An automotive application of real-time adaptive Wiener filter for non-stationary noise cancellation in a car environment

Chen, Yen-Hsiang; Ruan, Shanq-Jang; Qi, Ziming

doi:10.1109/icspcc.2012.6335628

Cited by 12 publications

(8 citation statements)

References 6 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…Not to mention the state that the driver has to be always on alert and driving itself can be strenuous at times particularity if the journey is filled with traffic. Filtering the noise has been subject to numerous research [7] [8] and is improving at an increasingly steady rate. The use of the current voice recognition systems nowadays is reported to be unsafe by several sources, including the American Automobile Association [9][10].…”

Section: Voice Recognition In Car Systemsmentioning

confidence: 99%

Ambient Technology in Vehicles: The Risks and Benefits

Bennakhi¹,

Safar²

2017

(JUSPN)

View full text Add to dashboard Cite

This paper is aimed towards studying, compiling, and analyzing the recent advances and risks of the current ambient technology that is present in modern day cars. The progression of sophisticated technologies inside cars make them an even more comfortable and entertaining place to be in especially during commutes to work, but recent security threats and distractions have been uncovered with the upsurge usage of new technologies. The future of car’s interfaces is an issue since driverless cars are taking the scene by storm. This study also includes a survey that senses the people’s use of car technologies when driving.

show abstract

Section: Voice Recognition In Car Systemsmentioning

confidence: 99%

Ambient Technology in Vehicles: The Risks and Benefits

Bennakhi¹,

Safar²

2017

(JUSPN)

View full text Add to dashboard Cite

show abstract

“…The authors Yen-Hsiang Chen et al [4] implemented a realtime adaptive wiener filter with two micro phones is implemented to reduce noisy speech when noise signals and desired speech are incoming simultaneously.…”

Section: Related Workmentioning

confidence: 99%

“…One of the most successful adaptive algorithms is the LMS algorithm which is shown in figure 5. Instead of computing in Wiener-Hopf equation, the LMS coefficients are adjusted from sample to sample in such a way to minimize the MSE [4], in descending array as shown in the figure 6. The LMS algorithm is based on the steepest descent algorithm where the weight vector is updated from sample to sample as shown below equation.…”

Section: Least Mean Square (Lms) Algorithmmentioning

confidence: 99%

See 1 more Smart Citation

Removal of Different Noises in Underwater Communication

Tejaswi¹,

Sudheera²,

Chowdary³

2015

IJERT

View full text Add to dashboard Cite

Acoustic waves are the most important characteristic to convey data in underwater domain as a practical method. But the oceans are increasingly exposed to sounds from human activities, such as shipping and the building of foundations for offshore construction projects and other different noises. This work presents the capacity of wiener filter and adaptive filter for removal of noise by estimating the signal by means of removing the noise signal from the corrupted signal. This paper compares the performance of adaptive algorithms for noise cancellation in underwater communication signals with different background noises. The proposed work is simulated using MATLAB and analyzed for different inputs with different algorithms.

show abstract

“…Opportunities and challenges of parallelizing speech recognition for real-time applications is discussed in [12], wherein, one of the major challenges towards improving the accuracy of speech recognition is found to be the presence of stationary (non-stationary)noise in the input speech. Though several real-time speech recognition techniques for non-stationary noisy environments exist [13], [14] , realtime speech enhancement as a preprocessing step coupled with speech recognition can greatly improve the quality of the speech recognized.…”

Section: Related Workmentioning

confidence: 99%

Real-time codebook-based speech enhancement with GPUs

Prasanna¹,

Gurumurthy²,

Naidu³

et al. 2014

2014 International Conference on Parallel, Distributed and Grid Computing

View full text Add to dashboard Cite

The advent of ubiquitous mobile communication has posed a lot of challenges, one of the prominent being suppression of background noise, especially in non-stationary noisy environments. In literature, several speech enhancement techniques have been proposed to tackle this problem of noise reduction. Codebook-based speech enhancement (CBSE) employing trained speech and noise codebooks, is one of the most effective noise reduction technique for handling non-stationary noise. However, the high compute intensive nature of this technique renders it inapplicable in real-time speech enhancement scenarios by introducing a significant delay in speech transmission. In this paper, this problem is addressed by providing an efficient, parallel CBSE algorithm. The proposed parallel CBSE algorithm achieves significant speedup and reduced execution time, resulting in a speech transmission delay which is well within the limits of realizing real-time speech enhancement. The proposed parallel CBSE algorithm is then used as a basis to provide a novel cloud based framework to achieve real-time speech enhancement in mobile communication as a proof-ofconcept. The proposed parallel implementation can also be used in a variety of applications which demand real-time speech enhancement such as teleconferencing systems, digital hearing aid devices and speech recognition systems.

show abstract

An automotive application of real-time adaptive Wiener filter for non-stationary noise cancellation in a car environment

Cited by 12 publications

References 6 publications

Ambient Technology in Vehicles: The Risks and Benefits

Ambient Technology in Vehicles: The Risks and Benefits

Removal of Different Noises in Underwater Communication

Real-time codebook-based speech enhancement with GPUs

Contact Info

Product

Resources

About