Experiments with an extended adaptive SVD enhancement scheme for speech recognition in noise

被引：0
|
作者：
Uhl, C [1 ]
Lieb, M [1 ]
机构：
[1] Philips Res Labs, D-52066 Aachen, Germany
来源：
2001 IEEE INTERNATIONAL CONFERENCE ON ACOUSTICS, SPEECH, AND SIGNAL PROCESSING, VOLS I-VI, PROCEEDINGS: VOL I: SPEECH PROCESSING 1; VOL II: SPEECH PROCESSING 2 IND TECHNOL TRACK DESIGN & IMPLEMENTATION OF SIGNAL PROCESSING SYSTEMS NEURALNETWORKS FOR SIGNAL PROCESSING; VOL III: IMAGE & MULTIDIMENSIONAL SIGNAL PROCESSING MULTIMEDIA SIGNAL PROCESSING - VOL IV: SIGNAL PROCESSING FOR COMMUNICATIONS; VOL V: SIGNAL PROCESSING EDUCATION SENSOR ARRAY & MULTICHANNEL SIGNAL PROCESSING AUDIO & ELECTROACOUSTICS; VOL VI: SIGNAL PROCESSING THEORY & METHODS STUDENT FORUM | 2001年
关键词：
D O I：
暂无
中图分类号：
O42 [声学];
学科分类号：
070206 ; 082403 ;
摘要：
An extension to adaptive signal subspace methods is presented, based on singular value decomposition (SVD) with an online estimation of the noise variance. With this approach aiming at automatic speech recognition (ASR) in adverse environmental conditions no speech detection has to be performed. A comparison of different SVD approaches and nonlinear spectral subtraction within ASR experiments of different applications is conducted for weakly correlated noise scenarios. Better performance in the case of signal subspace speech enhancement with respect to both accuracy as well as robustness of parameter tuning are reported.
引用
收藏
页码：281 / 284
页数：4
相关论文
共 50 条
  • [21] Noise adaptive speech recognition based on sequential noise parameter estimation
    Yao, KS
    Paliwal, KK
    Nakamura, S
    SPEECH COMMUNICATION, 2004, 42 (01) : 5 - 23
  • [22] Noise Robust Exemplar Matching for Speech Enhancement: Applications to Automatic Speech Recognition
    Yilmaz, Emre
    Baby, Deepak
    Van Hannne, Hugo
    16TH ANNUAL CONFERENCE OF THE INTERNATIONAL SPEECH COMMUNICATION ASSOCIATION (INTERSPEECH 2015), VOLS 1-5, 2015, : 688 - 692
  • [23] Assessment of signal subspace based speech enhancement for noise robust speech recognition
    Hermus, K
    Wambacq, P
    2004 IEEE INTERNATIONAL CONFERENCE ON ACOUSTICS, SPEECH, AND SIGNAL PROCESSING, VOL I, PROCEEDINGS: SPEECH PROCESSING, 2004, : 945 - 948
  • [24] Bayesian Feature Enhancement for Reverberation and Noise Robust Speech Recognition
    Leutnant, Volker
    Krueger, Alexander
    Haeb-Umbach, Reinhold
    IEEE TRANSACTIONS ON AUDIO SPEECH AND LANGUAGE PROCESSING, 2013, 21 (08): : 1640 - 1652
  • [25] Noise adaptive speech intelligibility enhancement based on improved StarGAN
    Zhao, Lanxin
    Li, Dengshi
    Xiao, Jing
    Zhu, Chenyi
    2023 IEEE INTERNATIONAL CONFERENCE ON MULTIMEDIA AND EXPO, ICME, 2023, : 1313 - 1318
  • [26] Research of Speech Enhancement Based on Adaptive Noise Cancellation Methods
    Lin, Cai
    MATERIAL SCIENCE, CIVIL ENGINEERING AND ARCHITECTURE SCIENCE, MECHANICAL ENGINEERING AND MANUFACTURING TECHNOLOGY II, 2014, 651-653 : 2368 - 2371
  • [27] Adaptive noise spectral estimation for spectral subtraction speech enhancement
    Hu, H. T.
    Yu, C.
    IET SIGNAL PROCESSING, 2007, 1 (03) : 156 - 163
  • [28] Adaptive speech enhancement based on wavelet in high noise environment
    Zhu, Y
    Li, XY
    Zhang, RB
    2002 INTERNATIONAL CONFERENCE ON MACHINE LEARNING AND CYBERNETICS, VOLS 1-4, PROCEEDINGS, 2002, : 885 - 889
  • [29] Noise Adaptive Speech Enhancement using Domain Adversarial Training
    Liao, Chien-Feng
    Tsao, Yu
    Lee, Hung-Yi
    Wang, Hsin-Min
    INTERSPEECH 2019, 2019, : 3148 - 3152
  • [30] An adaptive Kalman filter for the enhancement of speech signals in colored noise
    Gabrea, M
    2005 WORKSHOP ON APPLICATIONS OF SIGNAL PROCESSING TO AUDIO AND ACOUSTICS (WASPAA), 2005, : 45 - 48
12345