24.1.14 Acoustic Signals, Sounds

Lopes, P.A.C., Gerald, J.A.B.,
A Close to Optimal Adaptive Filter for Sudden System Changes,
SPLetters(24), No. 11, November 2017, pp. 1734-1738.
IEEE DOI 1710
Adaptation models, Approximation algorithms, Mathematical model, Noise measurement, Probability density function, Gaussian sum, Kalman filter (KF), impulsive noise, least mean squares (LMS), optimal filtering, sudden changes, variable, step, size BibRef

Jancovic, P., Kokuer, M.,
Acoustic Recognition of Multiple Bird Species Based on Penalized Maximum Likelihood,
SPLetters(22), No. 10, October 2015, pp. 1585-1589.
IEEE DOI 1506
Markov processes BibRef

Han, T.J.[Taek-Jin], Kim, K.J.[Ki-Jun], Park, H.[Hochong],
Location Estimation of Predominant Sound Source with Embedded Source Separation in Amplitude-Panned Stereo Signal,
SPLetters(22), No. 10, October 2015, pp. 1685-1688.
IEEE DOI 1506
audio signal processing BibRef

Comminiello, D., Cecchi, S., Scarpiniti, M., Gasparini, M., Romoli, L., Piazza, F., Uncini, A.,
Intelligent Acoustic Interfaces With Multisensor Acquisition for Immersive Reproduction,
MultMed(17), No. 8, August 2015, pp. 1262-1272.
IEEE DOI 1506
Acoustics BibRef

Yao, S.S.[Shan-Shan], Wang, Y.S.[Yun-Sheng], Niu, B.[Baoning],
An Efficient Cascaded Filtering Retrieval Method for Big Audio Data,
MultMed(17), No. 9, September 2015, pp. 1450-1459.
IEEE DOI 1509
Internet BibRef

Foggia, P.[Pasquale], Petkov, N.[Nicolai], Saggese, A.[Alessia], Strisciuglio, N.[Nicola], Vento, M.[Mario],
Reliable detection of audio events in highly noisy environments,
PRL(65), No. 1, 2015, pp. 22-28.
Elsevier DOI 1511
BibRef
Earlier: A1, A3, A4, A5, Only:
Cascade classifiers trained on gammatonegrams for reliably detecting audio events,
AVSS14(50-55)
IEEE DOI 1411
Audio surveillance. Auditory system BibRef

Foggia, P., Saggese, A., Strisciuglio, N., Vento, M., Petkov, N.,
Car crashes detection by audio analysis in crowded roads,
AVSS15(1-6)
IEEE DOI 1511
audio signal processing BibRef

Saggese, A.[Alessia], Strisciuglio, N.[Nicola], Vento, M.[Mario], Petkov, N.[Nicolai],
Time-frequency analysis for audio event detection in real scenarios,
AVSS16(438-443)
IEEE DOI 1611
Event detection BibRef

Beltrán, J.[Jessica], Chávez, E.[Edgar], Favela, J.[Jesús],
Scalable identification of mixed environmental sounds, recorded from heterogeneous sources,
PRL(68, Part 1), No. 1, 2015, pp. 153-160.
Elsevier DOI 1512
Sound event classification BibRef

Zhong, Z.[Zhang], Suzuki, J., Miyake, T., Kondou, H., Enastu, K.,
Study on water leak detection using wavelet instantaneous cross-correlation,
ICWAPR15(133-137)
IEEE DOI 1511
acoustic signal processing BibRef

Kelly, D., Caulfield, B.,
Pervasive Sound Sensing: A Weakly Supervised Training Approach,
Cyber(46), No. 1, January 2016, pp. 123-135.
IEEE DOI 1601
Feature extraction BibRef

Zheng, C., Hofmann, C., Li, X., Kellermann, W.,
Analysis of Additional Stable Gain by Frequency Shifting for Acoustic Feedback Suppression using Statistical Room Acoustics,
SPLetters(23), No. 1, January 2016, pp. 159-163.
IEEE DOI 1601
Acoustics BibRef

Trevino, J.[Jorge], Sakamoto, S.[Shuichi], Li, J.[Junfeng], Suzuki, Y.[Yôiti],
Enhancing Stereo Signals with High-Order Ambisonics Spatial Information,
IEICE(E99-D), No. 1, January 2016, pp. 41-49.
WWW Link. 1601
BibRef

Ávila, F.R., Carvalho, H.T., Biscainho, L.W.P.,
Bayesian Blind Identification of Nonlinear Distortion with Memory for Audio Applications,
SPLetters(23), No. 4, April 2016, pp. 414-418.
IEEE DOI 1604
Bayes methods BibRef

Ávila, F.R., Duarte, L.T., Biscainho, L.W.P.,
On the Sparsity-Based Identification and Compensation of Hammerstein Systems,
SPLetters(24), No. 9, September 2017, pp. 1363-1367.
IEEE DOI 1708
Analytical models, Frequency-domain analysis, Linear systems, Nonlinear distortion, Nonlinear systems, Blind system identification, Hammerstein systems, sparse, signal, processing BibRef

Parseihian, G., Gondre, C., Aramaki, M., Ystad, S., Kronland-Martinet, R.,
Comparison and Evaluation of Sonification Strategies for Guidance Tasks,
MultMed(18), No. 4, April 2016, pp. 674-686.
IEEE DOI 1604
Auditory displays BibRef

Luo, D., Sun, M., Huang, J.,
Audio Postprocessing Detection Based on Amplitude Cooccurrence Vector Feature,
SPLetters(23), No. 5, May 2016, pp. 688-692.
IEEE DOI 1604
Authentication BibRef

Valero, M.L.[M. Luis], Mabande, E., Habets, E.A.P.[E. A. P.],
An Alternative Complexity Reduction Method for Partitioned-Block Frequency-Domain Adaptive Filters,
SPLetters(23), No. 5, May 2016, pp. 668-672.
IEEE DOI 1604
Acoustics BibRef

Tuma, M.[Matthias], Rørbech, V., Prior, M.K.[Mark K.], Igel, C.[Christian],
Integrated Optimization of Long-Range Underwater Signal Detection, Feature Extraction, and Classification for Nuclear Treaty Monitoring,
GeoRS(54), No. 6, June 2016, pp. 3649-3659.
IEEE DOI 1606
BibRef
Earlier: A1, A4, A3, Only:
Hydroacoustic Signal Classification Using Kernel Functions for Variable Feature Sets,
ICPR10(1011-1014).
IEEE DOI 1008
feature extraction BibRef

Lin, X., Liu, J., Kang, X.,
Audio Recapture Detection With Convolutional Neural Networks,
MultMed(18), No. 8, August 2016, pp. 1480-1487.
IEEE DOI 1608
audio recording BibRef

Na, Y., Guo, Y., Fu, Q., Yan, Y.,
Cross Array and Rank-1 MUSIC Algorithm for Acoustic Highway Lane Detection,
ITS(17), No. 9, September 2016, pp. 2502-2514.
IEEE DOI 1609
Acoustics BibRef

Lee, H., Kim, G., Kim, H.G., Oh, S.H., Lee, S.Y.,
Deep CNNs Along the Time Axis With Intermap Pooling for Robustness to Spectral Variations,
SPLetters(23), No. 10, October 2016, pp. 1310-1314.
IEEE DOI 1610
acoustic signal processing BibRef

Salvati, D., Drioli, C., Foresti, G.L.,
Sound Source and Microphone Localization From Acoustic Impulse Responses,
SPLetters(23), No. 10, October 2016, pp. 1459-1463.
IEEE DOI 1610
acoustic generators BibRef

Huang, W.[Wei], Wang, D.[Delin], Ratilal, P.[Purnima],
Diel and Spatial Dependence of Humpback Song and Non-Song Vocalizations in Fish Spawning Ground,
RS(8), No. 9, 2016, pp. 712.
DOI Link 1610
BibRef

Wang, D.[Delin], Huang, W.[Wei], Garcia, H.[Heriberto], Ratilal, P.[Purnima],
Vocalization Source Level Distributions and Pulse Compression Gains of Diverse Baleen Whale Species in the Gulf of Maine,
RS(8), No. 11, 2016, pp. 881.
DOI Link 1612
BibRef

Ren, J., Jiang, X., Yuan, J., Magnenat-Thalmann, N.,
Sound-Event Classification Using Robust Texture Features for Robot Hearing,
MultMed(19), No. 3, March 2017, pp. 447-458.
IEEE DOI 1702
Auditory system BibRef

Salamon, J., Bello, J.P.,
Deep Convolutional Neural Networks and Data Augmentation for Environmental Sound Classification,
SPLetters(24), No. 3, March 2017, pp. 279-283.
IEEE DOI 1702
Convolution BibRef

Nanni, L., Costa, Y.M.G., Lucio, D.R., Silla, Jr., C.N., Brahnam, S.,
Combining visual and acoustic features for audio classification tasks,
PRL(88), No. 1, 2017, pp. 49-56.
Elsevier DOI 1703
Audio classification BibRef

Plinge, A.[Axel], Fink, G.A.[Gernot A.], Gannot, S.,
Passive Online Geometry Calibration of Acoustic Sensor Networks,
SPLetters(24), No. 3, March 2017, pp. 324-328.
IEEE DOI 1702
Acoustic sensors BibRef

Grzeszick, R.[Rene], Plinge, A.[Axel], Fink, G.A.[Gernot A.],
Temporal Acoustic Words for Online Acoustic Event Detection,
GCPR15(142-153).
Springer DOI 1511
BibRef

Bernardini, A., d'Aria, M., Sannino, R., Sarti, A.,
Efficient Continuous Beam Steering for Planar Arrays of Differential Microphones,
SPLetters(24), No. 6, June 2017, pp. 794-798.
IEEE DOI 1705
Acoustic beams, Array signal processing, Microphone arrays, Shape, Structural beams, Beam steering, differential, microphone, arrays BibRef

Bilbao, S., Esqueda, F., Parker, J.D., Välimäki, V.,
Antiderivative Antialiasing for Memoryless Nonlinearities,
SPLetters(24), No. 7, July 2017, pp. 1049-1053.
IEEE DOI 1706
audio signal processing, nonlinear functions, signal sampling, aliasing reduction method, antiderivative antialiasing, audio signal processing, discrete-time memoryless nonlinearities, discrete-time modeling, higher order antiderivatives, nonlinear analog systems, nonlinear function, oversampled rate, signal-to-noise ratio, Distortion, Harmonic analysis, Integral equations, Signal processing algorithms, Signal to noise ratio, Aliasing, harmonic distortion, nonlinear systems, signal denoising, signal, processing, algorithms BibRef

Krishnan, L., Betlehem, T., Teal, P.D.,
A Statistically Robust Approach to Acoustic Impulse Response Shaping,
SPLetters(24), No. 8, August 2017, pp. 1138-1142.
IEEE DOI 1708
acoustic signal processing, architectural acoustics, filtering theory, humidity, probability, reverberation, statistical analysis, stochastic processes, acoustic impulse response Shaping, channel variations stochastic model, BibRef

Yao, S., Niu, B., Liu, J.,
Audio Identification by Sampling Sub-fingerprints and Counting Matches,
MultMed(19), No. 9, September 2017, pp. 1984-1995.
IEEE DOI 1708
Acoustic distortion, Filtering, Fingerprint recognition, Indexes, Robustness, Audio fingerprint, audio retrieval, dynamic threshold, inverted index, multi-granularity, filter BibRef

Ramos, G., Cobos, M., Bank, B., Belloch, J.A.,
A Parallel Approach to HRTF Approximation and Interpolation Based on a Parametric Filter Model,
SPLetters(24), No. 10, October 2017, pp. 1507-1511.
IEEE DOI 1710
approximation theory, audio signal processing, filtering theory, BibRef

Rämö, J., Bech, S., Jensen, S.H.,
Real-Time Perceptual Model for Distraction in Interfering Audio-on-Audio Scenarios,
SPLetters(24), No. 10, October 2017, pp. 1448-1452.
IEEE DOI 1710
audio systems, mean square error methods, adaptive sound-zone systems, computational efficiency, BibRef

Cassier, M.[Maxence], Vasquez, F.G.[Fernando Guevara],
Imaging Polarizable Dipoles,
SIIMS(10), No. 3, 2017, pp. 1381-1415.
DOI Link 1710
BibRef

Cao, J., Wang, W., Wang, J., Wang, R.,
Excavation Equipment Recognition Based on Novel Acoustic Statistical Features,
Cyber(47), No. 12, December 2017, pp. 4392-4404.
IEEE DOI 1712
Acoustics, Engines, Monitoring, Performance evaluation, Pipelines, Support vector machines, Vehicles, Acoustic statistical feature, extreme learning machine BibRef

Kovács, G.[György], Tóth, L.[László], Van Compernolle, D.[Dirk], Ganapathy, S.[Sriram],
Increasing the robustness of CNN acoustic models using autoregressive moving average spectrogram features and channel dropout,
PRL(100), No. 1, 2017, pp. 44-50.
Elsevier DOI 1712
Convolutional neural network BibRef

Jing, L., Liu, B., Choi, J., Janin, A., Bernd, J., Mahoney, M.W., Friedland, G.,
DCAR: A Discriminative and Compact Audio Representation for Audio Processing,
MultMed(19), No. 12, December 2017, pp. 2637-2650.
IEEE DOI 1712
Covariance matrices, Event detection, Feature extraction, Gaussian mixture model, Manifolds, event detection BibRef

Ueno, N., Koyama, S., Saruwatari, H.,
Sound Field Recording Using Distributed Microphones Based on Harmonic Analysis of Infinite Order,
SPLetters(25), No. 1, January 2018, pp. 135-139.
IEEE DOI 1801
acoustic signal processing, audio recording, harmonic analysis, microphone arrays, numerical analysis, arbitrary array geometry, sound field reproduction BibRef

Nathwani, K., Vincent, E., Illina, I.,
DNN Uncertainty Propagation Using GMM-Derived Uncertainty Features for Noise Robust ASR,
SPLetters(25), No. 3, March 2018, pp. 338-342.
IEEE DOI 1802
Acoustics, Computational modeling, Maximum likelihood decoding, Noise measurement, Training, Uncertainty, DNN acoustic model, uncertainty decoding BibRef

Hashemgeloogerdi, S., Bocko, M.F.,
Inherently Stable Weighted Least-Squares Estimation of Common Acoustical Poles With the Application in Feedback Path Modeling Utilizing a Kautz Filter,
SPLetters(25), No. 3, March 2018, pp. 368-372.
IEEE DOI 1802
Acoustics, Adaptation models, Computational modeling, Estimation, Signal processing algorithms, Stability analysis, weighted least-squares (WLS) estimation BibRef

Peddinti, V., Wang, Y., Povey, D., Khudanpur, S.,
Low Latency Acoustic Modeling Using Temporal Convolution and LSTMs,
SPLetters(25), No. 3, March 2018, pp. 373-377.
IEEE DOI 1802
Acoustics, Computational modeling, Context, Context modeling, Convolution, Neural networks, Switches, Acoustic model, time-delay neural networks BibRef

Nanni, L.[Loris], Aguiar, R.L.[Rafael L.], Costa, Y.M.G.[Yandre M.G.], Brahnam, S.[Sheryl], Silla Jr., C.N.[Carlos N.], Brattin, R.L.[Ricky L.], Zhao, Z.[Zhao],
Bird and whale species identification using sound images,
IET-CV(12), No. 2, March 2018, pp. 178-184.
DOI Link 1804
BibRef

Roshan, A.[Aditya], Zhang, Y.[Yun],
Using mel-frequency audio features from footstep sound and spatial segmentation techniques to improve frame-based moving object detection,
IET-CV(12), No. 3, April 2018, pp. 341-349.
DOI Link 1804
BibRef

Pérez-Solano, J.J., Cobos, M., Segura, J., Felici-Castell, S.,
On the Design of Probe Signals in Wireless Acoustic Sensor Networks Self-Positioning Algorithms,
SPLetters(25), No. 4, April 2018, pp. 566-570.
IEEE DOI 1804
acoustic signal processing, acoustic transducers, audio signal processing, wireless sensor networks, wireless acoustic sensor networks BibRef

Vasundhara, Panda, G.[Ganapati], Puhan, N.B.,
A new evolving-update-based feedback cancellation scheme for hearing aids,
SIViP(12), No. 4, May 2018, pp. 731-738.
WWW Link. 1805
BibRef

Xia, X.J.[Xian-Jun], Togneri, R.[Roberto], Sohel, F.[Ferdous], Huang, D.[David],
Random forest classification based acoustic event detection utilizing contextual-information and bottleneck features,
PR(81), 2018, pp. 1-13.
Elsevier DOI 1806
Acoustic event detection, Contextual information, Global bottleneck features, Category-specific bottleneck features BibRef

Ureña, J., Hernández, Á., García, J.J., Villadangos, J.M., Pérez, M.C.[M. Carmen], Gualda, D., Álvarez, F.J., Aguilera, T.,
Acoustic Local Positioning With Encoded Emission Beacons,
PIEEE(106), No. 6, June 2018, pp. 1042-1062.
IEEE DOI 1806
Acoustic measurements, Acoustics, Magnetic fields, Magnetoacoustic effects, Radio frequency, Receivers, ultrasonic signals BibRef

Zhu, M., Shahnawaz, M., Tubaro, S., Sarti, A.,
HRTF personalization based on weighted sparse representation of anthropometric features,
IC3D17(1-7)
IEEE DOI 1804
acoustic signal processing, audio signal processing, transfer functions, CIPIC database, HRTF personalization, weighted sparse representation BibRef

Joshi, G., Dandvate, C., Tiwari, H., Mundhare, A.,
Prediction of Probability of Crying of a Child and System Formation for Cry Detection and Financial Viability of the System,
ICVISP17(134-141)
IEEE DOI 1712
Algorithm design and analysis, Data models, Machine learning algorithms, Monitoring, Pediatrics, Web Application BibRef