Speech Enhancement: A Survey of Approaches and Applications

Chhetri, Siddharth; Joshi, Manan; Mahamuni, Chaitanya Vijaykumar; Sangeetha, Repana Naga; Roy, Tushar

doi:10.1109/icecaa58104.2023.10212180

Cited by 3 publications

(2 citation statements)

References 89 publications

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“…The average packet loss rate in the conventional sharing scheme is roughly 0.47%, which is less packet loss. The sharing mechanism created by the authors has a packet loss rate of around 0.20 percent [31,32]. The author's resource sharing method has the lowest packet loss rate of the two systems stated above, and the instructional materials that are received are more comprehensive throughout the real corpus resource sharing procedure.…”

Section: Resultsmentioning

confidence: 99%

Design and Application of Corpus in Computational Linguistics based on Multimedia Virtual Technology

Cao,

Cui,

et al. 2023

SCPE

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In this paper a design and application of corpus in computational linguistics is proposed based on multimedia technology in order to solve the problem of the combination of corpus technology and multimedia teaching methods. The hardware interface circuit is created based on the USB interface board, and the S3C6410 CPU is chosen to build a multimedia embedded processor. The proposed study is primarily concerned with creating and using a corpus for computational linguistics that is based on multimedia virtual technology. Multimedia virtual technologies will be employed in this study to set up an environment that is appropriate for gathering and analyzing linguistic data. The goal is to offer a language analysis method that is more effective and efficient, as standard approaches have trouble dealing with complex and varied data sources. The accuracy, scope, and variety of the language data are anticipated to be improved by the suggested methodology. The research also suggests a possible way to improve the Corpus’s design and use in computational linguistics. In this study, encouraging results and an in-depth examination of important issues, such as reliability, validity, and efficiency, are examined. These issues should be measured when considering whether adopting a new technology is the right decision. According to the testing findings, the authors' shared system had the least reaction time-about 1.9 seconds. In conclusion, the author's corpus is more adaptable, usable, and practical for use in the classroom.

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Section: Resultsmentioning

confidence: 99%

Design and Application of Corpus in Computational Linguistics based on Multimedia Virtual Technology

Cao,

Cui,

et al. 2023

SCPE

View full text Add to dashboard Cite

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“…Their ability to modify or extract specific components of data or signals makes them valuable tools in a wide range of domains. As shown in Figure 6, here are some other application fields of filtering methods: Audio Processing : Filtering methods are extensively used in audio processing for tasks such as noise reduction, equalization, and audio effects like reverb and echo removal [60].Audio equalizers employ filters to adjust the frequency response of audio signals, allowing users to enhance or attenuate specific frequency bands.…”

Section: Other Application Fields Of Filtering Methodsmentioning

confidence: 99%

Filtering Methods for Biomedical Image Denoising

Zhao

2023

Preprint

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In this paper, the filtering method of biomedical image denoising is described comprehensively. Firstly, it introduces the biomedical image denoising, describes the relationship between biomedical image denoising and medical care, introduces the filtering methods, the filtering methods of biomedical image denoising, the challenges encountered by the current filtering methods, and other application fields of filtering methods. Firstly, the background of biomedical image denoising is introduced. Biomedical image denoising is a challenge. Different imaging modes have different noise characteristics, and noise levels can vary greatly depending on the specific application. Secondly, it describes that biomedical image denoising plays an important role in medical care, and the biomedical image directly affects the patient's diagnosis, treatment plan and the overall quality of medical care service. Then the filtering method is introduced in detail, describing the core concepts and related features of linear filtering, nonlinear filtering and frequency domain filtering, and then focusing on the adaptive filtering method, describing the characteristics, conditions of use, common algorithms and advantages of adaptive filtering method. Then the filter methods of biomedical image denoising are introduced, and the core concepts of Gaussian filter, median filter, total variation denoising and Wiener filter are introduced respectively. Then, the challenges encountered by filtering methods are described, such as the accurate selection of filters, the balance between noise reduction and image detail preservation are introduced. Finally, the application of filtering method in other fields is mentioned, such as audio processing, speech recognition and so on. In summary, this paper comprehensively expounds the denoising and filtering methods of biomedical images, the filtering methods of medical image denoising, the relationship between medical image denoising and medical care, and the challenges encountered by filtering methods.

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