Conferences related to Speech Recognition

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2018 26th Signal Processing and Communications Applications Conference (SIU)

The general scope of the conference ranges from signal and image processing to telecommunication, and applications of signal processing methods in biomedical and communication problems.

  • 2017 25th Signal Processing and Communications Applications Conference (SIU)

    Signal Processing and Communication Applications (SIU) conference is the most prominent scientific meeting on signal processing in Turkey bringing together researchers working in signal processing and communication fields. Topics include but are not limited to the areas of research listed in the keywords.

  • 2016 24th Signal Processing and Communication Application Conference (SIU)

    Signal Processing Theory, Statistical Signal Processing, Nonlinear Signal Processing, Adaptive Signal Processing, Array and Multichannel Signal Processing, Signal Processing for Sensor Networks, Time-Frequency Analysis, Speech / Voice Processing and Recognition, Computer Vision, Pattern Recognition, Machine Learning for Signal Processing, Human-Machine Interaction, Brain-Computer Interaction, Signal-Image Acquisition and Generation, image Processing, video Processing, Image Printing and Presentation, Image / Video / Audio browsing and retrieval, Image / Video / Audio Watermarking, Multimedia Signal Processing, Biomedical Signal Processing and Image Processing, Bioinformatics, Biometric Signal-Image Processing and Recognition, Signal Processing for Security and Defense, Signal and Image Processing for Remote Sensing, Signal Processing Hardware, Signal Processing Education, Radar Signal Processing, Communication Theory, Communication Networks, Wireless Communications

  • 2015 23th Signal Processing and Communications Applications Conference (SIU)

    Signal Processing Theory Statistical Signal Processing Nonlinear Signal Processing Adaptive Signal Processing Array and Multichannel Signal Processing Signal Processing for Sensor Networks Time-Frequency Analysis Speech / Voice Processing and Recognition Computer Vision Pattern Recognition Machine Learning for Signal Processing Human-Machine Interaction Brain-Computer Interaction Signal-Image Acquisition and Generation image Processing video Processing Image Printing and Presentation Image / Video / Audio browsing and retrieval Image / Video / Audio Watermarking Multimedia Signal Processing Biomedical Signal Processing and Image Processing Bioinformatics Biometric Signal-Image Processing and Recognition Signal Processing for Security and Defense Signal and Image Processing for Remote Sensing Signal Processing Hardware Signal Processing Education Radar Signal Processing Communication Theory Communication Networks Wireless Communications

  • 2014 22nd Signal Processing and Communications Applications Conference (SIU)

    SIU will be held in Trabzon, Turkey at the Karadeniz Technical University Convention and Exhibition Centre on April 23, 2014. SIU is the largest and most comprehensive technical conference focused on signal processing and its applications in Turkey. Last year there were 500 hundred participants. The conference will feature renowned speakers, tutorials, and thematic workshops. Topics include but are not limited to: Signal Procesing, Image Processing, Communication, Computer Vision, Machine Learning, Biomedical Signal Processing,

  • 2013 21st Signal Processing and Communications Applications Conference (SIU)

    Conference will discuss state of the art solutions and research results on existing and future DSP and telecommunication systems, applications, and related standardization activities. Conference will also include invited lectures, tutorials and special sessions.

  • 2012 20th Signal Processing and Communications Applications Conference (SIU)

    Conference will discuss state of the art solutions and research results on existing and future DSP and telecommunication systems, applications, and related standardization activities. Conference will also include invited lectures, tutorials and special sessions.

  • 2011 19th Signal Processing and Communications Applications Conference (SIU)

    Conference will bring together academia and industry professionals as well as students and researchers to present and discuss state of the art solutions and research results on existing and future DSP and telecommunication systems, applications, and related standardization activities. The Conference will also include invited lectures, tutorials and special sessions.

  • 2010 IEEE 18th Signal Processing and Communications Applications Conference (SIU)

    S1.Theory of Signal-Processing S2.Statistical Signal-Processing S3.Multimedia Signal-Processing S4.Biomedical Signal-Processing S5.Sensor Networks S6.Multirate Signal-Processing S7.Pattern Recognition S8.Computer Vision S9.Adaptive Filters S10.Image/Video/Speech Browsing, Retrieval S11.Speech/Audio Coding S12.Speech Processing S13.Human-Machine Interfaces S14.Surveillance Signal Processing S15.Bioinformatics S16.Self-Learning S17.Signal-Processing Education S18.Signal-Processing Systems S1

  • 2009 IEEE 17th Signal Processing and Communications Applications Conference (SIU)

    The scope of the conference is to cover recent topics in theory and applications of Signal Processing and Communications.

  • 2008 IEEE 16th Signal Processing and Communications Applications Conference (SIU)

    Signal Processing, Image Processing, Speech Processing, Pattern Recognition, Human Computer Interaction, Communication, Video and Speech indexing, Computer Vision, Biomedical Signal Processing

  • 2007 IEEE 15th Signal Processing and Communications Applications (SIU)

  • 2006 IEEE 14th Signal Processing and Communications Applications (SIU)

  • 2005 IEEE 13th Signal Processing and Communications Applications (SIU)

  • 2004 IEEE 12th Signal Processing and Communications Applications (SIU)


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


2018 IEEE International Conference on Multimedia and Expo (ICME)

The IEEE International Conference on Multimedia & Expo (ICME) has been the flagship multimedia conference sponsored by four IEEE societies since 2000. It serves as a forum to promote the exchange of the latest advances in multimedia technologies, systems, and applications from both the research and development perspectives of the circuits and systems, communications, computer, and signal processing communities. ICME also features an Exposition of multimedia products and prototypes.


2018 IEEE Seventh International Conference on Communications and Electronics (ICCE)

communications and electronics

  • 2016 IEEE Sixth International Conference on Communications and Electronics (ICCE)

    Contributed papers are solicited describing original works in electronics, communications engineering and related technologies. Topics and technical areas of interest include but are not limited to the following: 1. Communications Networks and Systems; 2. Signal Processing and Applications; 3. Microwave Engineering; 4. Electronics Systems. In addition, three special sessions are included in the scope of ICCE2016: 1. Software Defined Networking 2.Underwater Acoustic Communication3.Crowdsourcing and Crowdsourcing Application

  • 2014 IEEE Fifth International Conference on Communications and Electronics (ICCE)

    Contributed papers are solicited describing original works in electronics, communications engineering and related technologies. Topics and technical areas of interest include but are not limited to the following: Communications Networks & Systems; Signal Processing and Applications; Microwave Engineering; Electronics Systems; with 3 special sessions on: Software Defined Networking; Underwater Acoustic Communications; Crowdsourcing.

  • 2012 Fourth International Conference on Communications and Electronics (ICCE)

    ICCE 2012 looks for significant contributions to various topics in communication engineering, networking, microwave engineering, signal processing and electronics engineering. The conference will also include tutorials, workshops, and technology panels given by world-class speakers.

  • 2010 Third International Conference on Communications and Electronics (ICCE)

    ICCE 2010 will focus on cutting edge research, development, and applications of communications and electronics technologies, and aims at continuing and accelerating the momentum of researching in electronics and telecommunications areas. ICCE 2010 will also provide the best and most current tutorials, research results, industry-oriented technical contents, thereby facilitating scientific idea exchange and the identification and definition of future trends and directions on these fields.

  • 2008 Second International Conference on Communications and Electronics (ICCE)

    The Second International Conference on Communications and Electronics (ICCE 2008) is devoted to the research, development, and application of communications and electronics technologies, and aims at continuing and accelerating the momentum of researching in telecommunication areas.

  • 2006 First International Conference on Communications and Electronics (ICCE)


2018 International Symposium on Consumer Technologies (ISCT)

IEEE ISCT International Symposium on Consumer Technologies (former International Symposium on Consumer Electronics) is the established forum for innovative research in all technology areas of consumer electronics. The theme of ISCT 2018 is “Consumer Technologies in 10 years”.Paper contributions are sought in but are not limited to following areas:Internet of Things and Internet of Everywhere (IoT)Consumer Healthcare Systems (CHS)Energy Management of CE Hardware and Software Systems (EMC)Application-Specific CE for Smart Cities (SMC)Artificial Intelligence in Consumer Technologies (AIC)Consumer Technologies Quality and Testing (CTQ)Telecom, RF, Wireless, and Network Technologies (WNT)AV Systems, Image and Video, and Cameras and Acquisition (AVS)CE Sensors and MEMS (CSM)Smartphone and Mobile Device Technologies (MDT)Entertainment, Gaming, and Virtual and Augmented Reality (EGV)Other Technologies Related with CE (MIS)Education in Consumer Technologies Area (EDU)


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Periodicals related to Speech Recognition

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Aerospace and Electronic Systems Magazine, IEEE

The IEEE Aerospace and Electronic Systems Magazine publishes articles concerned with the various aspects of systems for space, air, ocean, or ground environments.


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.


Consumer Electronics, IEEE Transactions on

The design and manufacture of consumer electronics products, components, and related activities, particularly those used for entertainment, leisure, and educational purposes


Neural Networks, IEEE Transactions on

Devoted to the science and technology of neural networks, which disclose significant technical knowledge, exploratory developments, and applications of neural networks from biology to software to hardware. Emphasis is on artificial neural networks.


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Most published Xplore authors for Speech Recognition

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Xplore Articles related to Speech Recognition

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Evolution-Strategy-Based Automation of System Development for High-Performance Speech Recognition

[{u'author_order': 1, u'affiliation': u'Tokyo Institute of Technology, Yokohama, Japan', u'full_name': u'Takafumi Moriya'}, {u'author_order': 2, u'affiliation': u'Tokyo Institute of Technology, Yokohama, Japan', u'full_name': u'Tomohiro Tanaka'}, {u'author_order': 3, u'affiliation': u'Tokyo Institute of Technology, Yokohama, Japan', u'full_name': u'Takahiro Shinozaki'}, {u'author_order': 4, u'affiliation': u'Johns Hopkins University, Baltimore, USA', u'full_name': u'Shinji Watanabe'}, {u'author_order': 5, u'affiliation': u'Johns Hopkins University, Baltimore, USA', u'full_name': u'Kevin Duh'}] IEEE/ACM Transactions on Audio, Speech, and Language Processing, 2019

The state-of-the-art large vocabulary speech recognition systems consist of several components including hidden Markov model and deep neural network. To realize the highest recognition performance, numerous meta-parameters specifying the designs and training setups of these components must be optimized. A prominent obstacle in system development is the laborious effort required by human experts in tuning these meta-parameters. To automate the ...


A Biologically Plausible Speech Recognition Framework Based on Spiking Neural Networks

[{u'author_order': 1, u'affiliation': u'Department of Electrical and Computer Engineering, National University of Singapore', u'full_name': u'Jibin Wu'}, {u'author_order': 2, u'affiliation': u'Institute for Infocomm Research, A*STAR, Singapore', u'full_name': u'Yansong Chua'}, {u'author_order': 3, u'affiliation': u'Department of Electrical and Computer Engineering, National University of Singapore', u'full_name': u'Haizhou Li'}] 2018 International Joint Conference on Neural Networks (IJCNN), None

Humans perform remarkably well for speech recognition using sparse and asynchronous events carried by electrical impulses. Motivated by the observations that human brains primarily learn features from environmental stimuli in an unsupervised manner and consume extremely low power for complex cognitive tasks, we propose a biologically plausible speech recognition mechanism using unsupervised self-organizing map (SOM) for feature representation and event-driven ...


Syllable-Based Acoustic Modeling with CTC for Multi-Scenarios Mandarin speech recognition

[{u'author_order': 1, u'affiliation': u'Institute of Automation, Chinese Academy of Sciences, Beijing, P.R.China', u'full_name': u'Yuanyuan Zhao'}, {u'author_order': 2, u'affiliation': u'Institute of Automation, Chinese Academy of Sciences, Beijing, P.R.China', u'full_name': u'Linhao Dong'}, {u'author_order': 3, u'affiliation': u'Institute of Automation, Chinese Academy of Sciences, Beijing, P.R.China', u'full_name': u'Shuang Xu'}, {u'author_order': 4, u'affiliation': u'Institute of Automation, Chinese Academy of Sciences, Beijing, P.R.China', u'full_name': u'Bo Xu'}] 2018 International Joint Conference on Neural Networks (IJCNN), None

With the improvement of speech recognition, voice products are gradually applied to every scene of life. The existing approaches to handle various scenarios are often to build many different acoustic models using scenario- dependent data only, with each for a special scene. The obvious weakness of these approaches is that it seriously hampers the large-scale application and maintenance of voice ...


Deep Spiking Neural Network model for time-variant signals classification: a real-time speech recognition approach

[{u'author_order': 1, u'affiliation': u'Robotics and Computer Technology Lab., University of Seville, Seville, Spain', u'full_name': u'Juan P. Dominguez-Morales'}, {u'author_order': 2, u'affiliation': u'Advanced Processor Technologies Group, School of Computer Science., University of Manchester., Manchester, UK', u'full_name': u'Qian Liu'}, {u'author_order': 3, u'affiliation': u'Advanced Processor Technologies Group, School of Computer Science., University of Manchester., Manchester, UK', u'full_name': u'Robert James'}, {u'author_order': 4, u'affiliation': u'Robotics and Computer Technology Lab., University of Seville, Seville, Spain', u'full_name': u'Daniel Gutierrez-Galan'}, {u'author_order': 5, u'affiliation': u'Robotics and Computer Technology Lab., University of Seville, Seville, Spain', u'full_name': u'Angel Jimenez-Fernandez'}, {u'author_order': 6, u'affiliation': u'Advanced Processor Technologies Group, School of Computer Science., University of Manchester., Manchester, UK', u'full_name': u'Simon Davidson'}, {u'author_order': 7, u'affiliation': u'Advanced Processor Technologies Group, School of Computer Science., University of Manchester., Manchester, UK', u'full_name': u'Steve Furber'}] 2018 International Joint Conference on Neural Networks (IJCNN), None

Speech recognition has become an important task to improve the human-machine interface. Taking into account the limitations of current automatic speech recognition systems, like non-real time cloud-based solutions or power demand, recent interest for neural networks and bio-inspired systems has motivated the implementation of new techniques. Among them, a combination of spiking neural networks and neuromorphic auditory sensors offer an ...


Correntropy Based Hierarchical Linear Dynamical System For Speech Recognition

[{u'author_order': 1, u'affiliation': u'Department of Electrical and Computer Engineering, University of Florida, Gainesville, United States', u'full_name': u'Rishabh Singh'}, {u'author_order': 2, u'affiliation': u'Department of Electrical and Computer Engineering, University of Florida, Gainesville, United States', u'full_name': u'Jose C. Principe'}] 2018 International Joint Conference on Neural Networks (IJCNN), None

Hierarchical Linear Dynamical System (HLDS) is a recently introduced Kalman filter based generative state model that extracts relevant self-segmenting information from input time series signal by hierarchically constraining the information representing subspaces of its states thus slowing down the dynamics of the input signal. Despite the simplicity of its nested architecture and its dependance on linear Kalman update rules, the ...


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Educational Resources on Speech Recognition

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eLearning

No eLearning Articles are currently tagged "Speech Recognition"

IEEE-USA E-Books

  • Application of Hidden Markov Models in Speech Recognition

    Hidden Markov Models (HMMs) provide a simple and effective framework for modelling time-varying spectral vector sequences. As a consequence, almost all present day large vocabulary continuous speech recognition (LVCSR) systems are based on HMMs. Whereas the basic principles underlying HMM-based LVCSR are rather straightforward, the approximations and simplifying assumptions involved in a direct implementation of these principles would result in a system which has poor accuracy and unacceptable sensitivity to changes in operating environment. Thus, the practical application of HMMs in modern systems involves considerable sophistication. The Application of Hidden Markov Models in Speech Recognition presents the core architecture of a HMM-based LVCSR system and proceeds to describe the various refinements which are needed to achieve state-of-the-art performance. These refinements include feature projection, improved covariance modelling, discriminative parameter estimation, adaptation an normalisation, noise compensation and multi-pass system combination. It concludes with a case study of LVCSR for Broadcast News and Conversation transcription in order to illustrate the techniques described. The Application of Hidden Markov Models in Speech Recognition is an invaluable resource for anybody with an interest in speech recognition technology.

  • The Basics of Automatic Speech Recognition

    This chapter contains sections titled: Introduction Speech Recognition Viewed as Bayes Classification Hidden Markov Models HMM‐Based Speech Recognition References

  • Embedded Automatic Speech Recognition and Text‐To‐Speech Synthesis

    This chapter contains sections titled: Automatic speech recognition Mathematical formulation Acoustic parameterization Acoustic modeling Language modeling Modifications for embedded speech recognition Applications Text‐to‐speech synthesis Text to speech in a nutshell Front end Back end Embedded text‐to‐speech Evaluation Summary Bibliography

  • Reverberant Speech Recognition

    This chapter contains sections titled: Introduction The Effect of Reverberation Approaches to Reverberant Speech Recognition Feature Domain Model of the Acoustic Impulse Response Bayesian Feature Enhancement Experimental Results Conclusions Acknowledgment References

  • Acoustic Model Training for Robust Speech Recognition

    This chapter contains sections titled: Introduction Traditional Training Methods for Robust Speech Recognition A Brief Overview of Speaker Adaptive Training Feature‐Space Noise Adaptive Training Model‐Space Noise Adaptive Training Noise Adaptive Training using VTS Adaptation Discussion Conclusion References

  • Brief History of Automatic Speech Recognition

    This chapter contains sections titled: Radio Rex Digit Recognition Speech Recognition in the 1950s The 1960s 1971-1976 ARPA Project Achieved by 1976 The 1980s in Automatic Speech Recognition More Recent Work Some Lessons Exercises

  • Factorial Models for Noise Robust Speech Recognition

    This chapter contains sections titled: Introduction The Model‐Based Approach Signal Feature Domains Interaction Models Inference Methods Efficient Likelihood Evaluation in Factorial Models Current Directions References

  • Distributed Speech Recognition

    This chapter contains sections titled: Elements of distributed speech processing Front‐end processing ETSI standards Transfer protocol Energy‐aware distributed speech recognition ESR, NSR, DSR Bibliography

  • Computational Auditory Scene Analysis and Automatic Speech Recognition

    This chapter contains sections titled: Introduction Auditory Scene Analysis Computational Auditory Scene Analysis CASA Strategies Integrating CASA with ASR Concluding Remarks Acknowledgment References

  • The Problem of Robustness in Automatic Speech Recognition

    This chapter contains sections titled: Errors in Bayes Classification Bayes Classification and ASR External Influences on Speech Recordings The Effect of External Influences on Recognition Improving Recognition under Adverse Conditions References



Standards related to Speech Recognition

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Jobs related to Speech Recognition

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