Academic literature on the topic 'Spectrogram'
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Journal articles on the topic "Spectrogram"
Lee, Sang-Hoon, Hyun-Wook Yoon, Hyeong-Rae Noh, Ji-Hoon Kim, and Seong-Whan Lee. "Multi-SpectroGAN: High-Diversity and High-Fidelity Spectrogram Generation with Adversarial Style Combination for Speech Synthesis." Proceedings of the AAAI Conference on Artificial Intelligence 35, no. 14 (May 18, 2021): 13198–206. http://dx.doi.org/10.1609/aaai.v35i14.17559.
Full textJohnson, Alexander. "An integrated approach for teaching speech spectrogram analysis to engineering students." Journal of the Acoustical Society of America 152, no. 3 (September 2022): 1962–69. http://dx.doi.org/10.1121/10.0014172.
Full textBasak, Gopal K., and Tridibesh Dutta. "Statistical Speaker Identification Based on Spectrogram Imaging." Calcutta Statistical Association Bulletin 59, no. 3-4 (September 2007): 253–63. http://dx.doi.org/10.1177/0008068320070309.
Full textHan, Ying, Qiao Wang, Jianping Huang, Jing Yuan, Zhong Li, Yali Wang, Haijun Liu, and Xuhui Shen. "Frequency Extraction of Global Constant Frequency Electromagnetic Disturbances from Electric Field VLF Data on CSES." Remote Sensing 15, no. 8 (April 13, 2023): 2057. http://dx.doi.org/10.3390/rs15082057.
Full textShingchern D. You, Kai-Rong Lin, and Chien-Hung Liu. "Estimating Classification Accuracy for Unlabeled Datasets Based on Block Scaling." International Journal of Engineering and Technology Innovation 13, no. 4 (September 28, 2023): 313–27. http://dx.doi.org/10.46604/ijeti.2023.11975.
Full textLi, Hong Ping, and Hong Li. "Establish an Artificial Neural Networks Model to Make Quantitative Analysis about the Capillary Electrophoresis Spectrum." Advanced Materials Research 452-453 (January 2012): 1116–20. http://dx.doi.org/10.4028/www.scientific.net/amr.452-453.1116.
Full textLi, Juan, Xueying Zhang, Lixia Huang, Fenglian Li, Shufei Duan, and Ying Sun. "Speech Emotion Recognition Using a Dual-Channel Complementary Spectrogram and the CNN-SSAE Neutral Network." Applied Sciences 12, no. 19 (September 22, 2022): 9518. http://dx.doi.org/10.3390/app12199518.
Full textPethiyagoda, Ravindra, Scott W. McCue, and Timothy J. Moroney. "Spectrograms of ship wakes: identifying linear and nonlinear wave signals." Journal of Fluid Mechanics 811 (December 6, 2016): 189–209. http://dx.doi.org/10.1017/jfm.2016.753.
Full textGodbole, Shubham, Vaishnavi Jadhav, and Gajanan Birajdar. "Indian Language Identification using Deep Learning." ITM Web of Conferences 32 (2020): 01010. http://dx.doi.org/10.1051/itmconf/20203201010.
Full textSamad, Salina Abdul, and Aqilah Baseri Huddin. "Improving spectrogram correlation filters with time-frequency reassignment for bio-acoustic signal classification." Indonesian Journal of Electrical Engineering and Computer Science 14, no. 1 (April 1, 2019): 59. http://dx.doi.org/10.11591/ijeecs.v14.i1.pp59-64.
Full textDissertations / Theses on the topic "Spectrogram"
Lampert, Thomas. "Spectrogram track detection : an active contour algorithm." Thesis, University of York, 2010. http://etheses.whiterose.ac.uk/956/.
Full textBehr, Michael K. "State-space multitaper spectrogram algorithms : theory and applications." Thesis, Massachusetts Institute of Technology, 2016. http://hdl.handle.net/1721.1/107033.
Full textThis electronic version was submitted by the student author. The certified thesis is available in the Institute Archives and Special Collections.
Cataloged from student-submitted PDF version of thesis.
Includes bibliographical references (pages 63-67).
I present the state-space multitaper approach for analyzing non-stationary time series. Nonstationary time series are commonly divided into small time windows for analysis, but existing methods lose predictive power by analyzing each window independently, even though nearby windows have similar spectral properties. The state-space multitaper algorithm combines two approaches for spectral analysis: the state-space approach models the relations between nearby windows, and the multitaper approach balances a bias-variance tradeoff inherent in Fourier analysis of finite interval data. I illustrate an application of the algorithm to real-time anesthesia monitoring, which could prevent traumatic cases of intraoperative awareness. I discuss issues including a real-time implementation and modeling the system's noise parameters. I identify the new problem of phase censorship, by which spectral leakage hides some information necessary to relate signal phases across windows in time.
by Michael K. Behr.
M. Eng.
Hansen, Vedal Amund. "Unsupervised Audio Spectrogram Compression using Vector Quantized Autoencoders." Thesis, KTH, Skolan för elektroteknik och datavetenskap (EECS), 2019. http://urn.kb.se/resolve?urn=urn:nbn:se:kth:diva-264947.
Full textTrots de senaste framgångarna för neurala nätverk på en rad olika områden är musikalisk ljudmodellering fortfarande en svår uppgift, med karakteristiska egenskaper som spänner över tiotusentals dimensioner i inputrymnden. Genom att formulera ljuddatakomprimering som en oövervakad inlärningsuppgift undersöker detta projekt användbarheten av vektorkvantiserade neurala nätverkbaserade självkodare på spektrogram – en bildliknande representation av ljud. Med en nyligen beskriven gradientbaserad metod för approximering av vågformer från rekonstruerade (realvärda) spektrogram, producerar den diskreta pipelinen lyssningsbara rekonstruktioner med överraskande ljudåtergivning jämfört med okomprimerade versioner, även för exempel utanför domänen. Resultaten tyder på att den lärda diskreta kvantiseringsmetoden uppnår ungefär nio gånger hårdare spektrogramkompression jämfört med sin kontinuerliga motsvarighet, samtidigt som den skapar liknande rekonstruktioner, både kvalitativt och enligt kvantitativa felmått.
Kotte, Timo Oliver. "Application of Image Processing Techniques for Lamb Wave Characterization." Thesis, Georgia Institute of Technology, 2004. http://hdl.handle.net/1853/4787.
Full textLamel, Lori Faith. "Formalizing knowledge used in spectrogram reading : acoustic and perceptual evidence from stops." Thesis, Massachusetts Institute of Technology, 1988. http://hdl.handle.net/1721.1/14780.
Full textBleakley, Steven Shea, and steven bleakley@qr com au. "Time Frequency Analysis of Railway Wagon Body Accelerations for a Low-Power Autonomous Device." Central Queensland University, 2006. http://library-resources.cqu.edu.au./thesis/adt-QCQU/public/adt-QCQU20070622.121515.
Full textTsiappoutas, Kyriakos Michael. "Byzantine Music Intervals: An Experimental Signal Processing Approach." ScholarWorks@UNO, 2004. http://scholarworks.uno.edu/td/470.
Full textDias, Fábio Felix. "Uma estratégia para análise visual de Paisagens Acústicas com base em seleção de características discriminantes." Universidade de São Paulo, 2018. http://www.teses.usp.br/teses/disponiveis/55/55134/tde-29102018-172305/.
Full textThe growth of data volume caused by current technological development has been strongly evoked as a premise for use of techniques that help exploration, analysis, and understanding of data. A subset of these techniques is yielded by the field of Data Visualization, which provides visual manners to identify patterns and trends, as well as the extraction of hidden data features. Such approaches can be applied to problems that aim at data analysis with a strong exploratory component. One such problem is the use of sound as a tool to describe environmental landscapes, named ecological Soundscapes. A visual approach to analysis Soundscapes is presented in this master research. The approach contains two steps, and the first step applies visual (tSNE Multidimensional Projection) and numeric (Silhouette Coefficient) techniques to evaluate attributes groups that better describe a specific Soundscape. The second step employs visual techniques to analysis global differences and specific features of the terrestrial and underwater environment. To achieve these goals, the research used Heatmap, Parallel Coordinates, and xHiPP, an extension of HiPP projection. The xHiPP enhanced HiPP to improve its analytical capabilities and flexibility. The presented steps were able to show evidence of the Mel-frequency Cepstrum Coefficients is an effective attribute collection to represent and segregate Soundscapes. As well, visual techniques employed in the analysis are capable to highlight similar audio features, making exploration easy, allowing users to focus relevant environmental attributes, instead of analyzing individual audios to extraction some information.
Kalm, Helen. "Acoustic Soil-Rock Probing : A Case Study in Gubbängen." Thesis, KTH, Jord- och bergmekanik, 2019. http://urn.kb.se/resolve?urn=urn:nbn:se:kth:diva-256081.
Full textLacko, Tomáš. "Akustická simulace jedoucího automobilu." Master's thesis, Vysoké učení technické v Brně. Fakulta elektrotechniky a komunikačních technologií, 2011. http://www.nusl.cz/ntk/nusl-218916.
Full textBooks on the topic "Spectrogram"
Martin, Ann. VOICE - a spectrogram computer display package. Woods Hole, Mass: Woods Hole Oceanographic Institution, 1990.
Find full textElliott, K. H. Spectrograph user guide. Birmingham: School of Physics and Space Research, University of Birmingham, 1992.
Find full textRobinson, R. D. The RGO spectrograph. 2nd ed. Epping, N.S.W: Anglo-Australian Observatory, 1985.
Find full textD, Tsintikidis, and United States. National Aeronautics and Space Administration., eds. New voyager radio spectrograms of Uranus. Iowa City, IA: Dept. of Physics and Astronomy, University of Iowa, 1990.
Find full textBecher, Jacob. The simulated space proton environment for radiation effects on Space Telescope Imaging Spectrograph (STIS). Norfolk, Va: Old Dominion University Research Foundation, 1992.
Find full textH, Moseley S., and United States. National Aeronautics and Space Administration, eds. The Submillimeter And Far Infrared Experiment (SAFIRE): A PI class instrument for SOFIA. [Washington, D.C.?]: NASA, 1999.
Find full textUnited States. National Aeronautics and Space Administration., ed. Aries X-ray objective grating spectrograph: Final report. Palo Alto, CA: Lockheed Palo Alto Research Laboratory, 1991.
Find full textUnited States. National Aeronautics and Space Administration., ed. Aries X-ray objective grating spectrograph: Final report. Palo Alto, CA: Lockheed Palo Alto Research Laboratory, 1991.
Find full textUnited States. National Aeronautics and Space Administration., ed. Aries X-ray objective grating spectrograph: Final report. Palo Alto, CA: Lockheed Palo Alto Research Laboratory, 1991.
Find full textUnited States. National Aeronautics and Space Administration., ed. Goddard high resolution spectrograph instrument handbook. 2nd ed. [Baltimore, Md.]: Space Telescope Science Institute, 1990.
Find full textBook chapters on the topic "Spectrogram"
Kobrina, Anastasiya. "Sound Spectrogram." In Encyclopedia of Animal Cognition and Behavior, 1–5. Cham: Springer International Publishing, 2018. http://dx.doi.org/10.1007/978-3-319-47829-6_613-1.
Full textKobrina, Anastasiya. "Sound Spectrogram." In Encyclopedia of Animal Cognition and Behavior, 6585–89. Cham: Springer International Publishing, 2022. http://dx.doi.org/10.1007/978-3-319-55065-7_613.
Full textFulop, Sean A. "The Reassigned Spectrogram." In Signals and Communication Technology, 127–65. Berlin, Heidelberg: Springer Berlin Heidelberg, 2011. http://dx.doi.org/10.1007/978-3-642-17478-0_6.
Full textRiley, Michael D. "The Schematic Spectrogram." In The Kluwer International Series in Engineering and Computer Science, 87–119. Boston, MA: Springer US, 1989. http://dx.doi.org/10.1007/978-1-4613-1079-2_4.
Full textMontalvo, Ana, Yandre M. G. Costa, and José Ramón Calvo. "Language Identification Using Spectrogram Texture." In Progress in Pattern Recognition, Image Analysis, Computer Vision, and Applications, 543–50. Cham: Springer International Publishing, 2015. http://dx.doi.org/10.1007/978-3-319-25751-8_65.
Full textLorenzo, Javier, and Mario Hernández. "Habituation Based on Spectrogram Analysis." In Advances in Artificial Intelligence — IBERAMIA 2002, 893–902. Berlin, Heidelberg: Springer Berlin Heidelberg, 2002. http://dx.doi.org/10.1007/3-540-36131-6_91.
Full textSawada, Shun, Yoshinari Takegawa, and Keiji Hirata. "On Hierarchical Clustering of Spectrogram." In Music Technology with Swing, 226–37. Cham: Springer International Publishing, 2018. http://dx.doi.org/10.1007/978-3-030-01692-0_16.
Full textFulop, Sean A. "The Fourier Power Spectrum and Spectrogram." In Signals and Communication Technology, 69–106. Berlin, Heidelberg: Springer Berlin Heidelberg, 2011. http://dx.doi.org/10.1007/978-3-642-17478-0_4.
Full textLampert, Thomas A., Simon E. M. O’Keefe, and Nick E. Pears. "Line Detection Methods for Spectrogram Images." In Advances in Intelligent and Soft Computing, 127–34. Berlin, Heidelberg: Springer Berlin Heidelberg, 2009. http://dx.doi.org/10.1007/978-3-540-93905-4_16.
Full textMagazine, Raghav, Ayush Agarwal, Anand Hedge, and S. R. Mahadeva Prasanna. "Fake Speech Detection Using Modulation Spectrogram." In Speech and Computer, 451–63. Cham: Springer International Publishing, 2022. http://dx.doi.org/10.1007/978-3-031-20980-2_39.
Full textConference papers on the topic "Spectrogram"
Arabshahi, Payman, Robert J. Marks, and Les E. Atlas. "Fully parallel, real-time optical architectures for superior time–frequency representations of signals." In OSA Annual Meeting. Washington, D.C.: Optica Publishing Group, 1990. http://dx.doi.org/10.1364/oam.1990.thk7.
Full textReyes-Gomez, Manuel J., Nebojsa Jojic, and Daniel P. W. Ellis. "Modelling Sound Dynamics Using Deformable Spectrograms: Segmenting the Spectrogram into Smooth Regions." In 2006 Fortieth Asilomar Conference on Signals, Systems and Computers. IEEE, 2006. http://dx.doi.org/10.1109/acssc.2006.356581.
Full textEdwards, Matthew E. "Computer-Replicated Spectrograms By Ensemble Averaging and Normalization." In Laser Applications to Chemical Analysis. Washington, D.C.: Optica Publishing Group, 1992. http://dx.doi.org/10.1364/laca.1992.pd12.
Full textFlandrin, Patrick. "On spectrogram local maxima." In 2017 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP). IEEE, 2017. http://dx.doi.org/10.1109/icassp.2017.7952903.
Full textBeauregard, Gerald T., Mithila Harish, and Lonce Wyse. "Single Pass Spectrogram Inversion." In 2015 IEEE International Conference on Digital Signal Processing (DSP). IEEE, 2015. http://dx.doi.org/10.1109/icdsp.2015.7251907.
Full textGong, Yuan, Yu-An Chung, and James Glass. "AST: Audio Spectrogram Transformer." In Interspeech 2021. ISCA: ISCA, 2021. http://dx.doi.org/10.21437/interspeech.2021-698.
Full textDoura, Tomoki, and Toshihiko Shiraishi. "Sound Source Separation Using Spectrogram Analysis by Neural Networks." In ASME 2017 International Mechanical Engineering Congress and Exposition. American Society of Mechanical Engineers, 2017. http://dx.doi.org/10.1115/imece2017-71583.
Full textFlamant, Julien, Pierre Chainais, and Nicolas Le Bihan. "Polarization spectrogram of bivariate signals." In 2017 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP). IEEE, 2017. http://dx.doi.org/10.1109/icassp.2017.7952905.
Full textZawawi, T. N. S. T., A. R. Abdullah, E. F. Shair, I. Halim, and O. Rawaida. "Electromyography signal analysis using spectrogram." In 2013 IEEE Student Conference on Research and Development (SCOReD). IEEE, 2013. http://dx.doi.org/10.1109/scored.2013.7002599.
Full textDe Luca, A., M. Contu, S. Hristov, L. Daniel, M. Gashinova, and M. Cherniakov. "FSR velocity estimation using spectrogram." In 2016 17th International Radar Symposium (IRS). IEEE, 2016. http://dx.doi.org/10.1109/irs.2016.7497338.
Full textReports on the topic "Spectrogram"
Joggerst, Candace Church. PDV spectrogram automated extractions. Office of Scientific and Technical Information (OSTI), September 2019. http://dx.doi.org/10.2172/1561071.
Full textSkurikhin, Alexei N., and Richard J. Stead. Seismic Spectrogram Recognition by Matching the Energy Distributions. Office of Scientific and Technical Information (OSTI), November 2016. http://dx.doi.org/10.2172/1331246.
Full textLamei, Lori F. Formalizing Knowledge Used in Spectrogram Reading: Acoustic and Perceptual Evidence from Stops. Fort Belvoir, VA: Defense Technical Information Center, December 1988. http://dx.doi.org/10.21236/ada206826.
Full textSylvia, J. M., J. W. Haas, K. M. Spencer, M. M. Carrabba, R. D. Rauh, R. W. Forney, and T. M. Johnston. Field Raman Spectrograph for Environmental Analysis. Office of Scientific and Technical Information (OSTI), July 1998. http://dx.doi.org/10.2172/3969.
Full textRehm, K. E., and C. Bolduc. Upgrade of the area II spectrograph. Office of Scientific and Technical Information (OSTI), August 1995. http://dx.doi.org/10.2172/166380.
Full textBrake, M. L. Vacuum Spectrograph for E-Beam Ablation Studies. Fort Belvoir, VA: Defense Technical Information Center, July 1987. http://dx.doi.org/10.21236/ada190531.
Full textAldering, Greg. Comparison of STIS and SNAP spectrograph throughputs. Office of Scientific and Technical Information (OSTI), June 2002. http://dx.doi.org/10.2172/842491.
Full textH. FUNSTEN. IMAGING TIME-OF-FLIGHT ION MASS SPECTROGRAPH. Office of Scientific and Technical Information (OSTI), November 2000. http://dx.doi.org/10.2172/768176.
Full textStratton, B. C., R. J. Fonck, K. Ida, K. P. Jaehnig, and A. T. Ramsey. SPRED spectrograph upgrade: high resolution grating and improved absolute calibrations. Office of Scientific and Technical Information (OSTI), May 1986. http://dx.doi.org/10.2172/5628855.
Full textCarrabba, M. M. Fiber optic Raman spectrograph for in situ environmental monitoring. Final report. Office of Scientific and Technical Information (OSTI), November 1992. http://dx.doi.org/10.2172/10179341.
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