Motor Vehicle Acoustic Noise Reduction System

2012 ◽  
Vol 131 (1) ◽  
pp. 645
Author(s):  
Brett A. Campbell
1999 ◽  
Vol 105 (3) ◽  
pp. 1446
Author(s):  
Nils Eric Larson ◽  
Ajit Fathailal Sancheti

2020 ◽  
Author(s):  
Lieber Po-Hung Li ◽  
Ji-Yan Han ◽  
Wei-Zhong Zheng ◽  
Ren-Jie Huang ◽  
Ying-Hui Lai

BACKGROUND The cochlear implant technology is a well-known approach to help deaf patients hear speech again. It can improve speech intelligibility in quiet conditions; however, it still has room for improvement in noisy conditions. More recently, it has been proven that deep learning–based noise reduction (NR), such as noise classification and deep denoising autoencoder (NC+DDAE), can benefit the intelligibility performance of patients with cochlear implants compared to classical noise reduction algorithms. OBJECTIVE Following the successful implementation of the NC+DDAE model in our previous study, this study aimed to (1) propose an advanced noise reduction system using knowledge transfer technology, called NC+DDAE_T, (2) examine the proposed NC+DDAE_T noise reduction system using objective evaluations and subjective listening tests, and (3) investigate which layer substitution of the knowledge transfer technology in the NC+DDAE_T noise reduction system provides the best outcome. METHODS The knowledge transfer technology was adopted to reduce the number of parameters of the NC+DDAE_T compared with the NC+DDAE. We investigated which layer should be substituted using short-time objective intelligibility (STOI) and perceptual evaluation of speech quality (PESQ) scores, as well as t-distributed stochastic neighbor embedding to visualize the features in each model layer. Moreover, we enrolled ten cochlear implant users for listening tests to evaluate the benefits of the newly developed NC+DDAE_T. RESULTS The experimental results showed that substituting the middle layer (ie, the second layer in this study) of the noise-independent DDAE (NI-DDAE) model achieved the best performance gain regarding STOI and PESQ scores. Therefore, the parameters of layer three in the NI-DDAE were chosen to be replaced, thereby establishing the NC+DDAE_T. Both objective and listening test results showed that the proposed NC+DDAE_T noise reduction system achieved similar performances compared with the previous NC+DDAE in several noisy test conditions. However, the proposed NC+DDAE_T only needs a quarter of the number of parameters compared to the NC+DDAE. CONCLUSIONS This study demonstrated that knowledge transfer technology can help to reduce the number of parameters in an NC+DDAE while keeping similar performance rates. This suggests that the proposed NC+DDAE_T model may reduce the implementation costs of this noise reduction system and provide more benefits for cochlear implant users.


2021 ◽  
Author(s):  
Omar Lopez Rodriguez ◽  
Mohammad Saleem ◽  
Ephraim Gutmark ◽  
Junhui Liu

2005 ◽  
Vol 109 (1092) ◽  
pp. 65-74
Author(s):  
B. Timmins

Abstract This paper looks back on the designs and ambitions of ARA in resolving a long term acoustic noise problem which threatened ARA with closure. This paper today briefly looks back to the original issues but deals more fully with the later phases of a two phase project implementation and construction. ARA is now a truly ‘silent site’, where closure was once threatened, ARA has achieved the implementation of a bespoke noise reduction enclosure where 24-hour running has proved to be a reality. This paper looks at the design and construction phases, the ‘before and after’ noise footprints and at some of the financial benefits ARA has achieved. The ARA transonic wind tunnel is sited on an industrial estate on the north west perimeter of Bedford. When it was first built it was on an original farm site with no appreciable residential houses in close proximity. Since the early 1950s there has been considerable residential development around the ARA site resulting in the local householders complaining about the wind tunnel acoustic noise. In early 1999 ARA was obliged to consider several options for noise reduction measures to reduce the noise to within UK government statutory requirements. This paper deals briefly with the original noise nuisance characteristics and footprint, the noise reduction design and method that ARA selected and shows the construction phases, the further noise treatment ARA had to do on other major ancillary equipment to make ARA a truly quiet industrial site. The paper shows how ARA has utilised the resulting benefits of these investments to increase productivity and reduce costs, and the influence it has had on ARA’s financial health.


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