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检索条件"主题词=linear predictive coding"

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Phonetic and intonation enhancement of speech for Japanese hearing-impaired speakers

Phonetic and intonation enhancement of speech for Japanese h...

引用

IEEE International Conference on Multimedia and Expo (ICME)

作者： Shogo Watanabe Tsuyoshi Moriyama Shinji Ozawa Department of Information and Computer Science Keio University Yokohama Kanagawa Japan Department of Media and Image Technology Tokyo Polytechnic University Japan

We propose a system that is capable of improving intelligibility of speech by those with hearing impairment. We have found the speech often had problems in the intonation, the duration of the unvoiced consonants, and the tone of the voiced phonemes. The system systematically compensates problematic components of the speech using the counterparts in normal speech. It corrects the intonation using TD-PSOLA and elongates consonants by repeating the original waveform using inverting technique for making the result continuously connected until the duration reaches a threshold. Experimental results show that the proposed method successfully improves the intelligibility of the speech from 28% to 35% by making phonemes more articulated, and making double consonants, dasianpsila of syllabic consonant, and unvoiced consonants perceived clearer.

关键词： Speech Speech recognition Auditory system Speech enhancement Training Logic gates linear predictive coding

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New feature extraction methods using DWT and LPC for isolated word recognition

New feature extraction methods using DWT and LPC for isolate...

引用

IEEE Region 10 International Conference TENCON

作者： N. S. Nehe R. S. Holambe S.G.G.S. Institute of Engineering and Technology Nanded India

In this paper a new feature extraction methods, which utilize reduced order linear predictive coding (LPC) coefficients for speech recognition, have been proposed. The coefficients have been derived from the speech frames decomposed using Discrete Wavelet Transform (DWT). In the literature it is assumed that the speech frame of size 10 msec to 30 msec is stationary, however, in practice different parts of the speech signal may convey different amount of information (hence may not be perfectly stationary). LPC coefficients derived from subband decomposition of speech frame provide better representation than modeling the frame directly. Experimentally it has been shown that, the proposed approaches provide effective (better recognition rate) and efficient (reduced feature vector dimension) features. The speech recognition system using the continuous Hidden Markov Model (HMM) has been implemented. The proposed algorithms are evaluated using NIST TI-46 isolated-word database.

关键词： Feature extraction Discrete wavelet transforms linear predictive coding Speech recognition Hidden Markov models Speech processing Signal processing Wavelet packets Frequency Vectors

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Matrix-based linear predictive compression of multi-channel surface emg signals

Matrix-based linear predictive compression of multi-channel ...

引用

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

作者： Elias S. G. Carotti J. C. De Martin Roberto Merletti Dario Farina DAUIN Politecnico di Torino Torino Italy DELET-Politecnico di Torino Torino Italy Department of Health Science and TechnologyCenter for Sensory-Motor Interaction University of Aalborg Aalborg Denmark

We propose a linear predictive coding technique for multichannel electromyographic (EMG) recordings. The signals are acquired using two-dimensional grid of electrodes which generate strongly correlated signals. Previous work only considered spectral redundancy across the signal matrix. In this paper we exploit the correlation present in the residual signals, i.e., the signals after the short term prediction. The proposed technique achieves a compression ratio of about 1divide9, i.e., slightly better than spectral-only decorrelation methods, but with a strong increase of approximately 3.2 dB SNR in the quality of the reconstructed waveform.

关键词： Electromyography Filters Quantization Speech coding Muscles Sensor arrays Decoding linear predictive coding Electrodes Surface reconstruction

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A Transmission Scheme for Encrypted Speech over GSM Network

A Transmission Scheme for Encrypted Speech over GSM Network

引用

International Symposium on Computer Science and Computational Technology, ISCSCT

作者： Yucun Yang Suili Feng Wu Ye Xinsheng Ji School of Electronic and Information Engineering South China University of Technology Guangzhou China National Digital Switching System Engineering and Technological Research and Development Center Zhengzhou China

With the widely applications of mobile communication networks, end-to-end secure voice has become a very important research issue and has attracted many people¿s interests. A simple and effective method for end-to-end secure communication is to encrypt speech signal at user ends. But the use of encryption techniques leads to a hard problem that encrypted speech data can not be directly transmitted on mobile voice channel. In this paper, we propose a scheme for encrypted speech transmitting on GSM voice channel. Not only does this scheme offer a good method for encrypted speech accessing mobile voice channel by using a proposed special modem called smodem based on linear predictive coding (LPC) technique, but also it can ensure the encrypted data transmitting through GSM networks with sufficient accuracy so that the received data can be decrypted correctly at the receiver. Moreover, the proposed scheme has advantages of no change to the existing clear voice communication procedure, short time of call establishment and propagation delay, good interoperability over heterogeneous networks, and favorableness to encryption information hidden. The results of experiment show that the proposed scheme is feasible.

关键词： Cryptography GSM Mobile communication linear predictive coding Vocoders Speech coding Propagation delay Frequency Communication system security Phase change materials

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Embedded speech recognition applications in mobile phones: Status, trends, and challenges

Embedded speech recognition applications in mobile phones: S...

引用

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

作者： Jordan Cohen SRI International Inc. Menlo park CA USA

Voice centric interfaces are widely available in modern mobile phones, including low-cost versions. The applications have evolved from speaker-dependent name dialing, which require user enrollment of frequently dialed names, to speaker-independent capabilities including continuous digit dialing, command and control of phone functions, and name dialing directly from the phone's contacts directory. Recently available advances include capabilities like voice-enabled SMS, e-mail, and even mobile search with voice. This evolution has been enabled by advances in speech recognition robustness, network capabilities, and increased computational power in small devices. Systems may now be used in hands-busy/eyes-busy conditions including speakerphone and bluetooth scenarios. In this paper, we will provide an overview of embedded speech recognition centric applications in mobile phones, specifically focusing on current status, industry trends, and challenges in customer acceptance. Although voice interfaces are natural and attractive in theory, a majority of users do not use the voice-enabled features available in their mobile phones. We will discuss some of the reasons for this user behavior and recommend actions to be taken.

关键词： Speech recognition Mobile handsets linear predictive coding Hidden Markov models Signal processing algorithms Cellular phones Speech coding Space technology Application software Laboratories

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LSF and LPC - derived features for Large Vocabulary Distributed Continuous Speech Recognition in Brazilian Portuguese

LSF and LPC - derived features for Large Vocabulary Distribu...

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Asilomar Conference on Signals, Systems & Computers

作者： V. F. S. Alencar A. Alcaim CETUC Catholic University of Rio de Janeiro Rio de Janeiro Rio de Janeiro Brazil

In this paper, we describe several important experiments concerning large vocabulary distributed continuous speech recognition (LVDCSR) systems in Brazilian Portuguese using LSF and LPC - derived features. The ITU-T G.723.1 codec is employed and investigated as a case of practical use of this technology. Results are presented for both speaker dependent and independent modes as well as the situations where the same text or different texts were used for training and testing.

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

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Voice source cepstrum coefficients for speaker identification

Voice source cepstrum coefficients for speaker identificatio...

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

作者： Jon Gudnason Mike Brookes Department of Electrical and Electronic Engineering Imperial College London London UK

We propose a novel feature set for speaker recognition that is based on the voice source signal. The feature extraction process uses closed-phase LPC analysis to estimate the vocal tract transfer function. The LPC spectrum envelope is converted to cepstrum coefficients which are used to derive the voice source features. Unlike approaches based on inverse-filtering, our procedure is robust to LPC analysis errors and low-frequency phase distortion. We have performed text-independent closed-set speaker identification experiments on the TIMIT and the YOHO databases using a standard Gaussian mixture model technique. Compared to using mel- frequency cepstrum coefficients, the misclassification rate for the TIMIT database reduced from 1.51% to 0.16% when combined with the proposed voice source features. For the YOHO database the mis- classification rate decreased from 13.79% to 10.07%. The new feature vector also compares favourably to other proposed voice source feature sets.

关键词： Cepstrum linear predictive coding Spatial databases Cepstral analysis Speaker recognition Feature extraction Transfer functions Robustness Error analysis Phase distortion

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Case study for particle agglomeration during chemical mechanical polishing process

Case study for particle agglomeration during chemical mechan...

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International Conference on Solid-State and Integrated Circuit Technology

作者： Yongqing Lan Yuzhuo Li Clarkson University Potsdam NY USA BASF Corporation Ludwigshafen Germany

ISBN: (纸本)9781424421855

Over sized particles in spent slurry are analyzed to examine particle agglomeration during chemical mechanical polishing process. In tungsten (W) polishing, due to greater chance of collision for large particles, high abrasive content slurries yield less oversized particles during polishing. However, in oxide wafer polishing, fumed silica follows the similar agglomerating behavior as in tungsten polishing, while colloidal silica shows a reversed trend. Defectivity measurements on oxide wafer confirm the correlation between spent slurry large particle count (LPC) and defects number on wafers, which means agglomerates produced during polishing process may cause defects in CMP.

关键词： Chemical processes Slurries Silicon compounds Abrasives Chemical analysis Tungsten linear predictive coding Particle measurements Planarization Energy barrier

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A novel technique for Support Vector Machine based multi-class classifier

A novel technique for Support Vector Machine based multi-cla...

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IEEE Region 10 International Conference TENCON

作者： J. Manikandan B. Venkataramani V. Amudha A.Majed Arafat Hruday Sahu 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 known as Diminishing Learning (DL) is proposed for an SVM based multi-class pattern recognition system. In this technique, a sequential classifier is proposed wherein the classes which require stringent boundaries are tested one by one and once the tests for these classes fail, the stringency of the classifier is increasingly relaxed. The effect of, the sequence in which the classes are trained and tested, on the recognition accuracy is also studied in this paper. The proposed technique is applied for SVM based isolated digit recognition system and is studied using speaker 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 with and without DL technique. Based on this study, it is found that the use of diminishing learning reduces the number of support vectors by 35.5% and 39.5% respectively for SVM classifier with LPC and MFCC feature inputs. Recognition accuracies of 96% and 97% are achieved for SVM classifier with and without DL technique for LPC feature inputs respectively. Recognition accuracy of 100% is achieved for SVM with and without DL technique for MFCC feature inputs. The study confirms the effect of, the order in which the classes are trained and tested, on the recognition accuracy and for the TI46 database, about 7% increase in recognition accuracy is obtained by choosing the optimum order.

关键词： Support vector machines Support vector machine classification Spatial databases linear predictive coding Mel frequency cepstral coefficient Sequential analysis Testing Pattern classification Pattern recognition Feature extraction

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Frame energy estimation based on speech codec parameters

Frame energy estimation based on speech codec parameters

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

作者： Doh-Suk Kim Binshi Cao Ahmed Tarraf Alcatel-Lucent NJ USA

This paper proposes an efficient method for estimating frame energy of speech from enhanced variable rate coder (EVRC) bitstream for network-based speech processing applications in transcoder free operation (TrFO) environments, where speech signals are represented as speech coding parameters. A frame of speech energy is decomposed into the energy of excitation and vocal tract filter, and the frame energy estimation method is derived for each component. Among many parameters of EVRC bitstream, the fixed codebook gain and adaptive codebook gain are used for the estimation of excitation energy, and line spectrum pair (LSP) information is used to estimate the energy of vocal tract filter. Experimental results demonstrated the novelty of the proposed method. The correlation coefficient between the actual and estimated frame energy can be maintained at a value of 0.994 with just 5% multiplicative operations of full decoding.

关键词： Speech codecs Speech processing Decoding Speech coding Filters Speech synthesis linear predictive coding Speech enhancement Signal synthesis Signal processing

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