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Journal articles on the topic 'Acoustic fingerprinting'

Author: Grafiati

Published: 3 June 2025

Last updated: 1 August 2025

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1

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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2

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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3

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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4

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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5

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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6

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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7

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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8

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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9

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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10

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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11

DeCourcy, Brendan J., and Ying-Tsong Lin. "Spatial and temporal variation of three-dimensional ship noise coherence in a submarine canyon." Journal of the Acoustical Society of America 153, no. 2 (2023): 1042–51. http://dx.doi.org/10.1121/10.0017166.

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Ship noise recorded by a vertical hydrophone array in the Mississippi Canyon region of the Gulf of Mexico is shown to contain the acoustic influence of bathymetric features, seabed properties, and water column sound speeds. Noise coherence is demonstrated to be an effective metric not just for identifying ship traffic in recorded data but also for “fingerprinting” the environment. A three-dimensional acoustics model adopting automatic identification system ship track information and realistic oceanographic conditions is used to compute noise coherence distributions across the canyon area and e

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12

Rao, K. S., A. K. Chaudhary, F. Yehya, and A. Sudheer Kumar. "Study of acoustic fingerprinting of nitromethane and some triazole derivatives using UV 266nm pulsed photoacoustic pyrolysis technique." Spectrochimica Acta Part A: Molecular and Biomolecular Spectroscopy 147 (August 2015): 316–23. http://dx.doi.org/10.1016/j.saa.2015.03.017.

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13

Manas Sharma. "Real-time voice modulation detection: Protecting against AI-enabled ransomware call scams." World Journal of Advanced Engineering Technology and Sciences 15, no. 2 (2025): 1005–15. https://doi.org/10.30574/wjaets.2025.15.2.0576.

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This article addresses the growing threat of AI-enabled voice modulation scams by developing a comprehensive framework for real-time detection on mobile devices. The article examines current detection methodologies including machine learning classification, statistical anomaly detection, watermarking, model fingerprinting, and adversarial frameworks. Technical challenges are analyzed across acoustic feature extraction, temporal inconsistency identification, prosodic pattern recognition, real-time processing constraints, and differentiation between legitimate and fraudulent voice alterations. T

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14

Algredo-Badillo, Ignacio, Brenda Sánchez-Juárez, Kelsey A. Ramírez-Gutiérrez, Claudia Feregrino-Uribe, Francisco López-Huerta, and Johan J. Estrada-López. "Analysis and Hardware Architecture on FPGA of a Robust Audio Fingerprinting Method Using SSM." Technologies 10, no. 4 (2022): 86. http://dx.doi.org/10.3390/technologies10040086.

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The significant volume of sharing of digital media has recently increased due to the pandemic, raising the number of unauthorized uses of these media, such as emerging unauthorized copies, forgery, the lack of copyright, and electronic fraud, among others. In particular, several applications integrate services or products such as music distribution, content management, audiobooks, streaming, and so on, which require users to demonstrate and guarantee their audio ownership. The use of acoustic fingerprint technology has emerged as a solution that is widely used to secure audio applications. Thi

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15

A.Shaji, George, and S.Sagayarajan. "Acoustic Eavesdropping: How AIs Can Steal Your Secrets by Listening to Your Typing." Partners Universal International Innovation Journal ( PUIIJ) 01, no. 04 (2023): 1–14. https://doi.org/10.5281/zenodo.8260814.

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<strong>Abstract -</strong> Recent advances in artificial intelligence have enabled a disturbing new form of cyberattack - acoustic side channel attacks, where AIs can identify keystrokes and steal passwords simply by listening to the sounds of typing. A study published in 2021 demonstrated this is possible with 93% accuracy using common video conferencing apps like Zoom. By analyzing audio recordings, AIs can detect the precise timings between keystrokes, and map patterns to reveal what is being typed. This poses serious risks, as acoustic eavesdropping can steal passwords, private messages,

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16

Li, Yian, and Yibo Huang. "End-to-End Speech Hash Retrieval Algorithm based on Speech Content and Pre-training." Frontiers in Computing and Intelligent Systems 8, no. 2 (2024): 22–28. http://dx.doi.org/10.54097/xa8rfs68.

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Traditional speech retrieval tasks, such as audio fingerprinting and Spoken Word Detection Query (STD-QbE), focus on feature matching for speech or keyword retrieval. In this paper, we present a content-based speech retrieval algorithm. The algorithm allows matching based on the complete content of sentences in speech, not just local features or keywords. Importantly, it completely bypasses the Automatic Speech Recognition (ASR) transcription process by mapping the acoustic features of the sentence directly to the Hamming space. Retrieval of the same content is then achieved by comparing Hammi

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17

PRERNA, R. KUMBHARE, and ANJALI A. YADAV MRS. "SURVEY ON RECOGNITION OF S1 AND S2 HEART SOUND USING DEEP NEURAL NETWORKS." JournalNX - A Multidisciplinary Peer Reviewed Journal NCMTEE-2K17 (March 26, 2017): 27–31. https://doi.org/10.5281/zenodo.1451208.

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This study focuses on the first(S1) and second (S2) heart sound affirmation build just concerning acoustic attributes; the suppositions of the individual ranges of S1 and S2 additionally, time breaks of S1â€“S2 and S2â€“S1 are excluded in the affirmation handle. The crucial target is to analyze whether tried and true S1 and S2 affirmation execution can even now be accomplished under conditions where the term and interval information wont not be accessible. Methodologies: A significant neural framework (DNN) procedure is used for seeing S1 and S2 heart sounds.

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18

Sai Manoj Jayakannan. "Securing Voice-Based Financial Authentication in the Era of AI Voice Cloning: Challenges, Vulnerabilities, and Counter-Measures." Journal of Computer Science and Technology Studies 7, no. 4 (2025): 515–20. https://doi.org/10.32996/jcsts.2025.7.4.60.

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Voice-based authentication in financial services offers convenience but faces unprecedented challenges from advancing AI voice cloning technologies. These synthetic speech capabilities now generate remarkably convincing voice replicas with minimal sample data, creating critical security vulnerabilities. Financial institutions experiencing successful voice-based attacks face substantial monetary losses, regulatory penalties, and damaged customer trust. This article examines the evolution of voice synthesis technologies, their specific vulnerabilities in financial authentication systems, and pre

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19

Khan, Md Abdullah Al Hafiz, Nirmalya Roy, and H. M. Sajjad Hossain. "Wearable Sensor-Based Location-Specific Occupancy Detection in Smart Environments." Mobile Information Systems 2018 (2018): 1–21. http://dx.doi.org/10.1155/2018/4570182.

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Occupancy detection helps enable various emerging smart environment applications ranging from opportunistic HVAC (heating, ventilation, and air-conditioning) control, effective meeting management, healthy social gathering, and public event planning and organization. Ubiquitous availability of smartphones and wearable sensors with the users for almost 24 hours helps revitalize a multitude of novel applications. The inbuilt microphone sensor in smartphones plays as an inevitable enabler to help detect the number of people conversing with each other in an event or gathering. A large number of oth

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20

Yano, Shouhei. "3DMRI - Elucidating the origin of biometric authentication based on the acoustic characteristics of the ears with high resolution 3D MRI." Impact 2020, no. 2 (2020): 30–32. http://dx.doi.org/10.21820/23987073.2020.2.30.

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A world run on cash transactions is rapidly disappearing. The power and connectivity of the Internet has driven most business toward digital solutions. Paying bills and shopping is done online and paying while outside of the home is increasingly done by card or even smartphone apps. The diminished role of cash, while convenient, does require that consumers put their trust into security systems beyond their own control. Someone can safeguard their own wallet but cannot encrypt personal digital payment data. This transition has led to the vast cybersecurity industry which is constantly in need o

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21

Carpenter, Chris. "Approach Interprets Fracture Growth Through Microseismic Quiescent Zones." Journal of Petroleum Technology 77, no. 06 (2025): 1–4. https://doi.org/10.2118/0625-0018-jpt.

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_ This article, written by JPT Technology Editor Chris Carpenter, contains highlights of paper SPE 223533, “Fracture Growth Through Microseismic Quiescent Zones: Indication of Stealth or Complex Fracturing?” by Shawn C. Maxwell, SPE, Stacy Doss, and Robert Holman, Ovintiv, et al. The paper has not been peer reviewed. _ Microseismicity levels tend to vary from one lithological unit to the next, with some layers being predominantly quiet and lacking any microseismicity. Because shear-activated deformation associated with microseismicity will depend on the geomechanical properties and natural fab

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22

Sonoda, Kotaro, Ryouichi Nishimura, and Yôiti Suzuki. "Reduction of distributed data size in audio content fingerprinting (CoFIP)." Acoustical Science and Technology 26, no. 4 (2005): 362–64. http://dx.doi.org/10.1250/ast.26.362.

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23

Burges, C. J. C., J. C. Platt, and S. Jana. "Distortion discriminant analysis for audio fingerprinting." IEEE Transactions on Speech and Audio Processing 11, no. 3 (2003): 165–74. http://dx.doi.org/10.1109/tsa.2003.811538.

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24

Zia, Shafaq, Johan E. Carlson, and Pia Åkerfeldt. "Prediction of manufacturing parameters of additively manufactured 316L steel samples using ultrasound fingerprinting." Ultrasonics 137 (February 2024): 107196. http://dx.doi.org/10.1016/j.ultras.2023.107196.

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25

Pogorilyi, Oleksandr, Mohammad Fard, David Taylor, and John Davy. "Landmark-based audio fingerprinting system applied to vehicle squeak and rattle noises." Noise Control Engineering Journal 68, no. 2 (2020): 113–24. http://dx.doi.org/10.3397/1/376810.

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This article investigates whether the robust landmark-based audio fingerprinting method created for recognizing music can be applied to identify squeak and rattle (S&R) types of sounds. The identification is performed by matching a query audio sample to the perceptually closest audio sample that is stored in a pre-developed database of S&R audio sounds. The aim of the application of the method in the automotive industry is to facilitate the process S&R experts go through during sound identification. The experimental results show that the algorithm can be used for identification of

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26

Wahia, Hafida, Cunshan Zhou, Abdullateef Taiye Mustapha, et al. "Storage effects on the quality quartet of orange juice submitted to moderate thermosonication: Predictive modeling and odor fingerprinting approach." Ultrasonics Sonochemistry 64 (June 2020): 104982. http://dx.doi.org/10.1016/j.ultsonch.2020.104982.

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27

Exner, Hans Eckart. "STEREOLOGY AND 3D MICROSCOPY: USEFUL ALTERNATIVES OR COMPETITORS IN THE QUANTITATIVE ANALYSIS OF MICROSTRUCTURES?" Image Analysis & Stereology 23, no. 2 (2011): 73. http://dx.doi.org/10.5566/ias.v23.p73-82.

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With the rapid development of modern techniques for producing 3D images, the assessment of 3D geometry from 2D sections of projections by stereological methods seems to become more and more redundant. The paper aims to show the limits of the two approaches and to outline their relative advantages in practical applications. It is concluded that, for a large variety of applications, classical stereological methods are the most effective way to characterize 3D geometry of irregular microstructures. The basic equations for useful global (field) parameters are summarized and their assessment by man

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28

Jana, Saikat, and Nikhil Bhalla. "Acoustic Fingerprinting and Nanoslip Dynamics of Biofilms." Advanced Functional Materials, November 12, 2024. http://dx.doi.org/10.1002/adfm.202414687.

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AbstractIt is reported that bacteria can generate nanomotion, but understanding the complex dynamics of bacterial colony gliding on solid interfaces has remained unresolved. Here, this work captures the real‐time development and gliding of bacterial biofilms on vibrating solids made of piezoelectric quartz. The gliding, characterized by liquid slips, is measured in form of frequency and dissipation changes of the vibrating solid. These vibrations enable the generation of distinct acoustic fingerprints (sound/ music) of the three phases of biofilm development: viscoelastic strengthening, biofil

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29

Ding, Xuejie, and Tao Zhang. "State Identification of Smart Devices Using Acoustic Fingerprinting." DEStech Transactions on Engineering and Technology Research, apetc (June 26, 2017). http://dx.doi.org/10.12783/dtetr/apetc2017/11268.

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30

Ren, Yanzhi, Tingyuan Yang, Zhiliang Xia, et al. "Robust Mobile Two-Factor Authentication Leveraging Acoustic Fingerprinting." IEEE Transactions on Mobile Computing, 2024, 1–17. http://dx.doi.org/10.1109/tmc.2024.3391184.

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31

Ren, Yanzhi, Tingyuan Yang, Yufei Zhou, et al. "Two-Factor Authentication Based on Acoustic Fingerprinting in Modulation Domain." IEEE Transactions on Mobile Computing, 2024, 1–14. https://doi.org/10.1109/tmc.2024.3522077.

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32

Lee, Sunwoo, and Dong Hoon Lee. "From Attack to Identification: MEMS Sensor Fingerprinting using Acoustic Signals." IEEE Internet of Things Journal, 2022, 1. http://dx.doi.org/10.1109/jiot.2022.3221930.

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33

Vaidya, Girish, Prabhakar T.V., Nithish Gnani, Ryan Shah, and Shishir Nagaraja. "A novel approach for identification of sensor devices through Acoustic PUF." Digital Threats: Research and Practice, September 24, 2021. http://dx.doi.org/10.1145/3488306.

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The supply chain traceability of components from a production facility to deployment and maintenance depends upon its irrefutable identity. There are two well-known methods for identification which includes an identity code stored in the memory and embedding a custom identification hardware. While storing the identity code is susceptible to malicious and unintentional attacks, the approach of embedding a custom identification hardware is infeasible for sensor nodes assembled with Commercially-Off-the-Shelf (COTS) devices. We propose a novel identifier - Acoustic PUF based on the innate propert

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34

Aloui, Nadia, Kosai Raoof, Ammar Bouallegue, Stephane Letourneur, and Sonia Zaibi. "Performance evaluation of an acoustic indoor localization system based on a fingerprinting technique." EURASIP Journal on Advances in Signal Processing 2014, no. 1 (2014). http://dx.doi.org/10.1186/1687-6180-2014-13.

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35

Perera, Chatumal, Sharada Amarakoon, Dulaj Weerakoon, Roshan Godaliyadda, and Parakrama Ekanayake. "ENHANCED FEATURE SPACE CLUSTERING VIA SPECTRAL PARAMETER WEIGHTING FOR ACOUSTIC FINGERPRINTING BASED INDOOR LOCALIZATION." Control and Intelligent Systems 44, no. 3 (2016). http://dx.doi.org/10.2316/journal.201.2016.3.201-2757.

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36

Izquierdo-López, Raúl, Rajveer Fandan, Alberto Boscá, Fernando Calle, and Jorge Pedrós. "Surface-acoustic-wave-driven graphene plasmonic sensor for fingerprinting ultrathin biolayers down to the monolayer limit." Biosensors and Bioelectronics, June 2023, 115498. http://dx.doi.org/10.1016/j.bios.2023.115498.

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37

Wearn, Oliver R., Hoang Trinh-Dinh, Chang-Yong Ma, et al. "Vocal fingerprinting reveals a substantially smaller global population of the Critically Endangered cao vit gibbon (Nomascus nasutus) than previously thought." Scientific Reports 14, no. 1 (2024). http://dx.doi.org/10.1038/s41598-023-50838-2.

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AbstractThe cao vit gibbon (Nomascus nasutus) is one of the rarest primates on Earth and now only survives in a single forest patch of less than 5000 ha on the Vietnam–China border. Accurate monitoring of the last remaining population is critical to inform ongoing conservation interventions and track conservation success over time. However, traditional methods for monitoring gibbons, involving triangulation of groups from their songs, are inherently subjective and likely subject to considerable measurement errors. To overcome this, we aimed to use ‘vocal fingerprinting’ to distinguish the diff

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38

Chen, Liang, Liyi Xiong, Fang Zhao, Yanfei Ju, and An Jin. "Research on blind source separation of operation sounds of metro power transformer through an Adaptive Threshold REPET algorithm." Railway Sciences, August 20, 2024. http://dx.doi.org/10.1108/rs-07-2024-0026.

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PurposeThe safe operation of the metro power transformer directly relates to the safety and efficiency of the entire metro system. Through voiceprint technology, the sounds emitted by the transformer can be monitored in real-time, thereby achieving real-time monitoring of the transformer’s operational status. However, the environment surrounding power transformers is filled with various interfering sounds that intertwine with both the normal operational voiceprints and faulty voiceprints of the transformer, severely impacting the accuracy and reliability of voiceprint identification. Therefore

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39

Bo, Sun, Tan Bo, Wang Wenbo, and Lohan Elena-Simona. "A Comparative Study of 3D UE Positioning in 5G New Radio with a Single Station." February 8, 2021. https://doi.org/10.3390/s21041178.

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Sensors (ISSN 1424-8220; CODEN: SENSC9) is the leading international peer-reviewed open access journal on the science and technology of sensors. Sensors is published semimonthly online by MDPI. The Polish Society of Applied Electromagnetics (PTZE) and Japan Society of Photogrammetry and Remote Sensing (JSPRS) are affiliated with Sensors and their members receive a discount on the article processing charges. <strong>Citation</strong>: 1. Ruotsalainen, L.; Kirkko-Jaakkola, M.; Rantanen, J.; Mäkelä, M. Error Modeling for M

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