Relevant bibliographies by topics / Acoustic identification

Contents

  1. Journal articles
  2. Dissertations / Theses
  3. Books
  4. Book chapters
  5. Conference papers
  6. Reports

Academic literature on the topic 'Acoustic identification'

Author: Grafiati
Published: 4 June 2021
Last updated: 25 July 2025

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Journal articles on the topic "Acoustic identification"

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Wróbel, Jakub, and Damian Pietrusiak. "Noise Source Identification in Training Facilities and Gyms." Applied Sciences 12, no. 1 (2021): 54. http://dx.doi.org/10.3390/app12010054.

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This paper deals with noise problems in industrial sites adapted for commercial training venues. The room acoustics of such an object were analyzed in the scope of the reverberation time and potential acoustic adaptation measures are indicated. Identification and classification of noise sources in training facilities and gyms was carried out based on the acoustic measurements. The influence of rubber padding on impact and noise reduction was investigated in the case of chosen noise-intensive exercise activities performed in a previously described acoustic environment. Potential noise reduction
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Shen, Lue, Yuxuan Wang, Patrick Wong, and Tyler K. Perrachione. "Acoustic divergence from the training sample determines talker identification accuracy for emotional voices." Journal of the Acoustical Society of America 155, no. 3_Supplement (2024): A264. http://dx.doi.org/10.1121/10.0027444.

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Different emotional states introduce substantial acoustic variations in talkers’ voices. It remains unclear how within-talker variability across emotional states affects listeners' ability to maintain perceptual constancy during talker identification. Here, we investigated (1) how changes in talkers’ emotional state affected talker identification accuracy, (2) how emotional state affected key features of voice acoustics, and (3) how emotion-related changes in these acoustic features affected listeners’ talker identification performance. Forty-eight listeners learned to identify talkers from sp
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Stearns, Scott Donaldson. "Acoustic window identification." Journal of the Acoustical Society of America 112, no. 5 (2002): 1744. http://dx.doi.org/10.1121/1.1526596.

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Deng, Jiang Hua, Jun Hong Dong, and Guang De Meng. "Sound Source Identification and Acoustic Contribution Analysis Using Nearfield Acoustic Holography." Advanced Materials Research 945-949 (June 2014): 717–24. http://dx.doi.org/10.4028/www.scientific.net/amr.945-949.717.

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The main goal of the present paper is to provide a method of source identification. Firstly, statistically optimal near-field acoustical holography (SONAH) techniques are applied to locate sound sources with the reflected sound field. In the presence of reflection plane parallel and perpendicular to the source plane, the incoming wave and reflected waves are separated based on the acoustic superposition principle and acoustic mirror image principle to satisfy the condition of the sound sources reconstruction using SONAH. Secondly, contribution of noise source to the special field point is anal
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Coker, Cecil H., and David R. Fischell. "Acoustic direction identification system." Journal of the Acoustical Society of America 80, no. 5 (1986): 1566. http://dx.doi.org/10.1121/1.394304.

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McCullah-Boozer, Megan R., Brooke M. Hinds, Logan T. Mathews, et al. "A comparative analysis of rocket noise recordings from wildlife acoustic monitoring devices." Journal of the Acoustical Society of America 153, no. 3_supplement (2023): A72. http://dx.doi.org/10.1121/10.0018204.

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Remote acoustic recorders are used in wildlife passive acoustical monitoring (PAM) and species identification. Such devices are designed to be relatively low-cost, user-friendly, weather-robust, and operate for extended periods with low maintenance. Usually, the precision of these devices is limited because most applications do not require high-fidelity measurements for typical wildlife PAM applications. However, the relatively low cost and flexibility of deployment beg the question if they can accurately record other noise sources, such as rocket launches. Such a situation calls for an evalua
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Samet, A., M. A. Ben Souf, O. Bareille, M. N. Ichchou, T. Fakhfakh, and M. Haddar. "Structural Source Identification from Acoustic Measurements Using an Energetic Approach." Journal of Mechanics 34, no. 4 (2017): 431–41. http://dx.doi.org/10.1017/jmech.2017.24.

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AbstractAn inverse energy method for the identification of the structural force in high frequency ranges from radiated noise measurements is presented in this paper. The radiation of acoustic energy of the structure coupled to an acoustic cavity is treated using an energetic method called the simplified energy method. The main novelty of this paper consists in using the same energy method to solve inverse structural problem. It consists of localization and quantification of the vibration source through the knowledge of acoustic energy density. Numerical test cases with different measurement po
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Iwatsubo, Takuzo, Shozo Kawamura, and Masahito Kamada. "Identification of Acoustic-Vibratory System by Acoustic Measurement." Shock and Vibration 3, no. 1 (1996): 27–37. http://dx.doi.org/10.1155/1996/925970.

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A new method for reducing ill-conditioning in a class of identification problems is proposed. The key point of the method is that the identified vibration of the sound source is expressed as a superposition of vibration modes. The mathematical property of the coefficient matrix, the practical error expanding ratio, and the stochastic error expanding ratio are investigated in a numerical example. The mode-superposition method is shown to be an effective tool for acoustic-vibratory inverse analysis.
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Gaudette, Jason E., and James A. Simmons. "Linear time-invariant (LTI) modeling for aerial and underwater acoustics." Journal of the Acoustical Society of America 153, no. 3_supplement (2023): A95. http://dx.doi.org/10.1121/10.0018285.

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Most newcomers to acoustic signal processing understand that linear time-invariant (LTI) filters can remove out-of-band noise from time series signals. What many acoustics researchers may not realize is that LTI models can be applied much more broadly, including to non-linear and time-variant systems. This presentation covers an overview of the autoregressive (AR), moving-average (MA), and autoregressive moving-average (ARMA) family of LTI models and their many useful applications in acoustics. Examples include analytic time-frequency processing of multi-component echolocation signals, fractio
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Kloser, R. J., T. Ryan, P. Sakov, A. Williams, and J. A. Koslow. "Species identification in deep water using multiple acoustic frequencies." Canadian Journal of Fisheries and Aquatic Sciences 59, no. 6 (2002): 1065–77. http://dx.doi.org/10.1139/f02-076.

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Multifrequency 12, 38, and 120 kHz acoustics were used to identify the dominant fish groups around a deepwater (>600 m) seamount (a known spawning site for orange roughy, Hoplostethus atlanticus) by amplitude mixing of the frequencies. This method showed three distinct acoustic groupings that corresponded to three groups of fishes based on size and swimbladder type: myctophids of total length less than 10 cm, morids and macrourids with lengths >30 cm, and orange roughy with a mean standard length of 36 cm. These three groups were the dominant groups caught in the demersal and pelagic tra
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Dissertations / Theses on the topic "Acoustic identification"

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Silva, Bruno Miguel Santos Antunes. "Automated acoustic identification of bat species." Master's thesis, Universidade de Évora, 2013. http://hdl.handle.net/10174/9101.

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Automated acoustic identification of bat species Recent improvements in bat survey methods in Portugal, especially automatic recording stations, have led to an analysis problem due to the amount of data obtained. In this thesis we propose to develop an automated analysis and classification method for bat echolocation calls by developing a computer program based on statistical models and using a reference database of bat calls recorded in Portugal to quickly analyze and classify large amounts of recordings. We recorded 2968 calls from 748 bats of 20 (of the 25) bat species known in mainland Por
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Zaheer, Ruba. "Acoustic source identification in noisy environments." Thesis, Edith Cowan University, Research Online, Perth, Western Australia, 2024. https://ro.ecu.edu.au/theses/2761.

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Acoustic Source Identification (ASI) has many industrial and environmental applications, and the associated techniques and systems are continually improving in accuracy and efficiency. The detection of acoustic sources in noisy environments has been a topic of interest for researchers and scientists in the past few years. Identifying acoustic sources has been useful in many industrial and military applications, including acoustic ranging, acoustic surveillance and navigation, robot-nature interaction, and hearing aids that visualise sounds. However, it is difficult to identify a sound source w
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DeMarco, Andrea. "Acoustic approaches to gender and accent identification." Thesis, University of East Anglia, 2015. https://ueaeprints.uea.ac.uk/53443/.

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There has been considerable research on the problems of speaker and language recognition from samples of speech. A less researched problem is that of accent recognition. Although this is a similar problem to language identification, different accents of a language exhibit more fine-grained differences between classes than languages. This presents a tougher problem for traditional classification techniques. In this thesis, we propose and evaluate a number of techniques for gender and accent classification. These techniques are novel modifications and extensions to state of the art algorithms, a
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Cabell, Randolph H. "The automatic identification of aerospace acoustic sources." Thesis, Virginia Tech, 1989. http://hdl.handle.net/10919/45932.

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<p>This work describes the design of an intelligent recognition system used to distinguish noise signatures of five different acoustic sources. The system uses pattern recognition techniques to identify the information obtained from a single microphone. A training phase is used in which the system learns to distinguish the sources and automatically selects features for optimal performance. Results were obtained by training the system to distinguish jet planes, propeller planes, a helicopter, train, and wind turbine from one another, then presenting similar sources to the system and recor
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Fox, Elizabeth J. S. "Call-independent identification in birds." University of Western Australia. School of Animal Biology, 2008. http://theses.library.uwa.edu.au/adt-WU2008.0218.

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[Truncated abstract] The identification of individual animals based on acoustic parameters is a non-invasive method of identifying individuals with considerable advantages over physical marking procedures. One requirement for an effective and practical method of acoustic individual identification is that it is call-independent, i.e. determining identity does not require a comparison of the same call or song type. This means that an individuals identity over time can be determined regardless of any changes to its vocal repertoire, and different individuals can be compared regardless of whether
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Schuler, Leo Pius. "Wireless identification and sensing using surface acoustic wave devices." Thesis, University of Canterbury. Electrical Engineering, 2003. http://hdl.handle.net/10092/1081.

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Wireless Surface Acoustic Wave (SAW) devices were fabricated and tested using planar Lithium Niobate (LiNbO₃) as substrate. The working frequencies were in the 180 MHz and 360 MHz range. Using a network analyser, the devices were interrogated with a wireless range of more than 2 metres. Trials with Electron Beam Lithography (EBL) to fabricate SAW devices working in the 2450 MHz with a calculated feature size of 350 nm are discussed. Charging problems became evident as LiNbO₃ is a strong piezoelectric and pyroelectric material. Various attempts were undertaken to neutralise the charging problem
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Schuler, Leo P. "Wireless identification and sensing using surface acoustic wave devices." Thesis, University of Canterbury. Engineering, 2003. http://hdl.handle.net/10092/8565.

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Wireless Surface Acoustic Wave (SAW) devices were fabricated and tested using planar Lithium Niobate (LiNbO₃) as substrate. The working frequencies were in the 180 MHz and 360 MHz range. Using a network analyser, the devices were interrogated with a wireless range of more than 2 metres. Trials with Electron Beam Lithography (EBL) to fabricate SAW devices working in the 2450 MHz with a calculated feature size of 350 nm are discussed. Charging problems became evident as LiNbO₃ is a strong piezoelectric and pyroelectric material. Various attempts were undertaken to neutralise the charging problem
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Hedayetullah, Amin Mohammad. "Optimization of identification of particle impacts using acoustic emission." Thesis, Robert Gordon University, 2018. http://hdl.handle.net/10059/3116.

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Air borne or liquid-laden solid particle transport is a common phenomenon in various industrial applications. Solid particles, transported at severe operating conditions such as high flow velocity, can cause concerns for structural integrity through wear originated from particle impacts with structure. To apply Acoustic Emission (AE) in particle impact monitoring, previous researchers focused primarily on dry particle impacts on dry target plate and/or wet particle impacts on wet or dry target plate. For dry particle impacts on dry target plate, AE events energy, calculated from the recorded f
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Schofield, James. "Real-time acoustic identification of invasive wood-boring beetles." Thesis, University of York, 2011. http://etheses.whiterose.ac.uk/1978/.

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Wood-boring beetles are a cause of significant economic and environmental cost across the world. A number of species which are not currently found in the United Kingdom are constantly at risk of being accidentally imported due to the volume of global trade in trees and timber. The species which are of particular concern are the Asian Longhorn (Anoplophora glabripennis), Citrus Longhorn (A. chinensis) and Emerald Ash Borer (Agrilus planipennis). The Food and Environment Research Agency's plant health inspectors currently manually inspect high risk material at the point of import. The developmen
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Moat, Trevor P. B. M. "Orthogonal adaptive digital filters with applications to acoustic system identification." Thesis, National Library of Canada = Bibliothèque nationale du Canada, 1998. http://www.collectionscanada.ca/obj/s4/f2/dsk2/tape17/PQDD_0025/MQ27022.pdf.

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Books on the topic "Acoustic identification"

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Helwani, Karim. Adaptive Identification of Acoustic Multichannel Systems Using Sparse Representations. Springer International Publishing, 2015. http://dx.doi.org/10.1007/978-3-319-08954-6.

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Banks, H. Thomas. Parameter estimation in a structural acoustic system with fully nonlinear coupling conditions. Institute for Computer Applications in Science and Engineering, NASA Langley Research Center, 1994.

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C, Smith R., and Institute for Computer Applications in Science and Engineering., eds. Parameter estimation in a structural acoustic system with fully nonlinear coupling conditions. Institute for Computer Applications in Science and Engineering, NASA Langley Research Center, 1994.

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Healey, Anthony J. Sonar signal acquisition and processing for identification and classification of ship hull fouling. Naval Postgraduate School, 1993.

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Farren, Maureen A. Some experiments with underwater acoustic returns from cylinders relative to object identification for AUV operation. Naval Postgraduate School, 1988.

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United States. Bureau of Mines, ed. Multiple-channel trigger circuit for noise discrimination in ultrasonic acoustic emission studies. U.S. Dept. of the Interior, Bureau of Mines, 1995.

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Hanson, David R. Multiple-channel trigger circuit for noise discrimination in ultrasonic acoustic emission studies. U.S. Dept. of the Interior, Bureau of Mines, 1995.

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Hanson, David R. Multiple-channel trigger circuit for noise discrimination in ultrasonic acoustic emission studies. U.S. Dept. of the Interior, Bureau of Mines, 1995.

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Hanson, David R. Multiple-channel trigger circuit for noise discrimination in ultrasonic acoustic emission studies. U.S. Dept. of the Interior, Bureau of Mines, 1995.

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Hanson, David R. Multiple-channel trigger circuit for noise discrimination in ultrasonic acoustic emission studies. U.S. Dept. of the Interior, Bureau of Mines, 1995.

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Book chapters on the topic "Acoustic identification"

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Sas, P. "Numerical Acoustic Radiation Models." In Application of System Identification in Engineering. Springer Vienna, 1988. http://dx.doi.org/10.1007/978-3-7091-2628-8_4.

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Sas, P. "Digital Acoustic Intensity Measurements." In Application of System Identification in Engineering. Springer Vienna, 1988. http://dx.doi.org/10.1007/978-3-7091-2628-8_5.

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Tacconi, Giorgio, and Antonio Tiano. "Applied Modelling to Underwater Vehicles Identification." In Underwater Acoustic Data Processing. Springer Netherlands, 1989. http://dx.doi.org/10.1007/978-94-009-2289-1_45.

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Miles, Ronald N. "Parameter Identification of Acoustic Systems." In Mechanical Engineering Series. Springer International Publishing, 2019. http://dx.doi.org/10.1007/978-3-030-22676-3_13.

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Miles, Ronald N. "Parameter Identification of Acoustic Systems." In Mechanical Engineering Series. Springer International Publishing, 2023. http://dx.doi.org/10.1007/978-3-031-33009-4_13.

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Castagnède, Bernard. "Acoustic Emission Source Location in Anisotropic Composite Plates." In Mechanical Identification of Composites. Springer Netherlands, 1991. http://dx.doi.org/10.1007/978-94-011-3658-7_49.

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Munier, J., G. Jourdain, and G. Y. Delisle. "A New Algorithm for the Identification of Distorted Wavefronts." In Underwater Acoustic Data Processing. Springer Netherlands, 1989. http://dx.doi.org/10.1007/978-94-009-2289-1_7.

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Narkhede, Meenal, and Rashmika Patole. "Acoustic Scene Identification for Audio Authentication." In Advances in Intelligent Systems and Computing. Springer Singapore, 2019. http://dx.doi.org/10.1007/978-981-13-3600-3_56.

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Acconcjaioco, Michelangelo, and Stavros Ntalampiras. "Acoustic Identification of Nocturnal Bird Species." In Communications in Computer and Information Science. Springer Singapore, 2020. http://dx.doi.org/10.1007/978-981-15-4828-4_1.

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Benesty, Jacob, Constantin Paleologu, Tomas Gänsler, and Silviu Ciochină. "System Identification with the Wiener Filter." In A Perspective on Stereophonic Acoustic Echo Cancellation. Springer Berlin Heidelberg, 2011. http://dx.doi.org/10.1007/978-3-642-22574-1_3.

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Conference papers on the topic "Acoustic identification"

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Agarwal, Anchal, Praveen Dhoundiyal, Vikrant Sharma, and Satvik Vats. "Acoustic Based Drone Identification and Classification." In 2024 International Conference on Electrical Electronics and Computing Technologies (ICEECT). IEEE, 2024. http://dx.doi.org/10.1109/iceect61758.2024.10739288.

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Yamazaki, Shigeki, and Mitsuharu Matsumoto. "Object Identification Using Active Acoustic Sensing." In 2025 2nd International Conference on Advanced Innovations in Smart Cities (ICAISC). IEEE, 2025. https://doi.org/10.1109/icaisc64594.2025.10959484.

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chengyu, wang, jin long, fang ruiuua, and tian xinming. "Symmetric structure for teacher-student home acoustic scene domain adaptation." In Third International Conference on Machine Vision, Automatic Identification and Detection, edited by Renchao Jin. SPIE, 2024. http://dx.doi.org/10.1117/12.3036479.

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chen, wuchao, Lingli Xi, Xumeng Xie, et al. "Exploration and research on acoustic imaging technology in gas leakage detection." In Third International Conference on Machine Vision, Automatic Identification and Detection, edited by Renchao Jin. SPIE, 2024. http://dx.doi.org/10.1117/12.3035544.

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Hu, Zheng, Fidel Lozano-Galant, Jose Antonio Lozano-Galant, and Ye Xia. "Acoustic Signal Analysis in Bridge Territory for Traffic and Collision Identification." In IABSE Symposium, Tokyo 2025: Environmentally Friendly Technologies and Structures: Focusing on Sustainable Approaches. International Association for Bridge and Structural Engineering (IABSE), 2025. https://doi.org/10.2749/tokyo.2025.1244.

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&lt;p&gt;This paper proposes a methodology for utilizing acoustic signals as a source of information and integrating them as supplementary data into the bridge structural health monitoring system after digital analysis. The approach leverages the advantages of non-contact monitoring and the low-cost characteristic of acoustic sensors to collect various acoustic signals during the bridge operation period, including vehicle passing and collision sounds. The collected acoustic signals are labeled and then transformed into features such as normalized time series waveforms or Mel spectrograms, whic
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Sharma, Manish, and Richard J. Mammone. "Neural tree network for speech segmentation into subword acoustic units." In Substance Identification Technologies, edited by James L. Flanagan, Richard J. Mammone, Albert E. Brandenstein, et al. SPIE, 1994. http://dx.doi.org/10.1117/12.172489.

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Cevher, V., and J. H. McClellan. "An acoustic multiple target tracker." In 2005 Microwave Electronics: Measurements, Identification, Applications. IEEE, 2005. http://dx.doi.org/10.1109/ssp.2005.1628648.

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Rusovici, Razvan, and Daniel Mason. "Coupled Acoustic-Structural-Piezoelectric Modeling of Synthetic Jet." In Modelling, Identification and Control. ACTAPRESS, 2014. http://dx.doi.org/10.2316/p.2014.809-064.

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Calkins, Luke, Reza Khodayi-mehr, Wilkins Aquino, and Michael M. Zavlanos. "Physics-Based Acoustic Source Identification." In 2018 IEEE Conference on Decision and Control (CDC). IEEE, 2018. http://dx.doi.org/10.1109/cdc.2018.8619483.

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EVANS, N., and D. CHESMORE. "AUTOMATED ACOUSTIC IDENTIFICATION OF VEHICLES." In Spring Conference Acoustics 2008. Institute of Acoustics, 2023. http://dx.doi.org/10.25144/17586.

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Reports on the topic "Acoustic identification"

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Cobb, Wesley. Acoustic Identification of Filler Materials in Unexploded Ordnance. Defense Technical Information Center, 2006. http://dx.doi.org/10.21236/ada468491.

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Roch, Marie A. Passive Acoustic Monitoring for the Detection and Identification of Marine Mammals. Defense Technical Information Center, 2010. http://dx.doi.org/10.21236/ada541770.

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Cobb, Wesley. Operational Evaluation of a New Acoustic Technique for UXO Filler Identification. Defense Technical Information Center, 2009. http://dx.doi.org/10.21236/ada520496.

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Cobb, Wes. Operational Evaluation of a New Acoustic Technique for UXO Filler Identification. Defense Technical Information Center, 2010. http://dx.doi.org/10.21236/ada520499.

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Perry, R. L., and R. S. Roberts. In-situ identification of anti-personnel mines using acoustic resonant spectroscopy. Office of Scientific and Technical Information (OSTI), 1999. http://dx.doi.org/10.2172/8430.

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Bucaro, J. A., B. H. Houston, H. Simpson, et al. Wide Area Detection and Identification of Underwater UXO Using Structural Acoustic Sensors. Defense Technical Information Center, 2011. http://dx.doi.org/10.21236/ada546324.

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Hedlin, Michael A. Regional Small-Event Identification Using Networks and Arrays of Seismic and Acoustic Sensors. Defense Technical Information Center, 2006. http://dx.doi.org/10.21236/ada455277.

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Sinha, D. N., K. Springer, W. Han, D. Lizon, and S. Kogan. Applications of swept-frequency acoustic interferometer for nonintrusive detection and identification of chemical warfare compounds. Office of Scientific and Technical Information (OSTI), 1997. http://dx.doi.org/10.2172/555542.

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D'Amico, Angela, Christopher Kyburg, and Rowena Carlson. Software Tools for Visual and Acoustic Real-Time Tracking of Marine Mammals: Whale Identification and Logging Display (WILD). Defense Technical Information Center, 2010. http://dx.doi.org/10.21236/ada533470.

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Bucaro, Joseph A., Brian H. Houston, Harry Simpson, et al. Wide Area Detection and Identification of Underwater UXO Using Structural Acoustic Senors: 4th Annual Report to SERDP MM-1513. Defense Technical Information Center, 2010. http://dx.doi.org/10.21236/ada525163.

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