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AN IMPROVED LPC ALGORITHM FOR VOICED-SPEECH SYNTHESIS

IEEE TRANSACTIONS ON ACOUSTICS SPEECH AND SIGNAL PROCESSING 1984年第1期32卷 180-183页

作者： SHICHOR, E SILVERMAN, HF BROWN UNIV DIV ENGN PROVIDENCE RI 02912 USA

Current LPC synthesizers have a problem when the driving function is periodic; an output synthesized from LPC analysis has spectral properties which are not identical to those of the analyzed input. These distortions prevent a vocoder from being truly transparent for many voiced sounds. An iterative method, which modifies the conventional LPC coefficients such that the autocorrelation function of the output becomes identical to that of the input, is presented. A methodology for keeping the increased computational cost to a minimum is also to be discussed.

关键词： linear predictive coding Filters Autocorrelation Speech processing predictive models Speech synthesis Synthesizers Equations Testing Signal processing algorithms

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ANALYSES AND EXPERIMENTS ON THE DM INTO LPC TANDEM

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IEEE TRANSACTIONS ON ACOUSTICS SPEECH AND SIGNAL PROCESSING 1982年第3期30卷 436-439页

作者： MCVAY, JW GIBSON, JD TEXAS A&M UNIV DEPT ELECT ENGNCOLLEGE STNTX 77843 SEISMOG SERV CORP TULSAOK

Present plans for a defense communications digital voice network require both 16 kbit/s delta modulation (DM) and 2.4 kbit/s linear predictive coding (LPC). Unfortunately, when the output of a delta modulator receiver is used as the input to an LPC system, the speech synthesized by the LPC receiver is noticeably degraded. This paper investigates the use of sequential estimation algorithms to reduce this degradation without changing the given DM and LPC system designs. It is found that a particular scalar sequential filtering structure reduces the Itakura spectral distance measure by 60 percent, provides a more accurate LPC output spectrum, and provides a definite perceptual improvement in output speech quality. Most of the improvement is at higher frequencies, however.

关键词： Delta modulation linear predictive coding Speech synthesis Speech analysis Degradation Transmitters Signal processing algorithms Network synthesis Particle measurements Frequency

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WINDOWLESS TECHNIQUES FOR LPC ANALYSIS

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IEEE TRANSACTIONS ON ACOUSTICS SPEECH AND SIGNAL PROCESSING 1980年第4期28卷 421-427页

作者： BARNWELL, TP School of Electrical Engineering Georgia Institute of Technology Atlanta GA USA

The purpose of this work was to study, experimentally, two windowless LPC analysis algorithms for use in speech digitization. The two algorithms are a circular autocorrelation technique which utilizes the pseudoperiodic nature of voiced speed, and a reflection coefficient estimation technique suggestion by J. P. Burg. Both techniques showed considerable promise in the experimental results.

关键词： linear predictive coding Speech analysis Signal processing algorithms Algorithm design and analysis Signal analysis Vocoders Feature extraction Digital filters Autocorrelation Transfer functions

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SWITCHING SYSTEMS AND SWITCHING SOFTWARE-DEVELOPMENT IN CHINA

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IEEE COMMUNICATIONS MAGAZINE 1993年第7期31卷 56-60页

作者： CHEN, JL YAN, LM LI, YG CHINA ACAD POST & TELECOMMUN BEIJINGPEOPLES R CHINA CHINA NATL POSTS & TELECOMMUN IND CORP BEIJINGPEOPLES R CHINA

The architectures of two medium-sized digital telephone switching systems that were developed in China, the DS-30 and HJD-04 systems, are discussed. The DS-30 is a 30000 line digital telephone switching system, with a total capacity of 300000 busy hour call attempts (BHCA) using digital line concentration and a time-space-time switch fabric. Its architecture is a distributed control, multistage, multiprocessor system with load and function sharing. The HJD-04 is a 30000 line digital telephone switching system, with a total capacity of 2 million BHCA. The significant feature of the HJD-04 system is its switching network, which consists of a single time switch. The structure of the switching software support environment used in China is discussed.< >

关键词： Switching systems Programming Switches Telephony Communication system control Process control Control systems Communication switching Computer architecture linear predictive coding

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APPLYING IMPROVED SPECTRAL MODELING FOR HIGH QUALITY VOICE CONVERSION

APPLYING IMPROVED SPECTRAL MODELING FOR HIGH QUALITY VOICE C...

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IEEE International Conference on Acoustics, Speech and Signal Processing

作者： Villavicencio, Fernando Roebel, Axel Rodet, Xavier Univ Pompeu Fabra Music Technol Grp Ocata 1 Barcelona 08003 Spain CNRS IRCAM STMS Anal Synthesis Team F-75004 Paris France

ISBN: (纸本)9781424423538

In this work, accurate spectral envelope estimation is applied to Voice Conversion in order to achieve High-Quality timbre conversion. True-Envelope based estimators allow model order selection leading to an adaptation of the spectral features to the characteristics of the speaker. Optimal residual signals can also be computed following a local adaptation of the model order in terms of the F-0. A new perceptual criteria is proposed to measure the impact of the spectral conversion error. The proposed envelope models show improved spectral conversion performance as well as increased converted-speech quality when compared to linear Prediction.

关键词： Speech synthesis speech analysis cepstral analysis spectral analysis linear predictive coding

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Support Vector Machines and MLP for automatic classification of seismic signals at Stromboli volcano

Support Vector Machines and MLP for automatic classification...

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19th Italian Workshop of the Italian-Society-for-Neural-Network (SIREN) on Neural Nets (WIRN)

作者： Giacco, Ferdinando Esposito, Antonietta Maria Scarpetta, Silvia Giudicepietro, Flora Marinaro, Maria Univ Salerno Dept Phys I-84081 Baronissi SA Italy Osserv Vesuviano Ist Nazl Geofis & Vulcanol Naples Italy Ist Nazl Fis Nucl Salerno Italy INFM CNISM Salerno Italy Inst Adv Sci Studies Vietri Sul Mare Italy

ISBN: (纸本)9781607500728

We applied and compared two supervised pattern recognition techniques, namely the Multilayer Perceptron (MLP) and Support Vector Machine (SVM), to classify seismic signals recorded on Stromboli volcano. The available data are firstly preprocessed in order to obtain a compact representation of the raw seismic signals. We extract from data spectral and temporal information so that each input vector is made up of 71 components, containing both spectral and temporal information extracted from the early signal. We implemented two classification strategies to discriminate three different seismic events: landslide, explosion-quake, and volcanic microtremor signals. The first method is a two-layer MLP network, with a Cross-Entropy error function and logistic activation function for the output units. The second method is a Support Vector Machine, whose multi-class setting is accomplished through a 1vsAll architecture with gaussian kernel. The experiments show that although the MLP produces very good results, the SVM accuracy is always higher, both in term of best performance, 99.5%, and average performance, 98.8%, obtained with different sampling permutations of training and test sets.

关键词： Seismic signals discrimination linear predictive coding Neural Networks Support Vector Machine Multilayer Perceptron

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A SPEAKER-INDEPENDENT, SYNTAX-DIRECTED, CONNECTED WORD RECOGNITION SYSTEM BASED ON HIDDEN MARKOV-MODELS AND LEVEL BUILDING

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IEEE TRANSACTIONS ON ACOUSTICS SPEECH AND SIGNAL PROCESSING 1985年第3期33卷 561-573页

作者： RABINER, LR LEVINSON, SE AT and T Bell Laboratories Inc. Murray Hill NJ USA

In the last several years, a wide variety of techniques have been developed which make practical the implementation and development of large networks for recognizing connected sequences of words. Included among these techniques are efficient and accurate speech modeling methods (e.g., vector quantization, hidden Markov models) and efficient, optimal network search procedures (i.e., level building). In this paper we show how to integrate these techniques to give a speaker-independent, syntax-directed, connected word recognition system which requires only a modest amount of computation, and whose performance is comparable to that of previous recognizers requiring an order of magnitude more computation. In particular, the recognizer we studied was an airlines information and reservation system using a 129 word vocabulary, and a deterministic syntax (grammar) with 144 states, 450 state transitions, and 21 final states, generating more than 6 × 10 9 sentences. An evaluation of the system, using six talkers each speaking 51 test sentences, yielded a sentence accuracy of about 75 percent resulting from a word accuracy of about 93 percent, for an average speaking rate of about 210 words per minute.

关键词： Hidden Markov models Vocabulary Speech recognition Natural languages linear predictive coding Speech analysis Vector quantization System testing Laboratories Computer networks

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A HYBRID TIME-FREQUENCY DOMAIN ARTICULATORY SPEECH SYNTHESIZER

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IEEE TRANSACTIONS ON ACOUSTICS SPEECH AND SIGNAL PROCESSING 1987年第7期35卷 955-967页

作者： SONDHI, MM SCHROETER, J AT and T Bell Laboratories Inc. Murray Hill NJ USA

High quality speech at low bit rates (e.g., 2400 bits/s) is one of the important objectives of current speech research. As part of long range activity on this problem, we have developed an efficient computer program that will serve as a tool for investigating whether articulatory speech synthesis may achieve this low bit rate. At a sampling frequency of 8 kHz, the most comprehensive version of the program, including nasality and frication, runs at about twice real time on a Cray-1 computer.

关键词： Time frequency analysis Speech synthesis Synthesizers Bit rate Signal synthesis Transmission line matrix methods linear predictive coding predictive models Speech analysis Size control

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Enhanced Spin-Down Diagnostics for Nondestructive Evaluation of High-Value Systems 34th

Enhanced Spin-Down Diagnostics for Nondestructive Evaluation...

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34th IMAC Conference and Exposition on Structural Dynamics

作者： Sehloff, David Shurtleff, Clark Pribe, Josh Haynes, Colin Heit, John Washington Univ Dept Elect & Syst Engn St Louis MO USA Univ Penn Dept Mat Sci & Engn 3231 Walnut St Philadelphia PA 19104 USA Missouri Univ Sci & Technol Dept Mech & Aerosp Engn Rolla MO USA Los Alamos Natl Lab Weap Engn Los Alamos NM 87544 USA

ISBN: (纸本)9783319300849;9783319300832

The nature of some high-value systems requires that damage be detected without disassembly of the test article. Spin-down testing, one such nondestructive evaluation method, involves spinning a test article and observing its angular deceleration. An increase in angular deceleration compared to an identical test of a healthy system indicates damage has occurred. However, current testing is limited, providing only a binary result of "damaged" or "undamaged". More sophisticated techniques are required to identify the location, extent, and type of damage. To achieve this, non-contact and surface-mounted sensors were used to monitor the test article in this experiment. A spin-down unit was used to test both a healthy specimen and a specimen with simulated damage. The signals from each sensor were compared across tests. Correlation of anomalous signals with rotational position and multi-sensor triangulation techniques were used to localize damage. Analysis of the frequency content and amplitude of output signals allowed for a degree of characterization of the damage. Through these techniques, spin-down testing was enhanced from a binary detector to a more thorough testing method giving detailed information about the type and location of damage.

关键词： Spin-down testing Rotating system Nondestructive evaluation Acoustic emissions sensing linear predictive coding

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A STUDY OF LPC ANALYSIS OF SPEECH IN ADDITIVE NOISE

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IEEE TRANSACTIONS ON ACOUSTICS SPEECH AND SIGNAL PROCESSING 1980年第4期28卷 389-397页

作者： TIERNEY, J Lincoln Laboratory Massachusetts Institute of Technology Lexington MA USA

A study of the autocorrelation LPC analysis of speech in additive noise is presented. In the noise-free case it is shown that finite word length implementation of the analysis may produce stable but poor spectral estimates. The beneficial effects of proper preemphasis are reaffirmed in terms of decreased numerical error as well as decreased LPC order needed for a good spectral fit. For the ease of noisy input speech the conditions for severe distortion of the spectral estimate are presented. A proper LPC spectral analysis of speech in additive noise is shown to require a higher order fit than currently used, a more precise implementation, and a more accurate parameter quantization for transmission.

关键词： Speech analysis linear predictive coding Speech enhancement Additive noise Noise shaping Acoustic noise Acoustic distortion Vocoders Autocorrelation Quantization

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