Conferences related to Speech Analysis

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ICASSP 2020 - 2020 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP)

The ICASSP meeting is the world's largest and most comprehensive technical conference focused on signal processing and its applications. The conference will feature world-class speakers, tutorials, exhibits, and over 50 lecture and poster sessions.


IECON 2020 - 46th Annual Conference of the IEEE Industrial Electronics Society

IECON is focusing on industrial and manufacturing theory and applications of electronics, controls, communications, instrumentation and computational intelligence.


2019 IEEE International Professional Communication Conference (ProComm)

The scope of the conference includes the study, development, improvement, and promotion ofeffective techniques for preparing, organizing, processing, editing, collecting, conserving,teaching, and disseminating any form of technical information by and to individuals and groupsby any method of communication. It also includes technical, scientific, industrial, and otheractivities that contribute to the techniques and products used in this field.


2018 15th IEEE Annual Consumer Communications & Networking Conference (CCNC)

IEEE CCNC 2018 will present the latest developments and technical solutions in the areas of home networking, consumer networking, enabling technologies (such as middleware) and novel applications and services. The conference will include a peer-reviewed program of technical sessions, special sessions, business application sessions, tutorials, and demonstration sessions


2018 IEEE 61st International Midwest Symposium on Circuits and Systems (MWSCAS)

Analog Circuits, Digital VLSI Circuits, Neural Networks, Non-Linear System, Computer Aided Design, Communication Systems, Digital Signal Processing, MEMS, Nano-electronics


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Periodicals related to Speech Analysis

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Audio, Speech, and Language Processing, IEEE Transactions on

Speech analysis, synthesis, coding speech recognition, speaker recognition, language modeling, speech production and perception, speech enhancement. In audio, transducers, room acoustics, active sound control, human audition, analysis/synthesis/coding of music, and consumer audio. (8) (IEEE Guide for Authors) The scope for the proposed transactions includes SPEECH PROCESSING - Transmission and storage of Speech signals; speech coding; speech enhancement and noise reduction; ...


Biomedical Engineering, IEEE Transactions on

Broad coverage of concepts and methods of the physical and engineering sciences applied in biology and medicine, ranging from formalized mathematical theory through experimental science and technological development to practical clinical applications.


Communications Magazine, IEEE

IEEE Communications Magazine was the number three most-cited journal in telecommunications and the number eighteen cited journal in electrical and electronics engineering in 2004, according to the annual Journal Citation Report (2004 edition) published by the Institute for Scientific Information. Read more at http://www.ieee.org/products/citations.html. This magazine covers all areas of communications such as lightwave telecommunications, high-speed data communications, personal communications ...


Communications, IEEE Transactions on

Telephone, telegraphy, facsimile, and point-to-point television, by electromagnetic propagation, including radio; wire; aerial, underground, coaxial, and submarine cables; waveguides, communication satellites, and lasers; in marine, aeronautical, space and fixed station services; repeaters, radio relaying, signal storage, and regeneration; telecommunication error detection and correction; multiplexing and carrier techniques; communication switching systems; data communications; and communication theory. In addition to the above, ...


Computer

Computer, the flagship publication of the IEEE Computer Society, publishes peer-reviewed technical content that covers all aspects of computer science, computer engineering, technology, and applications. Computer is a resource that practitioners, researchers, and managers can rely on to provide timely information about current research developments, trends, best practices, and changes in the profession.


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Most published Xplore authors for Speech Analysis

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Xplore Articles related to Speech Analysis

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F0 contour estimation using ELS-based robust time-varying complex speech analysis

2011 Digital Signal Processing and Signal Processing Education Meeting (DSP/SPE), 2011

Robust F0 (Fundamental frequency) estimation plays an important role in speech processing. This paper proposes simple F0 contour estimation algorithm based on the robust TV-CAR speech analysis, in which the F0 contour is estimated by peak-picking for the estimated time-varying spectrum by means of ELS-based robust complex speech analysis for an analytic speech signal. The experimental results demonstrate that the ...


Standard and target driven AR-vector models for speech analysis and speaker recognition

[Proceedings] ICASSP-92: 1992 IEEE International Conference on Acoustics, Speech, and Signal Processing, 1992

Theoretical aspects and practical applications are reported of two variants of the AR-vector modeling technique: the standard AR-vector model and the target driven (or multistep excited) AR-vector model. The standard version supposes a white excitation, while the target driven model assumes a piecewise constant input. The standard AR-vector model turns out to be extremely efficient for speaker recognition, since, for ...


Research and implementation of linear predictive speech analysis and synthesis

China., 1991 International Conference on Circuits and Systems, 1991

The purpose of this paper, which deals with research on the linear predictive speech analysis and synthesis system, is to provide feature analysis for the study on speaker recognition and the development of VCEA (Voice Countermeasures Effectiveness Analysis). The analysis conditions and algorithms are determined, an efficient method for pitch extraction is designed, and the TMS32020 software is developed and ...


Rule-based speech analysis and application of CELP coding

ICASSP-88., International Conference on Acoustics, Speech, and Signal Processing, 1988

An approach is presented for efficiently encoding speech signals at low bit rates, by exploiting a combination of various speech analysis and compression techniques cooperating via a rule-based reasoning system. A front-end analyzer compresses speech events at nonuniformly spaced time intervals, by resorting to dynamic and static variable-frame-rate methods relevant to perception models. Then a codebook-excited-linear-predictive (CELP) coder performs a ...


Speech analysis based on locally linear embedding(LLE)

2010 Sixth International Conference on Natural Computation, 2010

This paper describes a novel speech analysis method that creates a readable pattern based on locally linear embedding (LLE). LLE is an unsupervised learning algorithm for feature extraction. If the speech variability is described by a small number of continuous features, then we can imagine the data as lying on a low dimensional manifold in the high dimensional space of ...


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Educational Resources on Speech Analysis

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IEEE-USA E-Books

  • F0 contour estimation using ELS-based robust time-varying complex speech analysis

    Robust F0 (Fundamental frequency) estimation plays an important role in speech processing. This paper proposes simple F0 contour estimation algorithm based on the robust TV-CAR speech analysis, in which the F0 contour is estimated by peak-picking for the estimated time-varying spectrum by means of ELS-based robust complex speech analysis for an analytic speech signal. The experimental results demonstrate that the proposed method leads to more accurate continuous F0 estimation than the conventional ones for high-pitched speech.

  • Standard and target driven AR-vector models for speech analysis and speaker recognition

    Theoretical aspects and practical applications are reported of two variants of the AR-vector modeling technique: the standard AR-vector model and the target driven (or multistep excited) AR-vector model. The standard version supposes a white excitation, while the target driven model assumes a piecewise constant input. The standard AR-vector model turns out to be extremely efficient for speaker recognition, since, for a set of 420 different speakers, the recognition score ranges from 93% to 100%, depending on the duration of the test speech sample. The target driven AR-vector model shows very interesting properties for speech analysis and segmentation. There exists a strong correspondence between the steps in the input function and the underlying phonetic content of speech. Moreover, under some normalization, the values of the steps can be interpreted as acoustic targets.<<ETX>>

  • Research and implementation of linear predictive speech analysis and synthesis

    The purpose of this paper, which deals with research on the linear predictive speech analysis and synthesis system, is to provide feature analysis for the study on speaker recognition and the development of VCEA (Voice Countermeasures Effectiveness Analysis). The analysis conditions and algorithms are determined, an efficient method for pitch extraction is designed, and the TMS32020 software is developed and debugged with the help of computer simulation. Analysis and synthesis are implemented in real time by TMS32020. A single Texas Instruments TMS32020 microprocessor performs LPC analysis, pitch detection, synthesis, and data I/O.<<ETX>>

  • Rule-based speech analysis and application of CELP coding

    An approach is presented for efficiently encoding speech signals at low bit rates, by exploiting a combination of various speech analysis and compression techniques cooperating via a rule-based reasoning system. A front-end analyzer compresses speech events at nonuniformly spaced time intervals, by resorting to dynamic and static variable-frame-rate methods relevant to perception models. Then a codebook-excited-linear-predictive (CELP) coder performs a perceptually meaningful identification and quantization of the excitation parameters, to provide an optimal rendition of the original signal. This coding scheme can reduce the transmission rate down to 2.4-2.8 kb/s, while retaining a very good quality. The main applications are in voice response systems and voice mail.<<ETX>>

  • Speech analysis based on locally linear embedding(LLE)

    This paper describes a novel speech analysis method that creates a readable pattern based on locally linear embedding (LLE). LLE is an unsupervised learning algorithm for feature extraction. If the speech variability is described by a small number of continuous features, then we can imagine the data as lying on a low dimensional manifold in the high dimensional space of speech waveforms. The goal of feature extraction is to reduce the dimensionality of the speech signal while preserving the informative signatures. In this paper we have present results from the analysis of speech data using PCA and LLE. And we observed that the nonlinear embeddings of LLE separated certain Chinese phonemes better than the linear projections of PCA.

  • Phonetic Speech Analysis for Speech to Text Conversion

    This paper presents a description of the work done on phonetic speech analysis. The work aims in generating phonetic codes of the uttered speech in training-less, human independent manner. This work is guided by the working of ear in response to audio signals. The Devnagri script inspires the work presented. The Devnagari script classifies and arranges 46 phonemes in a scientific manner based on the process of its generation. The work at present focuses on identifying the class (varna) of the phoneme as specified by the Devnagari script. More work is needed to identify the variant of the class identified. Phoneme code thus generated can be used in an application specific way. This work also explains and proves the scientific arrangement of the Devnagari script. This work tries to segment speech into phonemes and identify the phoneme using simple operations like differentiation, zero-crossing calculation and FFT.

  • Time-varying linear prediction for speech analysis and synthesis

    In this contribution, a time-varying linear prediction is proposed for speech analysis and synthesis. In comparison to the time-invariant prediction, the predictor coefficients are time-varying within the frames. For that purpose, the coefficient trajectories can be described by basis functions. This approach leads to discontinuities between the frames if the frames are analyzed independently. Therefore, continuous conditions are defined which force continuous trajectories also between the frames. The estimation of the optimum coefficients of the basis functions is solved analytically by a least mean square approach. The analysis results show that the estimation algorithm achieves smooth trajectories of the vocal-tract resonances together with a high time resolution, which is interesting for a variety of application.

  • RASTA-PLP speech analysis technique

    Most speech parameter estimation techniques are easily influenced by the frequency response of the communication channel. The authors have developed a technique that is more robust to such steady-state spectral factors in speech. The approach is conceptually simple and computationally efficient. The new method is described, and experimental results are proposed that show significant advantages for the proposed method.<<ETX>>

  • Quantizer design in LSP speech analysis and synthesis

    The performance of several algorithms for the quantization of the line spectrum pair (LSP) parameters is studied. An adaptive method which utilizes the ordering property of the LSP parameters is presented. The performance of the different quantization schemes is studied on a long sequence of speech samples. For the spectral distortion measure, appropriate performance comparisons between the different quantization schemes are rendered. Experimental results indicate that high-quality synthesized speech can be obtained using the LSP parameters at relatively low rates.<<ETX>>

  • ARES: An environment for speech analysis and labelling

    The ARES (analyze, represent, and elaborate speech) software environment, based on the Tektronix 4125 workstation and VAX 11/750 computer is presented. The sampling procedure makes it possible to store in a RA81 disk up to 6.5 h of speech at a 10 kHz sampling rate. The information related to each utterance is organized in a database. Fundamental characteristics of speech, waveform, power spectrum, pitch, and such other useful parameters as formant frequency and zero crossing rate are computed using an array processor and are displayed with the Tektronix graphic facility. The software organization makes it easy to introduce a new feature pattern, and a special graphic option makes it possible to represent these new data in the old scale.<<ETX>>



Standards related to Speech Analysis

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Jobs related to Speech Analysis

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