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Cheng-Wen Wei

dblp:75/11154 · DBLP profile ↗
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3ranked-venue papers
1as first author
0since 2021 · last 2014
—ORCID · none

Domains — the database's venue-derived domains; a paper can count in several

Artificial intelligence and machine learning · 2Systems, architecture and hardware · 1 · 1 first-author

Expertise — from the expertise taxonomy: the topics of the expert's papers under the CCF categories. A weight counts papers with recency: 1 for a paper about the topic, 0.3 when the topic is its context, halved every five years.

Computer graphics and multimedia
1 paper
Audio and music processing · 100%

Topics — the 4 heaviest of 4, each with the papers that count most for it

TopicWeightPapersLastEvidence papers
Audio and music processing › hearing aids › acoustic feedback cancellation
adaptive feedback cancellation
0.212014
Low Complexity Formant Estimation Adaptive Feedback Cancellation for Hearing Aids Using Pitch Based Processing · IEEE ACM Trans. Audio Speech Lang. Process. 2014
Audio and music processing › speech analysis
formant tracking
0.212014
Low Complexity Formant Estimation Adaptive Feedback Cancellation for Hearing Aids Using Pitch Based Processing · IEEE ACM Trans. Audio Speech Lang. Process. 2014
Audio and music processing › hearing aids
hearing aid signal processing
0.212014
Low Complexity Formant Estimation Adaptive Feedback Cancellation for Hearing Aids Using Pitch Based Processing · IEEE ACM Trans. Audio Speech Lang. Process. 2014
Audio and music processing › speech processing
voice activity detection
0.112014
Low Complexity Formant Estimation Adaptive Feedback Cancellation for Hearing Aids Using Pitch Based Processing · IEEE ACM Trans. Audio Speech Lang. Process. 2014

Methods — techniques the papers use, named apart from their topics

pitch-based processing · 0.2decorrelation filters · 0.2
YearPublicationVenuePosition
2014 Low Complexity Formant Estimation Adaptive Feedback Cancellation for Hearing Aids Using Pitch Based Processing
abstract
This paper proposes a novel algorithm and architecture for the adaptive feedback cancellation (AFC) based on the pitch and the formant information for hearing aid (HA) applications. The proposed method, named as Pitch based Formant Estimation (PFE-AFC), has significantly low complexity compared to Prediction Error Method AFC (PEM-AFC). The proposed PFE-AFC consists of a forward and a backward path processing. The forward path processing includes a low complexity pitch based formant estimator for decorrelation filter coefficients update and a pitch based voice activity detector for speech detection, which facilitates the feedback cancellation filter in the backward path to reduce feedback component and maintain speech quality. From system point of view, the PFE-AFC has low complexity overhead since it is easy to share computation resource with other components in the HA system, such as noise reduction and auditory compensation. In addition, the PFE-AFC is suitable for hardware implementation owing to its regular structure. Complexity evaluations show that the PFE-AFC has four orders lower complexity than the PEM-AFC. Simulation results show that the PFE-AFC and the PEM-AFC can achieve similar PESQ (perceptual evaluation speech quality) and ASG (added stable gain). Moreover, the proposed PFE-AFC can outperform the conventional AFC.
Yi FanChiang, Cheng-Wen Wei, Yi-Le Meng, Yu-Wen Lin, Shyh-Jye Jou, Tian-Sheuan Chang
IEEE ACM Trans. Audio Speech Lang. Process.2
2014 Correction to "Low complexity formant estimation adaptive feedback cancellation for hearing aids using pitch based processing"
abstract
In the above paper (ibid., vol. 22, no. 8, pp.1248-1259, Aug. 2014), Table IV is incorrect. The correct table is presented here.
Yi FanChiang, Cheng-Wen Wei, Yi-Le Meng, Yu-Wen Lin, Shyh-Jye Jou, Tian-Sheuan Chang
IEEE ACM Trans. Audio Speech Lang. Process.2
2012 Sub µW Noise Reduction for CIC Hearing Aids
abstract
This paper presents a sub noise reduction design to enhance speech for completely-in-the-canal (CIC) type hearing aids by optimizing its algorithm and associated architecture. In algorithm optimization, a low-complexity mixed perceptual-discrete wavelet packet transform (P-DWPT) and fast Hartley transform (FHT) are adopted for spectral decomposition and reconstruction. A simple yet efficient denoise method with 4-zone-voice activity detection (VAD) supports a consonant protection to improve speech quality and a skip scheme to reduce power consumption. In the designed architecture, mixed P-DWPT and FHT are folded into one 8-by-8 configurable butterfly computation unit with on-time scheduling for low power operation. The circuit is implemented with 0.18 μm CMOS process and consumes only 0.65 μW power at 1.0 V with a speech quality that is comparable to that achieved using other high-complexity algorithms.
Cheng-Wen Wei, Sheng-Jie Su, Tian-Sheuan Chang, Shyh-Jye Jou
IEEE Trans. Very Large Scale Integr. Syst.1