AND PREDICTION ORDER ESTIMATOR FOR LOSSLESS SPEECH coding

LOW-COMPLEXITY PARCOR COEFFICIENT QUANTIZER AND PREDICTION O...

引用

IEEE International Conference on Acoustics, Speech, and Signal Processing

作者： Yutaka Kamamoto Takehiro Moriya Noboru Harada NTT Communication Science Laboratories Nippon Telegraph and Telephone Corporation JAPAN

ISBN: (纸本)9781424442959

This paper describes two low-complexity tools used for the new ITU-T recommendation G.711.0, the lossless coding of G.711 (A-law/mu-law logarithmic PCM) speech data. One is an algorithm for quantizing the PARCOR/reflection coefficients and the other is an estimation method for the optimal prediction order. Both tools are based on a criterion that minimizes the entropy of the prediction residual signals and can be implemented in a fixed-point low-complexity algorithm. G.711.0 with the developed practical tools will be widely used everywhere because it can losslessly reduce the data rate of G.711, the prevailing speech-coding technology.

关键词： Speech coding Lossless compression Standardization linear predictive coding G.711 lossless compression speech coding quantizer linear Prediction coding Standardization Speech Data transfer rates

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Automatic filter design for synthesis of haptic textures from recorded acceleration data

Automatic filter design for synthesis of haptic textures fro...

引用

IEEE International Conference on Robotics and Automation (ICRA)

作者： Joseph M. Romano Takashi Yoshioka Katherine J. Kuchenbecker Haptics Group GRASP Laboratory University of Pennsylvania USA Zanvyl Krieger Mind/Brain Institute Johns Hopkins University USA

Sliding a probe over a textured surface generates a rich collection of vibrations that one can easily use to create a mental model of the surface. Haptic virtual environments attempt to mimic these real interactions, but common haptic rendering techniques typically fail to reproduce the sensations that are encountered during texture exploration. Past approaches have focused on building a representation of textures using a priori ideas about surface properties. Instead, this paper describes a process of synthesizing probe-surface interactions from data recorded from real interactions. We explain how to apply the mathematical principles of linear predictive coding (LPC) to develop a discrete transfer function that represents the acceleration response under specific probe-surface interaction conditions. We then use this predictive transfer function to generate unique acceleration signals of arbitrary length. In order to move between transfer functions from different probe-surface interaction conditions, we develop a method for interpolating the variables involved in the texture synthesis process. Finally, we compare the results of this process with real recorded acceleration signals, and we show that the two correlate strongly in the frequency domain.

关键词： Filters Haptic interfaces Acceleration Surface texture Transfer functions Signal synthesis linear predictive coding Probes Cognitive science Virtual environment

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Singer and music discrimination based threshold in polyphonic music

Singer and music discrimination based threshold in polyphoni...

引用

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

作者： Hassan Ezzaidi Mohammed Bahoura Jean Rouat Department of Applied Sciences University of Quebec Chicoutimi Chicoutimi QUE Canada Department of Engineering University of Quebec Rimouski Rimouski QUE Canada Department Electrical & Computer Engineering University of Sherbrooke Sherbrooke QUE Canada

Song and music discrimination play a significant role in multimedia applications such as genre classification and singer identification. Song and music discrimination play a significant role in multimedia applications such as genre classification and singer identification. The problem of identifying sections of singer voice and instrument signals is addressed in this paper. It must therefore be able to detect when a singer starts and stops singing. In addition, it must be efficient in all circumstances that the interpreter is a man or a woman or that he or she has a different register (soprano, alto, baritone, tenor or bass), different styles of music and independent of the number of instruments. Our approach does not assume a priori knowledge of song and music segments. We use simple and efficient threshold-based distance measurements for discrimination. Linde-Buzo-Gray vector quantization algorithm and Gaussian Mixture Models (GMMs) are used for comparison purposes. Our approach is validated on a large experimental dataset from the music genre database RWC that includes many styles (25 styles and 272 minutes of data).

关键词： Instruments Mel frequency cepstral coefficient Databases Speech Feature extraction Training linear predictive coding

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Research on Speaker Recognition Based on Multifractal Spectrum Feature

Research on Speaker Recognition Based on Multifractal Spectr...

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International Conference on Computer Modeling and Simulation, ICCMS

作者： Yuhuan Zhou Jinming Wang Xiongwei Zhang People''s Liberation Army University of Science and Technology Nanjing China

In this paper, a new nonlinear feature extraction method based on the WTMM (wavelet transform modulus-maxima method) is proposed, which can greatly facilitate the extraction of the multifractal spectrum feature (MSF) from speech signals. The MSF combined with traditional linear features can obviously improve the performance of speaker recognition system. Experiment results show that 6-dimensional MSF combined with LPC make recognition accuracy increase 6.4 percentage points, and 6-dimensional MSF combined with MFCC, LPC make recognition accuracy increase 1.6 percentage points and reach 98.8% in short speech (2 seconds) speaker recognition.

关键词： Speaker recognition Fractals Speech analysis Feature extraction Wavelet transforms linear predictive coding Speech recognition Geometry Mel frequency cepstral coefficient Data mining

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