Relevant bibliographies by topics / Acoustic fingerprinting

Contents

  1. Journal articles
  2. Dissertations / Theses
  3. Book chapters
  4. Conference papers

Academic literature on the topic 'Acoustic fingerprinting'

Author: Grafiati
Published: 3 June 2025
Last updated: 1 August 2025

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Journal articles on the topic "Acoustic fingerprinting"

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Hussain, F., H. A. Habib, and M. J. Khan. "A Framework for Music-Speech Segregation using Music Fingerprinting and Acoustic Echo Cancellation Principle." Nucleus 52, no. 1 (2015): 29–39. https://doi.org/10.71330/thenucleus.2015.663.

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Background interference creates voice intelligibility issue for listener. This research work considers background music as interference for communication through smart phone in areas with loud background music. This paper proposes a novel framework for background music segregation from human speech using music fingerprinting and acoustic echo cancellation. Initially, background music is searched in the database by music fingerprinting. Identified background music is registered and segregated using acoustic echo cancellation. Proposed approach generates better quality music speech segregation t
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Shreedharan, Srisharan, Chiranth Hegde, Sunil Sharma, and Harsha Vardhan. "Acoustic fingerprinting for rock identification during drilling." International Journal of Mining and Mineral Engineering 5, no. 2 (2014): 89. http://dx.doi.org/10.1504/ijmme.2014.060193.

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Firdaus, Firdaus, Noor Azurati Ahmad, and Shamsul Sahibuddin. "A Review of Hybrid Indoor Positioning Systems Employing WLAN Fingerprinting and Image Processing." International journal of electrical and computer engineering systems 10, no. 2 (2020): 59–72. http://dx.doi.org/10.32985/ijeces.10.2.2.

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Location-based services (LBS) are a significant permissive technology. One of the main components in indoor LBS is the indoor positioning system (IPS). IPS utilizes many existing technologies such as radio frequency, images, acoustic signals, as well as magnetic sensors, thermal sensors, optical sensors, and other sensors that are usually installed in a mobile device. The radio frequency technologies used in IPS are WLAN, Bluetooth, Zig Bee, RFID, frequency modulation, and ultra-wideband. This paper explores studies that have combined WLAN fingerprinting and image processing to build an IPS. T
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Zhang, Zhengyan, Yue Yu, Liang Chen, and Ruizhi Chen. "Hybrid Indoor Positioning System Based on Acoustic Ranging and Wi-Fi Fingerprinting under NLOS Environments." Remote Sensing 15, no. 14 (2023): 3520. http://dx.doi.org/10.3390/rs15143520.

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An accurate indoor positioning system (IPS) for the public has become an essential function with the fast development of smart city-related applications. The performance of the current IPS is limited by the complex indoor environments, the poor performance of smartphone built-in sensors, and time-varying measurement errors of different location sources. This paper introduces a hybrid indoor positioning system (H-IPS) that combines acoustic ranging, Wi-Fi fingerprinting, and low-cost sensors. This system is designed specifically for large-scale indoor environments with non-line-of-sight (NLOS)
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Lee, Kun Chou. "Underwater acoustic localisation by GMM fingerprinting with noise reduction." International Journal of Sensor Networks 31, no. 1 (2019): 1. http://dx.doi.org/10.1504/ijsnet.2019.10022954.

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Lee, Kun Chou. "Underwater acoustic localisation by GMM fingerprinting with noise reduction." International Journal of Sensor Networks 31, no. 1 (2019): 1. http://dx.doi.org/10.1504/ijsnet.2019.101568.

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Wang, Shuopeng, Peng Yang, and Hao Sun. "Fingerprinting Acoustic Localization Indoor Based on Cluster Analysis and Iterative Interpolation." Applied Sciences 8, no. 10 (2018): 1862. http://dx.doi.org/10.3390/app8101862.

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Fingerprinting acoustic localization usually requires tremendous time and effort for database construction in sampling phase and reference points (RPs) matching in positioning phase. To improve the efficiency of this acoustic localization process, an iterative interpolation method is proposed to reduce the initial RPs needed for the required positioning accuracy by generating virtual RPs in positioning phase. Meanwhile, a two-stage matching method based on cluster analysis is proposed for computation reduction of RPs matching. Results reported show that, on the premise of ensuring positioning
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Horváth-Mezőfi, Zsuzsanna, László Baranyai, Lien Le Phuong Nguyen, et al. "Evaluation of Color and Pigment Changes in Tomato after 1-Methylcyclopropene (1-MCP) Treatment." Sensors 24, no. 8 (2024): 2426. http://dx.doi.org/10.3390/s24082426.

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The Polar Qualification System (PQS) was applied on hue spectra fingerprinting to describe color changes in tomato during storage. The cultivar ‘Pitenza’ was harvested at six different maturity stages, and half of the samples were subjected to gaseous 1-methylcyclopropene (1-MCP) treatment. Reference color parameters were recorded with a vision system colorimeter instrument, and the fruit pigment concentration was assessed with the DA-index®. Additionally, acoustic firmness (Stiffness) was measured. All acquired reference parameters were used to grade fruit in the supply chain. The applied 1-M
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Seo, Dae-Hoon, Jung-Woo Choi, and Yang-Hann Kim. "Buzz, squeak, and rattle noise classification by using acoustic-fingerprinting technology." Journal of the Acoustical Society of America 135, no. 4 (2014): 2297. http://dx.doi.org/10.1121/1.4877553.

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Semma, Andi Bahtiar, Kusrini Kusrini, Arif Setyanto, Bruno Da Silva, and An Braeken. "Environmental Acoustic Features Robustness Analysis: A Multi-Aspecs Study." INTENSIF: Jurnal Ilmiah Penelitian dan Penerapan Teknologi Sistem Informasi 9, no. 1 (2025): 46–59. https://doi.org/10.29407/intensif.v9i1.23723.

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Abstract—Background: Acoustic signals are complex, with temporal, spectral, and amplitude variations. Their non-stationarity complicates analysis, as traditional methods often fail to capture their richness. Environmental factors like reflections, refractions, and noise further distort signals. While advanced techniques such as adaptive filtering and deep learning exist, comprehensive acoustic feature analysis remains limited. Objective: This study investigates which acoustic features maintain the highest robustness across diverse environments while preserving discriminative power. Methods: Au
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Dissertations / Theses on the topic "Acoustic fingerprinting"

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Choi, Bumsuk. "Acoustic source localization in 3D complex urban environments." Diss., Virginia Tech, 2012. http://hdl.handle.net/10919/27739.

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The detection and localization of important acoustic events in a complex urban environment, such as gunfire and explosions, is critical to providing effective surveillance of military and civilian areas and installations. In a complex environment, obstacles such as terrain or buildings introduce multipath propagations, reflections, and diffractions which make source localization challenging. This dissertation focuses on the problem of source localization in three-dimensional (3D) realistic urban environments. Two different localization techniques are developed to solve this problem: a) Beamfor
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Aloui, Nadia. "Localisation sonore par retournement temporel." Thesis, Grenoble, 2014. http://www.theses.fr/2014GRENT079/document.

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L'objectif général de cette thèse était de proposer une solution de localisation en intérieur à la fois simple et capable de surmonter les défis de la propagation dans les environnements en intérieur. Pour ce faire, un système de localisation basé sur la méthode des signatures et adoptant le temps d'arrivée du signal de l'émetteur au récepteur comme signature, a été proposé. Le système présente deux architectures différentes, une première orientée privée utilisant la méthode d'accès multiple à répartition par code et une deuxième centralisée basée sur la méthode d'accès multiple à répartition
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Dzhivhuho, Godfrey Azwinndini. "Isolation and characterization of microsatellite markers for human identification in the vhembe District, Limpopo Province, South Africa." Diss., 2015. http://hdl.handle.net/11602/209.

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Book chapters on the topic "Acoustic fingerprinting"

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Álvarez Franco, Fernando J. "Fundamentals of Airborne Acoustic Positioning Systems." In Geographical and Fingerprinting Data to Create Systems for Indoor Positioning and Indoor/Outdoor Navigation. Elsevier, 2019. http://dx.doi.org/10.1016/b978-0-12-813189-3.00017-4.

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Conference papers on the topic "Acoustic fingerprinting"

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Liu, Yu, Yifei Cheng, Yujia Zhu, Yong Ding, Yong Sun, and Xiaoou Zhang. "Knocking on IP: Unveiling Websites through Cache-Aware Fingerprinting." In ICASSP 2025 - 2025 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP). IEEE, 2025. https://doi.org/10.1109/icassp49660.2025.10890152.

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Zhou, Zhe, Wenrui Diao, Xiangyu Liu, and Kehuan Zhang. "Acoustic Fingerprinting Revisited." In CCS'14: 2014 ACM SIGSAC Conference on Computer and Communications Security. ACM, 2014. http://dx.doi.org/10.1145/2660267.2660300.

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Cevher, V., R. Chellappa, and J. H. McClellan. "Joint Acoustic-Video Fingerprinting of Vehicles, Part I." In 2007 IEEE International Conference on Acoustics, Speech and Signal Processing - ICASSP '07. IEEE, 2007. http://dx.doi.org/10.1109/icassp.2007.366343.

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Cevher, V., F. Guo, A. C. Sankaranarayanan, and R. Chellappa. "Joint Acoustic-Video Fingerprinting of Vehicles, Part II." In 2007 IEEE International Conference on Acoustics, Speech, and Signal Processing. IEEE, 2007. http://dx.doi.org/10.1109/icassp.2007.366344.

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Ondel, Lucas, Xavier Anguera, and Jordi Luque. "MASK+: Data-driven regions selection for acoustic fingerprinting." In ICASSP 2015 - 2015 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP). IEEE, 2015. http://dx.doi.org/10.1109/icassp.2015.7177986.

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Lee, Kun-Chou, Jhih-Sian Ou, and Lan-Ting Wang. "Underwater acoustic localization by probabilistic fingerprinting in eigenspace." In OCEANS 2009. IEEE, 2009. http://dx.doi.org/10.23919/oceans.2009.5422226.

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Jiang, Meng, Jan Lundgren, Shahab Pasha, Marco Carratu, Consolatina Liguori, and Goran Thungstrom. "Indoor Silent Object Localization using Ambient Acoustic Noise Fingerprinting." In 2020 IEEE International Instrumentation and Measurement Technology Conference (I2MTC). IEEE, 2020. http://dx.doi.org/10.1109/i2mtc43012.2020.9129086.

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Ren, Yanzhi, Tingyuan Yang, Zhiliang Xia, et al. "Secure and Robust Two Factor Authentication via Acoustic Fingerprinting." In IEEE INFOCOM 2023 - IEEE Conference on Computer Communications. IEEE, 2023. http://dx.doi.org/10.1109/infocom53939.2023.10229054.

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Schmitt, Rainer M., and Justin Owen. "Acoustic impediography: Imaging surface acoustic impedance using 1–3 piezo-composite for Integrated fingerprinting." In 2011 IEEE 61st Electronic Components and Technology Conference (ECTC). IEEE, 2011. http://dx.doi.org/10.1109/ectc.2011.5898678.

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Thoen, Bart, Stijn Wielandt, and Lieven De Strycker. "Fingerprinting Method for Acoustic Localization Using Low-Profile Microphone Arrays." In 2018 International Conference on Indoor Positioning and Indoor Navigation (IPIN). IEEE, 2018. http://dx.doi.org/10.1109/ipin.2018.8533866.

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