Conferences related to Mel frequency cepstral coefficient

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2020 42nd Annual International Conference of the IEEE Engineering in Medicine & Biology Society (EMBC)

The conference program will consist of plenary lectures, symposia, workshops and invitedsessions of the latest significant findings and developments in all the major fields of biomedical engineering.Submitted papers will be peer reviewed. Accepted high quality papers will be presented in oral and postersessions, will appear in the Conference Proceedings and will be indexed in PubMed/MEDLINE


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.


Oceans 2020 MTS/IEEE GULF COAST

To promote awareness, understanding, advancement and application of ocean engineering and marine technology. This includes all aspects of science, engineering, and technology that address research, development, and operations pertaining to all bodies of water. This includes the creation of new capabilities and technologies from concept design through prototypes, testing, and operational systems to sense, explore, understand, develop, use, and responsibly manage natural resources.

  • OCEANS 2018 MTS/IEEE Charleston

    Ocean, coastal, and atmospheric science and technology advances and applications

  • OCEANS 2017 - Anchorage

    Papers on ocean technology, exhibits from ocean equipment and service suppliers, student posters and student poster competition, tutorials on ocean technology, workshops and town meetings on policy and governmental process.

  • OCEANS 2016

    The Marine Technology Scociety and the Oceanic Engineering Society of the IEEE cosponor a joint annual conference and exposition on ocean science, engineering, and policy. The OCEANS conference covers four days. One day for tutorials and three for approx. 500 technical papers and 150 -200 exhibits.

  • OCEANS 2015

    The Marine Technology Scociety and the Oceanic Engineering Society of the IEEE cosponor a joint annual conference and exposition on ocean science, engineering, and policy. The OCEANS conference covers four days. One day for tutorials and three for approx. 450 technical papers and 150-200 exhibits.

  • OCEANS 2014

    The OCEANS conference covers four days. One day for tutorials and three for approx. 450 technical papers and 150-200 exhibits.

  • OCEANS 2013

    Three days of 8-10 tracks of technical sessions (400-450 papers) and concurent exhibition (150-250 exhibitors)

  • OCEANS 2012

    Ocean related technology. Tutorials and three days of technical sessions and exhibits. 8-12 parallel technical tracks.

  • OCEANS 2011

    The Marine Technology Society and the Oceanic Engineering Scociety of the IEEE cosponsor a joint annual conference and exposition on ocean science engineering, and policy.

  • OCEANS 2010

    The Marine Technology Society and the Oceanic Engineering Scociety of the IEEE cosponsor a joint annual conference and exposition on ocean science engineering, and policy.

  • OCEANS 2009

  • OCEANS 2008

    The Marine Technology Society (MTS) and the Oceanic Engineering Society (OES) of the Institute of Electrical and Electronic Engineers (IEEE) cosponsor a joint conference and exposition on ocean science, engineering, education, and policy. Held annually in the fall, it has become a focal point for the ocean and marine community to meet, learn, and exhibit products and services. The conference includes technical sessions, workshops, student poster sessions, job fairs, tutorials and a large exhibit.

  • OCEANS 2007

  • OCEANS 2006

  • OCEANS 2005

  • OCEANS 2004

  • OCEANS 2003

  • OCEANS 2002

  • OCEANS 2001

  • OCEANS 2000

  • OCEANS '99

  • OCEANS '98

  • OCEANS '97

  • OCEANS '96


2019 Chinese Control And Decision Conference (CCDC)

Chinese Control and Decision Conference is an annual international conference to create a forum for scientists, engineers and practitioners throughout the world to present the latest advancement in Control, Decision, Automation, Robotics and Emerging Technologies.

  • 2018 Chinese Control And Decision Conference (CCDC)

    Chinese Control and Decision Conference is an annual international conference to create a forum for scientists, engineers and practitioners throughout the world to present the latest advancement in Control, Decision, Automation, Robotics and Emerging Technologies.

  • 2017 29th Chinese Control And Decision Conference (CCDC)

    Chinese Control and Decision Conference is an annual international conference to create a forum for scientists, engineers and practitioners throughout the world to present the latest advancement in Control, Decision, Automation, Robotics and Emerging Technologies.

  • 2016 Chinese Control and Decision Conference (CCDC)

    Chinese Control and Decision Conference is an annual international conference to create aforum for scientists, engineers and practitioners throughout the world to present the latestadvancement in Control, Decision, Automation, Robotics and Emerging Technologies.

  • 2015 27th Chinese Control and Decision Conference (CCDC)

    Chinese Control and Decision Conference is an annual international conference to create a forum for scientists, engineers and practitioners throughout the world to present the latest advancement in Control, Decision, Automation, Robotics and Emerging Technologies.

  • 2014 26th Chinese Control And Decision Conference (CCDC)

    Chinese Control and Decision Conference is an annual international conference to create aforum for scientists, engineers and practitioners throughout the world to present the latestadvancement in Control, Decision, Automation, Robotics and Emerging Technologies.

  • 2013 25th Chinese Control and Decision Conference (CCDC)

    Chinese Control and Decision Conference is an annual international conference to create a forum for scientists, engineers and practitioners throughout the world to present the latest advancement in Control, Decision, Automation, Robotics and Emerging Technologies.

  • 2012 24th Chinese Control and Decision Conference (CCDC)

    Chinese Control and Decision Conference is an annual international conference to create a forum for scientists, engineers and practitioners throughout the world to present the latest advancement in Control, Decision, Automation, Robotics and Emerging Technologies.

  • 2011 23rd Chinese Control and Decision Conference (CCDC)

    Chinese Control and Decision Conference is an annual international conference to create a forum for scientists, engineers and practitioners throughout the world to present the latest advancement in Control, Decision, Automation, Robotics and Emerging Technologies.

  • 2010 Chinese Control and Decision Conference (CCDC)

    Chinese Control and Decision Conference is an annual international conference to create a forum for scientists, engineers and practitioners throughout the world to present the latest advancement in Control, Decision, Automation, Robotics and Emerging Technologies

  • 2009 Chinese Control and Decision Conference (CCDC)

    Chinese Control and Decision Conference is an annual international conference to create a forum for scientists, engineers and practitioners throughout the world to present the latest advancement in Control, Decision, Automation, Robotics and Emerging Technologies.

  • 2008 Chinese Control and Decision Conference (CCDC)


2019 IEEE 15th International Colloquium on Signal Processing & Its Applications (CSPA)

The colloquium will provide an excellent platform for knowledge exchange between researchers,scientists, academicians and engineers working in the areas of automation, process, scientificresearch and analysis. This event calls for local and international participation.


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Periodicals related to Mel frequency cepstral coefficient

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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.


Circuits and Systems Magazine, IEEE


Information Forensics and Security, IEEE Transactions on

Research on the fundamental contributions and the mathematics behind information forensics, information seurity, surveillance, and systems applications that incorporate these features.


Instrumentation and Measurement, IEEE Transactions on

Measurements and instrumentation utilizing electrical and electronic techniques.


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Most published Xplore authors for Mel frequency cepstral coefficient

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Xplore Articles related to Mel frequency cepstral coefficient

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New time-frequency derived cepstral coefficients for automatic speech recognition

1996 8th European Signal Processing Conference (EUSIPCO 1996), 1996

The goal is to improve recognition rate by optimisation of Mel Frequency Cepstral Coefficients (MFCCs): modifications concern the time-frequency representation used to estimate these coefficients. There are many ways to obtain a spectrum out of a signal which differ in the method itself (Fourier, Wavelets,…), and in the normalisation. We show here that we can obtain noise resistant cepstral coefficients, ...


Representing speech

2000 10th European Signal Processing Conference, 2000

The properties of the speech production process and the auditory periphery have led to the usage of similar speech signal representations for various processing tasks such as speech and speaker recognition, speech synthesis, and speech coding. The representation is generally divided into a description of the vocal-tract transfer function and the excitation source. For recognition purposes, the biased characterization of ...


Template-based personalized singing voice synthesis

2012 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP), 2012

In this paper, a template-based personalized singing voice synthesis method is proposed. It generates singing voices by means of conversion from the narrated lyrics of a song with the use of template recordings. The template voices are parallel speaking and singing voices recorded from professional singers, which are used to derive the transformation models for acoustic feature conversion. When converting ...


Audio source indexing by sub-band PCA with empirical mode decomposition

IEEE International Workshop on Intelligent Signal Processing, 2005., 2005

This paper presents a sub-bund approach of audio source indexing technique without any prior information about the sources. The empirical mode decomposition (EMD) scheme, capable of decomposing nonlinear and non- stationary signal into some bases, is employed to implement the proposed sub- band method. The feature vectors are derived from each of the selected sub- bands of the signal block. ...


A confidence measure based — Score fusion technique to integrate MFCC and Pitch for speaker verification

2011 3rd International Conference on Electronics Computer Technology, 2011

The objective of this paper is to evaluate the effectiveness of complementary speech features extracted from a speaker for verification. Traditionally, speaker verification systems use a single feature for representing speaker- specific information. In this work extraction of segmental and suprasegmental features is proposed which shows a significant improvement in the performance of verification. The size and shape assumed by ...


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Educational Resources on Mel frequency cepstral coefficient

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IEEE.tv Videos

IMS 2014:Active 600GHz Frequency Multiplier-by-Six S-MMICs for Submillimeter-Wave Generation
IMS 2011 Microapps - Local Fundamental Frequency Enhancements for X-Parameter Models
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IMS 2014: Super High Bit Rate Radio Access Technologies for Small Cells Using Higher Frequency Bands
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A Highly-Efficient 138?170GHz SiGe HBT Frequency Doubler for PowerConstrained Applications: RFIC Interactive Forum
An 8-10GHz Upconversion Mixer, with a Low-Frequency Calibration Loop Resulting in Better Than -73dBc In-Band Spurs: RFIC Interactive Forum
Co-design of Power Amplifier and Dynamic Power Supplies for Radar and Communications Transmitters
A Precision 140MHz Relaxation Oscillator in 40nm CMOS with 28ppm/C Frequency Stability for Automotive SoC Applications: RFIC Interactive Forum 2017
Ultrafast Photonics Time Frequency Signal Processing Using Integrated Photonics: An IPC Keynote with Andrew M. Weiner
IMS MicroApp: Advances in High Frequency Printed Circuit Board (PCB)
A 10-40GHz Frequency Quadrupler Source with Switchable Bandpass Filters and >30dBc Harmonic Rejection: RFIC Interactive Forum 2017
State-of-the art techniques for advanced vehicle dynamics control & vehicle state estimation
A 30-MHz-to-3-GHz CMOS Array Receiver with Frequency and Spatial Interference Filtering for Adaptive Antenna Systems: RFIC Industry Showcase
Wireless Power Charging of Plug-In Electric Vehicles
Radio Frequency Identification(RFID)
Micro-Apps 2013: Frequency Planning Synthesis for Wireless Systems Design
MicroApps: Different Methods for Capacitor Modelling in High-Frequency PCB-Based Diplexers (National Instruments)
MicroApps: Phase Noise, Allan Variance, and Frequency Reference (Agilent Technologies)

IEEE-USA E-Books

  • New time-frequency derived cepstral coefficients for automatic speech recognition

    The goal is to improve recognition rate by optimisation of Mel Frequency Cepstral Coefficients (MFCCs): modifications concern the time-frequency representation used to estimate these coefficients. There are many ways to obtain a spectrum out of a signal which differ in the method itself (Fourier, Wavelets,…), and in the normalisation. We show here that we can obtain noise resistant cepstral coefficients, for speaker independent connected word recognition. The recognition system is based on a continuous whole word hidden Markov model. An error reduction rate of approximately 50% is achieved. Moreover evaluation tests demonstrate that these results can be obtained with smaller databases: halving the training database have small effects on recognition rates (which is not the case with traditional MFCCs).

  • Representing speech

    The properties of the speech production process and the auditory periphery have led to the usage of similar speech signal representations for various processing tasks such as speech and speaker recognition, speech synthesis, and speech coding. The representation is generally divided into a description of the vocal-tract transfer function and the excitation source. For recognition purposes, the biased characterization of the vocal-tract transfer function by a time sequence of low-dimension cepstral vectors performs well. For coding and synthesis, we argue that for the vocal-tract transfer function autoregressive (AR) models are more effective than filter banks, while for the excitation source pitch-synchronous filter banks and modulation-domain filters are most effective. A clear trend exists towards the exploitation of the time variation of both the vocal-tract transfer function and the excitation source.

  • Template-based personalized singing voice synthesis

    In this paper, a template-based personalized singing voice synthesis method is proposed. It generates singing voices by means of conversion from the narrated lyrics of a song with the use of template recordings. The template voices are parallel speaking and singing voices recorded from professional singers, which are used to derive the transformation models for acoustic feature conversion. When converting a new instance of speech, its acoustic features are modified to approximate those of the actual singing voice based on the transformation models. Since the pitch contour of the synthesized singing is derived from an actual singing voice, it is more natural than modifying a step contour to implement pitch fluctuations such as overshoot and vibrato. It has been shown from the subjective tests that nearly natural singing quality with the preservation of the timbre can be achieved with the help of our method.

  • Audio source indexing by sub-band PCA with empirical mode decomposition

    This paper presents a sub-bund approach of audio source indexing technique without any prior information about the sources. The empirical mode decomposition (EMD) scheme, capable of decomposing nonlinear and non- stationary signal into some bases, is employed to implement the proposed sub- band method. The feature vectors are derived from each of the selected sub- bands of the signal block. Linear predictive cepstral coefficient (LPCC) is used as the principal feature of this indexing system. The dominant features are selected at each sub-band with principal component analysis (PCA). A dominancy dependent weighted function is introduced to measure the similarity between the source model and the derived feature vectors. The higher order statistics (HOS) is employed to compute the sub-band LPCC features. The use of HOS makes LPCC less affected by Gaussian type noises. The experimental results show that the sub-band technique produces better indexing efficiency than that of the full-band technique.

  • A confidence measure based — Score fusion technique to integrate MFCC and Pitch for speaker verification

    The objective of this paper is to evaluate the effectiveness of complementary speech features extracted from a speaker for verification. Traditionally, speaker verification systems use a single feature for representing speaker- specific information. In this work extraction of segmental and suprasegmental features is proposed which shows a significant improvement in the performance of verification. The size and shape assumed by the vocal tract while producing various sound units is generated by Mel Frequency Cepstral Coefficient (MFCC) which is a segmental feature. Pitch information contributes to the uniqueness of the speaker's voice at the suprasegmental feature which spans for a longer duration than the frames used for short term spectral analysis. The scores obtained using MFCC and Pitch based systems are fused using a confidence measure. Speaker Verification experiments were carried out on the CHAINS corpus database. The equal error rate (EER) obtained for the MFCC system is 12.8%. The MFCC system outperforms the system based on Pitch alone. The integration MFCC and Pitch for speaker verification using a confidence measure gives an EER of 11.2%.

  • Group delay features for speaker recognition

    Group delay is proposed as an effective means of representing spectral phase information as a feature in speaker recognition. Robustness of group delay features is difficult to achieve, since the spiky nature of the group delay masks the fine structure of the group delay. In this paper, two features based on group delay are proposed by reducing the effect of spikes with two different approaches. The first is log compression, to address the masking effects of the spikes, and the second is to use a sub-band based approach, where masking is restricted within certain bands containing the spikes. The purpose of this paper is to introduce different types of group delay feature extraction methods. The two features are evaluated on the cellular NIST 2001 database.

  • Discriminating semi-continuous HMM for speaker verification

    This paper describes the use of a multiple codebook SCHMM speaker verification system, which uses a novel technique for discriminative hidden Markov modelling known as discriminative observation probabilities (DOP). DOP can easily be added to a multiple codebook HMM system and require minimal additional computation and no additional training. The DOP technique can be applied to both speech and speaker recognition. Results are presented for text-dependent experiments on isolated digits from 27 true speakers and 84 casual imposters, recorded over the public telephone network in the United Kingdom. DOP are shown to significantly improve speaker verification performance for several commonly used parameter sets.<<ETX>>

  • Evalutation of Performance of KNN, MLP and RBF Classifiers in Emotion Detection Problem

    Emotion detection has gained increasing attention and become an active research area. The problem is solved with improved feature set with different number of feature groups, by employing different classifiers in order to achieve satisfactory recognition rate. In this study, speech related features are employed to evaluate the performance of different classifiers in emotion detection problem.

  • Exploration of Phase Information for Speech Emotion Classification

    This paper explores the significance of phase information for speech emotion classification. The phase information is extracted from the discrete Fourier transform (DFT) spectrum. The phase of the pitch harmonic is used as a proposed feature for speech emotion classification. Pitch frequency varies with emotions, and due to this pitch harmonic also varies with different emotions. It is expected that the phase of the pitch harmonic contains emotion information. Significance of the harmonic phase is carried out by evaluating the mean and variance values for speech emotion classification. Support Vector Machine (SVM) classifier is used to evaluate the performance of the proposed feature. The performance is evaluated using EMODB database. The performance of the proposed feature is compared with the the linear prediction coefficients (LPC), mel frequency cepstral coefficients (MFCC) and Teager energy operator (TEO) based non-linear critical band TEO autocorrelation envelope (TEO-CB- Auto-Env) features. An average recognition rate of 73.9% is achieved with the combination of the MFCC and proposed features.

  • Speech recognition using Support Vector Machines

    In this article we applied Support Vector Machines to acoustic model of Speech Recognition System based on MFCC and LPC features for Azerbaijani DataSet. This DataSet has been used for speech recognition by Multilayer Artificial Neural Network and achieved some results. The main goal of this work is applying SVM techniques to the Azerbaijan Speech Recognition System. The variety of results of SVM with different Kernel functions is analyzed in the training process. It is shown that SVM with radial basis and polynomial kernels give better recognition results that Multilayer Artificial Neural Network.



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