A novel dual-microphone speech enhancement technique is proposed in the present paper. The technique utilizes the coherence between the target and noise signals as a criterion for noise reduction and can be generally applied to arrays with closely-spaced microphones, where noise captured by the sensors is highly correlated. The proposed algorithm is simple to implement and requires no estimation of noise statistics. In addition, it offers the capability of coping with multiple interfering sources that might be located at different azimuths. The proposed algorithm was evaluated with normal hearing listeners using intelligibility listening tests and compared against a well-established beamforming algorithm. Results indicated large gains in speech intelligibility relative to the baseline (front microphone) algorithm in both single and multiple-noise source scenarios. The proposed algorithm was found to yield substantially higher intelligibility than that obtained by the beamforming algorithm, particularly when multiple noise sources or competing talker(s) were present. Objective quality evaluation of the proposed algorithm also indicated significant quality improvement over that obtained by the beamforming algorithm. The intelligibility and quality benefits observed with the proposed coherence-based algorithm make it a viable candidate for hearing aid and cochlear implant devices.
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http://dx.doi.org/10.1109/TASL.2011.2162406 | DOI Listing |
Biometrics
January 2025
Department of Statistics and Data Science, National University of Singapore, Singapore 117546, Singapore.
Pharmacogenomics stands as a pivotal driver toward personalized medicine, aiming to optimize drug efficacy while minimizing adverse effects by uncovering the impact of genetic variations on inter-individual outcome variability. Despite its promise, the intricate landscape of drug metabolism introduces complexity, where the correlation between drug response and genes can be shaped by numerous nongenetic factors, often exhibiting heterogeneity across diverse subpopulations. This challenge is particularly pronounced in datasets such as the International Warfarin Pharmacogenetic Consortium (IWPC), which encompasses diverse patient information from multiple nations.
View Article and Find Full Text PDFAnal Methods
January 2025
Jiangsu Beier Machinery Co. Ltd, Jiangsu, 215600, China.
Plastic waste management is one of the key issues in global environmental protection. Integrating spectroscopy acquisition devices with deep learning algorithms has emerged as an effective method for rapid plastic classification. However, the challenges in collecting plastic samples and spectroscopy data have resulted in a limited number of data samples and an incomplete comparison of relevant classification algorithms.
View Article and Find Full Text PDFBioelectromagnetics
January 2025
Department of Electrical Engineering and ITEMS, University of Southern California, Los Angeles, California, USA.
As the clinical applicability of peripheral nerve stimulation (PNS) expands, the need for PNS-specific safety criteria becomes pressing. This study addresses this need, utilizing a novel machine learning and computational bio-electromagnetics modeling platform to establish a safety criterion that captures the effects of fields and currents induced on axons. Our approach is comprised of three steps: experimentation, model creation, and predictive simulation.
View Article and Find Full Text PDFWorld J Gastrointest Oncol
January 2025
Department of Hepatobiliary and Pancreaticosplenic Surgery, Jingzhou Hospital Affiliated to Yangtze University, Jingzhou 434100, Hubei Province, China.
Background: The liver, as the main target organ for hematogenous metastasis of colorectal cancer, early and accurate prediction of liver metastasis is crucial for the diagnosis and treatment of patients. Herein, this study aims to investigate the application value of a combined machine learning (ML) based model based on the multiparameter magnetic resonance imaging for prediction of rectal metachronous liver metastasis (MLM).
Aim: To investigate the efficacy of radiomics based on multiparametric magnetic resonance imaging images of preoperative first diagnosed rectal cancer in predicting MLM from rectal cancer.
R Soc Open Sci
January 2025
Department of Forensic Medicine, School of Basic Medical Sciences, Central South University, No172. Tongzipo Road, Changsha, Hunan 410013, People's Republic of China.
DNA mixtures containing semen and vaginal fluid are common biological samples in forensic analysis. However, the analysis of semen-vaginal fluid mixtures remains challenging. In this study, to solve these problems, it is proposed to combine semen-specific CpG sites and closely related microhaplotype sites to form a new composite genetic marker (semen-specific methylation-microhaplotype).
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