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    NOISE in SPEECH and LANGUAGE PROCESSING

The amount of noise which anyone can bear undisturbed
stands in inverse proportion to his mental capacity”
Arthur Schopenhauer (1788 - 1860)
  1. Zhang Xiao-Lei, Wang DeLiang: A Deep Ensemble Learning Method for Monaural Speech Separation. IEEE/ACM Trans on Audio, Speech, and Language Processing, Vol. 24, no. 5, 2016, pp. 967 – 977. DOI 10.1109/TASLP.2016.2536478

  2. Chen Jitong, Wang Yuxuan, Yoho Sarah E., et al.: Large-scale training to increase speech intelligibility for hearing-impaired listeners in novel noises. J. of the Acoustical Society of America, Vol. 139, no. 5, 2016, pp. 2604 – 2612. DOI 10.1121/1.4948445

  3. Wang Zhong-Qiu, Wang DeLiang: A Joint Training Framework for Robust Automatic Speech Recognition. IEEE/ACM Trans on Audio, Speech, and Language Processing, Vol. 24, no. 4, 2016, pp. 796 – 806. DOI 10.1109/TASLP.2016.2528171

  4. Williamson D.S., Wang Yuxuan, Wang DeLiang: Complex Ratio Masking for Monaural Speech Separation. IEEE/ACM Trans on Audio, Speech, and Language Processing, Vol. 24, no. 3, 2016, pp. 483 – 492. DOI 10.1109/TASLP.2015.2512042

  5. Zhang Xiao-Lei, DeLiang Wang: Boosting Contextual Information for Deep Neural Network Based Voice Activity Detection. IEEE/ACM Trans on Audio, Speech, and Language Processing, Vol. 24, no. 2, 2016, pp. 252 – 264. DOI 10.1109/TASLP.2015.2505415

  6. Du Jun, Tu Yanhui, Dai Li-Rong, et al.: A Regression Approach to Single-Channel Speech Separation Via High-Resolution Deep Neural Networks. IEEE/ACM Trans on Audio, Speech, and Language Processing, Vol. 24, no. 8, 2016, pp. 1424 – 1437. DOI 10.1109/TASLP.2016.2558822

  7. Han Wei, Zhang Xiongwei, Min Gang, et al.: A Perceptually Motivated Approach for Speech Enhancement Based on Deep Neural Network. IEICE Trans on Fundamentals of Electronics, Communications & Computer Sciences, Vol. E99A, no. 4, 2016, pp. 835 – 838. DOI 10.1587/transfun.E99.A.835

  8. Lee Yune-Sang, Min Nam Eun, Wingfield A., et al.: Acoustic richness modulates the neural networks supporting intelligible speech processing. Hearing Research, Vol. 333, 2016, pp. 108 – 117. DOI 10.1016/j.heares.2015.12.008

  9. Evans S., McGettigan C., Agnew Zarinah K., et al.: Getting the Cocktail Party Started: Masking Effects in Speech Perception. J. of Cognitive Neuroscience, Vol. 28, no. 3, 2016, pp. 483 – 500. DOI 10.1162/jocn_a_00913

  10. Patel Vinal, George Nithin V.: Compensating acoustic feedback in feed-forward active noise control systems using spline adaptive filters. Signal Processing, Vol. 120, 2016, pp. 448 – 455. DOI 10.1016/j.sigpro.2015.10.003

  11. Gauvin H.S., De Baene W., Brass M., et al.: Conflict monitoring in speech processing: An fMRI study of error detection in speech production and perception. Neuroimage, Vol. 126, 2016, pp. 96 – 105. DOI 10.1016/j.neuroimage.2015.11.037

  12. Gholami-Boroujeny S., Fallatah A., Heffernan B.P., et al.: Neural network-based adaptive noise cancellation for enhancement of speech auditory brainstem responses. Signal Image & Video Processing, Vol. 10, no. 2, 2016, pp. 389 – 395. DOI 10.1007/s11760-015-0752-x

  13. Henry Molly J., Herrmann B., Obleser J.: Neural Microstates Govern Perception of Auditory Input without Rhythmic Structure. J. of Neuroscience, Vol. 36, no. 3, 2016, pp. 860 – 871. DOI 10.1523/JNEUROSCI.2191-15.2016

  14. Sun Meng, Zhang Xiongwei, Van hamme H., et al.: Unseen Noise Estimation Using Separable Deep Auto Encoder for Speech Enhancement. IEEE/ACM Trans on Audio, Speech, and Language Processing, Vol. 24, no. 1, 2016, pp. 93 – 104. DOI 10.1109/TASLP.2015.2498101

  15. Petkov P.N., Stylianou Y.: Adaptive Gain Control for Enhanced Speech Intelligibility Under Reverberation. IEEE Signal Processing Lett., Vol. 23, no. 10, 2016, pp. 1434 – 1438. DOI 10.1109/LSP.2016.2598807

  16. Zorilă T.C., Stylianou Y., T. Ishihara, M. Akamine: Near and Far Field Speech-in-Noise Intelligibility Improvements Based on a Time–Frequency Energy Reallocation Approach. IEEE/ACM Trans on Audio, Speech, and Language Processing, Vol. 24, no. 10, 2016, pp. 1808 – 1818. DOI 10.1109/TASLP.2016.2585864

  17. Jensen J., Taal C.H.: An Algorithm for Predicting the Intelligibility of Speech Masked by Modulated Noise Maskers. IEEE/ACM Trans on Audio, Speech, and Language Processing, Vol. 24, no. 11, 2016, pp. 2009 – 2022. DOI 10.1109/TASLP.2016.2585878

  18. Hung J.W., Hsieh H.J., Chen B.: Robust Speech Recognition via Enhancing the Complex-Valued Acoustic Spectrum in Modulation Domain. IEEE/ACM Trans on Audio, Speech, and Language Processing, Vol. 24, no. 2, 2016, pp. 236 – 251. DOI 10.1109/TASLP.2015.2504781

  19. Tavares R., Coelho R.: Speech Enhancement with Nonstationary Acoustic Noise Detection in Time Domain. IEEE Signal Processing Lett., Vol. 23, no. 1, 2016, pp. 6 – 10. DOI 10.1109/LSP.2015.2495102

  20. Gupta D., Bansal P., Choudhary K.: Noise robust acoustic signal processing using a Hybrid approach for speech recognition. Int. Conf. - Cloud System and Big Data Engineering (Confluence), 2016, pp. 489 – 492. DOI 10.1109/CONFLUENCE.2016.7508169

  21. Baby Deepak, Virtanen T., Gemmeke J.F., et al.: Coupled Dictionaries for Exemplar-Based Speech Enhancement and Automatic Speech Recognition. IEEE/ACM Trans on Audio, Speech, and Language Processing, Vol. 23, no. 11, 2015, pp. 1788 – 1799. DOI 10.1109/TASLP.2015.2450491

  22. Chen Zhangli, Hohmann Volker: Online Monaural Speech Enhancement Based on Periodicity Analysis and A Priori SNR Estimation. IEEE/ACM Trans on Audio, Speech, and Language Processing, Vol. 23, no. 11, 2015, pp. 1904 – 1916. DOI 10.1109/TASLP.2015.2456423

  23. Weng Chao, Yu Dong, Seltzer M.L., et al.: Deep Neural Networks for Single-Channel Multi-Talker Speech Recognition. IEEE/ACM Trans on Audio, Speech, and Language Processing, Vol. 23, no. 10, 2015, pp. 1670 – 1679. DOI 10.1109/TASLP.2015.2444659

  24. Williamson D.S., Wang Yuxuan, Wang DeLiang: Estimating nonnegative matrix model activations with deep neural networks to increase perceptual speech quality. J. of the Acoustical Society of America, Vol. 138, no. 3, 2015, pp. 1399 – 1407. DOI 10.1121/1.4928612

  25. Healy E.W., Yoho S.E., Chen Jitong, et al.: An algorithm to increase speech intelligibility for hearing-impaired listeners in novel segments of the same noise type. J. of the Acoustical Society of America, Vol. 138, no. 3, 2015, pp. 1660 – 1669. DOI 10.1121/1.4929493

  26. Delcroix M., Yoshioka Takuya, Ogawa Atsunori, et al.: Strategies for distant speech recognition in reverberant environments. EURASIP Journal on Advances in Signal Processing, 2015, Article # 60. DOI 10.1186/s13634-015-0245-7

  27. Xia Youshen, Wang Jun: Low-dimensional recurrent neural network-based Kalman filter for speech enhancement. Neural Networks, Vol. 67, 2015, pp. 131 – 139. DOI http://dx.doi.org/10.1016/j.neunet.2015.03.008

  28. Zaatri A., Azzizi N., Rahmani F.L.: Voice Recognition Technology Using Neural Networks. J. of New Technology and Materials, Vol. 5, no. 1, 2015, pp. 27 – 31.

  29. Gibak Kim: Binary mask estimation for noise reduction based on instantaneous SNR estimation using Bayes risk minimisation. Electronics Lett., Vol. 51, no. 6, 2015, pp. 526 – 528. DOI 10.1049/el.2014.4242

  30. Renjie Tong, Guangzhao Bao, Zhongfu Ye: A Higher Order Subspace Algorithm for Multichannel Speech Enhancement. IEEE Signal Processing Lett., Vol. 22, no. 11, 2015, pp. 2004 – 2008. DOI 10.1109/LSP.2015.2453205

  31. Kisoo Kwon, Jong Won Shin, Nam Soo Kim: NMF-Based Speech Enhancement Using Bases Update. IEEE Signal Processing Lett., Vol. 22, no. 4, 2015, pp. 450 – 454. DOI 10.1109/LSP.2014.2362556

  32. Yousefian N., Hansen J.H.L., Loizou P.C.: A Hybrid Coherence Model for Noise Reduction in Reverberant Environments. IEEE Signal Processing Lett., Vol. 22, no. 3, 2015, pp. 279 – 282. DOI 10.1109/LSP.2014.2352352

  33. Wei Xue, Wenju Liu, Shan Liang: Noise Robust Direction of Arrival Estimation for Speech Source With Weighted Bispectrum Spatial Correlation Matrix. IEEE Journal of Selected Topics in Signal Processing, Vol. 9, no. 5, 2015, pp. 837 – 851. DOI 10.1109/JSTSP.2015.2416686

  34. Shin H.S., Fingscheidt T., Kang H.G.: A Priori SNR Estimation Using Air- and Bone-Conduction Microphones. IEEE/ACM Trans on Audio, Speech, and Language Processing, Vol. 23, no. 11, 2015, pp. 2015 – 2025. DOI 10.1109/TASLP.2015.2446202

  35. Hendriks R.C., Crespo J.B., Jensen J., Taal C.H.: Optimal Near-End Speech Intelligibility Improvement Incorporating Additive Noise and Late Reverberation Under an Approximation of the Short-Time SII. IEEE/ACM Trans on Audio, Speech, and Language Processing, Vol. 23, no. 5, 2015, pp. 851 – 862. DOI 10.1109/TASLP.2015.2409780

  36. Deng F., Bao C., Kleijn W.B.: Sparse Hidden Markov Models for Speech Enhancement in Non-Stationary Noise Environments. IEEE/ACM Trans on Audio, Speech, and Language Processing, Vol. 23, no. 11, 2015, pp. 1973 – 1987. DOI 10.1109/TASLP.2015.2458585

  37. Mai V.K., Pastor D., Aïssa-El-Bey A., Le-Bidan R.: Robust Estimation of Non-Stationary Noise Power Spectrum for Speech Enhancement. IEEE/ACM Trans on Audio, Speech, and Language Processing, Vol. 23, no. 4, 2015, pp. 670 – 682. DOI 10.1109/TASLP.2015.2401426

  38. Schwartz O., Gannot S., Habets E.A.P.: Multi-Microphone Speech Dereverberation and Noise Reduction Using Relative Early Transfer Functions. IEEE/ACM Trans on Audio, Speech, and Language Processing, Vol. 23, no. 2, 2015, pp. 240 – 251. DOI 10.1109/TASLP.2014.2372335

  39. Schasse A., Gerkmann T., Martin R., Sörgel W., Pilgrim T., Puder H.: Two-Stage Filter-Bank System for Improved Single-Channel Noise Reduction in Hearing Aids. IEEE/ACM Trans on Audio, Speech, and Language Processing, Vol. 23, no. 2, 2015, pp. 383 – 393. DOI 10.1109/TASLP.2014.2365992

  40. Gerkmann T., Krawczyk-Becker M., Le Roux J.: Phase Processing for Single-Channel Speech Enhancement: History and recent advances. IEEE Signal Processing Magazine, Vol. 32, no. 2, 2015, pp. 55 – 66. DOI 10.1109/MSP.2014.2369251

  41. Koning R., Madhu N., Wouters J.: Ideal Time–Frequency Masking Algorithms Lead to Different Speech Intelligibility and Quality in Normal-Hearing and Cochlear Implant Listeners. IEEE Trans on Biomedical Eng., Vol. 62, no. 1, 2015, pp. 331 – 341. DOI 10.1109/TBME.2014.2351854

  42. Kleijn W.B., Hendriks R.C.: A Simple Model of Speech Communication and its Application to Intelligibility Enhancement. IEEE Signal Processing Lett., Vol. 22, no. 3, 2015, pp. 303 – 307. DOI 10.1109/LSP.2014.2351784

  43. Zendel B.R., Tremblay C.D., Belleville S., Peretz I.: The Impact of Musicianship on the Cortical Mechanisms Related to Separating Speech from Background Noise. J. of Cognitive Neuroscience, Vol. 27, no. 5, 2015, pp. 1044 – 1059. DOI 10.1162/jocn_a_00758

  44. Lim H., Yoo I.C., Cho Y., Yook D.: Speaker localization in noisy environments using steered response voice power. IEEE Trans on Consumer Electronics, Vol. 61, no. 1, 2015, pp. 112 – 118. DOI 10.1109/TCE.2015.7064118

  45. Schasse A., Martin R.: Estimation of Subband Speech Correlations for Noise Reduction via MVDR Processing. IEEE/ACM Trans on Audio, Speech, and Language Processing, vol. 22, no. 9, 2014, pp. 1355 – 1365. DOI 10.1109/TASLP.2014.2329633

  46. Biho Kim, Yunil Hwang, Hyung-Min Park: Speech enhancement based on softmasking exploiting both output SNR and selectivity of spatial filtering. Electronics Lett., Vol. 50, no. 12, 2014, pp. 889 – 891. DOI 10.1049/el.2014.0416

  47. Erro D., Sainz I., Navas E., Hernaez I.: Harmonics Plus Noise Model Based Vocoder for Statistical Parametric Speech Synthesis. IEEE Journal of Selected Topics in Signal Processing, Vol. 8, no. 2, 2014, pp. 184 – 194. DOI 10.1109/JSTSP.2013.2283471

  48. Karhila R., Remes U., Kurimo M.: Noise in HMM-Based Speech Synthesis Adaptation: Analysis, Evaluation Methods and Experiments. IEEE Journal of Selected Topics in Signal Processing, Vol. 8, no. 2, 2014, pp. 285 – 295. DOI 10.1109/JSTSP.2013.2278492

  49. Jihwan Park, Joon-Hyuk Chang: Frequency-Domain Volterra Filter Based on Data-Driven Soft Decision for Nonlinear Acoustic Echo Suppression. IEEE Signal Processing Lett., Vol. 21, no. 9, 2014, pp. 1088 – 1092. DOI 10.1109/LSP.2014.2325644

  50. Benxu Liu, Reju V.G., Khong A.W.H., Reddy V.V.: A GMM Post-Filter for Residual Crosstalk Suppression in Blind Source Separation. IEEE Signal Processing Lett., Vol. 21, no. 8, 2014, pp. 942 – 946. DOI 10.1109/LSP.2014.2317761

  51. Yi Jiang, DeLiang Wang, RunSheng Liu, et al.: Binaural Classification for Reverberant Speech Segregation Using Deep Neural Networks. IEEE/ACM Trans on Audio, Speech, and Language Processing, Vol. 22, no. 12, 2014, pp. 2112 – 2121. DOI 10.1109/TASLP.2014.2361023

  52. Kun Han, DeLiang Wang: Neural Network Based Pitch Tracking in Very Noisy Speech. IEEE/ACM Trans on Audio, Speech, and Language Processing, Vol. 22, no. 12, 2014, pp. 2158 – 2168. DOI 10.1109/TASLP.2014.2363410

  53. Wang Yuxuan, Narayanan Arun, DeLiang Wang: On Training Targets for Supervised Speech Separation. IEEE/ACM Trans on Audio, Speech, and Language Processing, Vol. 22, no. 12, 2014, pp. 1849 – 1858. DOI 10.1109/TASLP.2014.2352935

  54. Schwerin B., Paliwal K.: An improved speech transmission index for intelligibility prediction. Speech Communication, Vol. 65, 2014, pp. 9 – 19. DOI 10.1016/j.specom.2014.05.003

  55. Kates J.M., Arehart K.H.: The Hearing-Aid Speech Perception Index (HASPI). Speech Communication, Vol. 65, 2014, pp. 75 – 93. DOI 10.1016/j.specom.2014.06.002

  56. Ives D. T., Kalluri S., Strelcyk O., et al.: Effects of Noise Reduction on AM Perception for Hearing-Impaired Listeners. JARO – Journal of the Association for Research in Otolaryngology, Vol. 15, no. 5, 2014, pp. 839 – 848. DOI 10.1007/s10162-014-0466-8

  57. Moore D. R., Edmondson-Jones M., Dawes P. et al.: Relation between Speech-in-Noise Threshold, Hearing Loss and Cognition from 40-69 Years of Age. PLoS One, Vol. 9, no. 9, 2014, Article # e107720. DOI 10.1371/journal.pone.0107720

  58. Smeds K., Leijon A., Wolters F., Hammarstedt A., Basjo S., Hertzman S.: Comparison of predictive measures of speech recognition after noise reduction processing. Journal of the Acoustical Society of America, Vol. 136, no. 3, 2014, pp. 1363 – 1374. DOI 10.1121/1.4892766

  59. Neher T., Grimm G., Hohmann V.: Perceptual Consequences of Different Signal Changes Due to Binaural Noise Reduction: Do Hearing Loss and Working Memory Capacity Play a Role? Ear and Hearing, Vol. 35, no. 5, 2014, pp. E213 – E227.

  60. Taal C.H., Hendriks R.C., Heusdens R.: Speech energy redistribution for intelligibility improvement in noise based on a perceptual distortion measure. Computer Speech and Language, Vol. 28, no. 4, 2014, pp. 858 – 872. DOI 10.1016/j.csl.2013.11.003

  61. Vieira M.N., Sansao J.P.H., Yehia H.C.: Measurement of signal-to-noise ratio in dysphonic voices by image processing of spectrograms. Speech Communication, Vol. 61-62, 2014, pp. 17 – 32. DOI 10.1016/j.specom.2014.04.001

  62. Thibodeau L.: Comparison of speech recognition with adaptive digital and FM remote microphone hearing assistance technology by listeners who use hearing aids. American Journal of Audiology, Vol. 23, no. 2, 2014, pp. 201 – 210. DOI 10.1044/2014_AJA-13-0065

  63. Cooper A., Brouwer S., Bradlow A.R.: Interdependent processing of speech and background noise. The Journal of the Acoustical Society of America, Vol. 135, no. 4, 2014, pp. 2421 DOI 10.1121/1.4878038

  64. Li Jinyu, Deng Li, Gong Yifan, Haeb-Umbach R.: An Overview of Noise-Robust Automatic Speech Recognition. IEEE/ACM Trans on Audio, Speech, and Language Processing, Vol. 22, no. 4, 2014, pp. 745 – 777. DOI 10.1109/TASLP.2014.2304637

  65. Costa M.H.: A complementary low-cost method for broadband noise reduction in hearing aids for medium to high SNR levels. Computers in Biology and Medicine, Vol. 46, 2014, pp. 29 – 41. DOI 10.1016/j.compbiomed.2013.12.009

  66. Yousefian N., Loizou P.C., Hansen J.H.L.: A coherence-based noise reduction algorithm for binaural hearing aids. Speech Communication, Vol. 58, 2014, pp. 101 – 110. DOI 10.1016/j.specom.2013.11.003

  67. Gonzalez S., Brookes M.: PEFAC - A Pitch Estimation Algorithm Robust to High Levels of Noise.IEEE/ACM Trans on Audio, Speech, and Language Processing, Vol. 22, no. 2, 2014, pp. 518 – 530. DOI 10.1109/TASLP.2013.2295918

  68. Lu Ching-Ta: Noise reduction using three-step gain factor and iterative-directional-median filter. Applied Acoustics, Vol. 76, 2014, pp. 249 – 261. DOI 10.1016/j.apacoust.2013.08.015

  69. McLachlan N.M., Grayden D.B.: Enhancement of speech perception in noise by periodicity processing: A neurobiological model and signal processing algorithm. Speech Communication, Vol. 57, 2014, pp. 114 – 125. DOI 10.1016/j.specom.2013.09.007

  70. Wu Dalei, Zhu Wei-Ping, Swamy M.N.S.: The Theory of Compressive Sensing Matching Pursuit Considering Time-domain Noise with Application to Speech Enhancement. IEEE/ACM Trans on Audio, Speech, and Language Processing, Vol. 22, no. 3, 2014, pp. 682 – 696. DOI 10.1109/TASLP.2014.2300336

  71. Kim Seon Man, Kim Hong Kook: Noise variance estimation based on dual-channel phase difference for speech enhancement. Digital Signal Processing, Vol. 26, 2014, pp. 169 – 182. DOI 10.1016/j.dsp.2013.11.012

  72. Moon T.K., Gunther J.H., Broadus C., Hou W., Nelson N.: Turbo Processing for Speech Recognition. IEEE Trans on Cybernetics, Vol. 44, no. 1, 2014, pp. 83 – 91. DOI 10.1109/TCYB.2013.2247593

  73. Glyde H., Cameron S., Dillon H., et al.: The Effects of Hearing Impairment and Aging on Spatial Processing. Ear and Hearing, Vol. 34, no. 1, 2013, pp. 15 – 28. DOI 10.1097/AUD.0b013e3182617f94

  74. Ooi K.E.B., Lech M., Allen N.B.: Multichannel Weighted Speech Classification System for Prediction of Major Depression in Adolescents. IEEE Trans on Biomedical Eng., Vol. 60, no. 2, 2013, pp. 497 – 506. DOI 10.1109/TBME.2012.2228646

  75. Sprechmann P., Bronstein A., Bronstein M., Sapiro G.: Learnable Low Rank Sparse Models for Speech Denoising. IEEE Int. Conf on Acoustics, Speech, and Signal Processing (ICASSP), 2013, pp. 136 – 140.

  76. Li J., Ouazzane K., Kazemian H.B., Afzal M.S.: Neural Network Approaches for Noisy Language Modeling. IEEE Trans on Neural Networks and Learning Systems, Vol. 24, no. 11, 2013, pp. 1773 – 1784. DOI 10.1109/TLS.2013.2263557

  77. Kolossa D., Zeiler S., Saeidi R., Fernandez Astudillo R.: Noise-Adaptive LDA: A New Approach for Speech Recognition Under Observation Uncertainty. IEEE Signal Processing Lett., Vol. 20, no. 11, 2013, pp. 1018 – 1021. DOI 10.1109/LSP.2013.2278556

  78. Kolossa D., Zeiler S., Saeidi R., Fernandez Astudillo R.: Noise-Adaptive LDA: A New Approach for Speech Recognition Under Observation Uncertainty. IEEE Signal Processing Lett., Vol. 20, no. 11, 2013, pp. 1018 – 1021. DOI 10.1109/LSP.2013.2278556

  79. Xugang Lu, Unoki M., Matsuda S., Hori C., Kashioka H.: Controlling Tradeoff Between Approximation Accuracy and Complexity of a Smooth Function in a Reproducing Kernel Hilbert Space for Noise Reduction. IEEE Trans on Signal Processing, Vol. 61, no. 3, 2013, pp. 601 – 610. DOI 10.1109/TSP.2012.2229991

  80. Nakagawa C.R.C., Nordholm S., Yan W.-Y.: New Insights Into Optimal Acoustic Feedback Cancellation. IEEE Signal Processing Lett., Vol. 20, no. 9, 2013, pp. 869 – 872. DOI 10.1109/LSP.2013.2271318

  81. Sarria-Paja M., Falk T.H.: Whispered Speech Detection in Noise Using Auditory-Inspired Modulation Spectrum Features. IEEE Signal Processing Lett., Vol. 20, no. 8, 2013, pp.783 – 786. DOI 10.1109/LSP.2013.2266860

  82. Szurley J., Bertrand A., Moonen M.: On the Use of Time-Domain Widely Linear Filtering for Binaural Speech Enhancement. IEEE Signal Processing Lett., Vol. 20, no. 7, 2013, pp. 649 – 652. DOI 10.1109/LSP.2013.2261058

  83. Weifeng Li, Yicong Zhou, Poh N., Fei Zhou, Qingmin Liao: Feature Denoising Using Joint Sparse Representation for In-Car Speech Recognition. IEEE Signal Processing Lett., Vol. 20, no. 7, 2013, pp. 681 – 684. DOI 10.1109/LSP.2013.2245894

  84. Carmona J.L., Barker J., Gomez A.M., Ning Ma: Speech Spectral Envelope Enhancement by HMM-Based Analysis/Resynthesis. IEEE Signal Processing Lett., Vol. 20, no. 6, 2013, pp. 563 – 566. DOI 10.1109/LSP.2013.2255125

  85. Teng P., Jia Y.: Voice Activity Detection Via Noise Reducing Using Non-Negative Sparse Coding. IEEE Signal Processing Lett., Vol. 20, no. 5, 2013, pp. 475 – 478. DOI 10.1109/LSP.2013.2252615

  86. Taal C.H., Jensen J., Leijon A.: On Optimal Linear Filtering of Speech for Near-End Listening Enhancement. IEEE Signal Processing Lett., Vol. 20, no. 3, 2013, pp. 225 – 228. DOI 10.1109/LSP.2013.2240297

  87. Li Sheng, Xue Huijun, Lu Guohua, et al.: Bioradar Non-air Conducted Speech Enhancement based on Adaptive Wavelet Packet Entropy. Journal of Pure and Applied Microbiology, Vol. 7, Special Issue: SI, 2013, pp. 263 – 268.

  88. Woodruff J., Wang D.: Binaural Localization of Multiple Sources in Reverberant and Noisy Environments. IEEE Trans. on Audio, Speech, and Language Processing, Vol. 20, no. 5, 2012, pp. 1503 – 1512. DOI 10.1109/TASL.2012.2183869

  89. Hanilci C., Kinnunen T., Ertas F., Saeidi R., Pohjalainen J., Alku P.: Regularized All-Pole Models for Speaker Verification Under Noisy Environments. IEEE Signal Processing Letters, Vol. 19, no. 3, 2012, pp. 163 – 166. DOI 10.1109/LSP.2012.2184284

  90. Yang F., Wu M., Yang J.: Stereophonic Acoustic Echo Suppression Based on Wiener Filter in the Short-Time Fourier Transform Domain. IEEE Signal Processing Letters, Vol. 19, no. 4, 2012, pp. 227 – 230. DOI 10.1109/LSP.2012.2187446

  91. D. Marelli, M. Aramaki, R. Kronland-Martinet, C. Verron : An Efficient Time–Frequency Method for Synthesizing Noisy Sounds With Short Transients and Narrow Spectral Components. IEEE Trans on Audio, Speech, and Language Processing, Vol. 20, no. 4, 2012, pp 1400 – 1408. DOI 10.1109/TASL.2011.2176334

  92. Ning Ma, Barker J., Christensen H., Green P. : Combining Speech Fragment Decoding and Adaptive Noise Floor Modeling. IEEE Trans on Audio, Speech, and Language Processing, Vol. 20, no 3, 2012, pp. 818 – 827. DOI 10.1109/TASL.2011.2165945

  93. R. Serizel, M. Moonen, J. Wouters, S. H. Jensen : A Zone-of-Quiet Based Approach to Integrated Active Noise Control and Noise Reduction for Speech Enhancement in Hearing Aids. IEEE Trans on Audio, Speech, and Language Processing, Vol. 20, no. 6, 2012, pp 1685 – 1697. DOI 10.1109/TASL.2012.2187193

  94. Bergamasco M., Della Rossa F., Piroddi L : Active noise control with on-line estimation of non-Gaussian noise characteristics. Journal of Sound and Vibration, Vol. 331, no 1, 2012, pp. 27 – 40. DOI 10.1016/j.jsv.2011.08.025

  95. Newman J.L., Cox S.J.: Language Identification Using Visual Features. IEEE Trans on Audio, Speech, and Language Processing, Vol. 20, no. 7, 2012, pp. 1936 – 1947. DOI 10.1109/TASL.2012.2191956

  96. Alves R. G., Zuluaga W. A.: Active noise cancellation (ANC) for stereo headphones using a single bluetooth chip solution. IEEE Int. Conf. on Consumer Electronics (ICCE), 2012, pp. 15 – 16. DOI 10.1109/ICCE.2012.6161716

  97. Deepa D., Prakarsha C., Shanmugam A.: Single channel speech enhancement using spectral gain shaping method and dereverberation for digital hearing aid. Int. Conf. on Computer Communication and Informatics (ICCCI), 2012, pp. 1 – 6. DOI 10.1109/ICCCI.2012.6158847

  98. Taghia J., Mohammadiha N., Jinqiu Sang, Bouse V., Martin R.: An evaluation of noise power spectral density estimation algorithms in adverse acoustic environments. IEEE Int. Conf on Acoustics, Speech and Signal Processing (ICASSP), 2011, pp 4640 – 4643. DOI 10.1109/ICASSP.2011.5947389

  99. Kim D K., Gales M.J.F.: Noisy Constrained Maximum-Likelihood Linear Regression for Noise-Robust Speech Recognition. IEEE Trans Audio, Speech, and Language Processing, Vol. 19, no 2, 2011, p. 315 – 325. DOI 10.1109/TASL.2010.2047756

  100. Breithaupt C, Martin R.: Analysis of the Decision-Directed SNR Estimator for Speech Enhancement With Respect to Low-SNR and Transient Conditions. IEEE Trans Audio, Speech, and Language Processing, Vol. 19, no 2, 2011, pp 277 – 289. DOI 10.1109/TASL.2010.2047681

  101. Suhadi S., Last C., Fingscheidt T.: A Data-Driven Approach to A Priori SNR Estimation. IEEE Trans Audio, Speech, and Language Processing, Vol. 19, no 1, 2011, pp 186 – 195. DOI 10.1109/TASL.2010.2045799

  102. Corona-Strauss F.I., Bernarding C., Latzel M., Strauss D.J.: Syllable evoked auditory late responses: Effects of noise onsets and noise types. 5th Int. IEEE/EMBS Conf. on Neural Engineering (NER), 2011, pp.140-143 DOI 10.1109/NER.2011.5910508

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