VHF Speech Enhancement Based on Transformer Article Swipe
Xue Han
,
Mingyang Pan
,
Zheng-zhong Li
,
Haipeng Ge
,
Zongying Liu
·
YOU?
·
· 2022
· Open Access
·
· DOI: https://doi.org/10.1109/ojits.2022.3147816
YOU?
·
· 2022
· Open Access
·
· DOI: https://doi.org/10.1109/ojits.2022.3147816
To solve the poor quality of Very high frequency (VHF) speech communication in the navigation field, a VHF speech enhancement model based on an improved transformer (VHFSE) is proposed in this paper. The long-term and short-term noise are the reasons for the poor quality of VHF voice communication. VHFSE can reduce these two aspects of noise. We select the Two-stage Transformer based Neural Network (TSTNN) as the baseline. The Transformer structure pays attention to global information and parallel computing, which can reduce the long-term noise. In order to strengthen the ability of the model to reduce short-term noise, we add CNN module to the transformer according to the ability of revolutionary neural networks (CNN) to extract local information. Meanwhile, to improve the real-time performance, this study employs the lightweight convolution module (Depthwise Separable Convolution) to efficiency of VHF speech communication. Experimental results show that the proposed model VHFSE obtains the highest PESQ and STOI values than other compared modules. Besides, we apply the self-built dataset in our proposed model. The spectrum diagram shows that our model has the best enhancement effect on navigation VHF speech.
Related Topics
Concepts
Metadata
- Type
- article
- Language
- en
- Landing Page
- https://doi.org/10.1109/ojits.2022.3147816
- https://ieeexplore.ieee.org/ielx7/8784355/9680328/09698100.pdf
- OA Status
- gold
- Cited By
- 11
- References
- 26
- Related Works
- 10
- OpenAlex ID
- https://openalex.org/W4210682693
All OpenAlex metadata
Raw OpenAlex JSON
- OpenAlex ID
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https://openalex.org/W4210682693Canonical identifier for this work in OpenAlex
- DOI
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https://doi.org/10.1109/ojits.2022.3147816Digital Object Identifier
- Title
-
VHF Speech Enhancement Based on TransformerWork title
- Type
-
articleOpenAlex work type
- Language
-
enPrimary language
- Publication year
-
2022Year of publication
- Publication date
-
2022-01-01Full publication date if available
- Authors
-
Xue Han, Mingyang Pan, Zheng-zhong Li, Haipeng Ge, Zongying LiuList of authors in order
- Landing page
-
https://doi.org/10.1109/ojits.2022.3147816Publisher landing page
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https://ieeexplore.ieee.org/ielx7/8784355/9680328/09698100.pdfDirect link to full text PDF
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YesWhether a free full text is available
- OA status
-
goldOpen access status per OpenAlex
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https://ieeexplore.ieee.org/ielx7/8784355/9680328/09698100.pdfDirect OA link when available
- Concepts
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Computer science, PESQ, Transformer, Speech recognition, Speech enhancement, Convolutional neural network, Electronic engineering, Artificial intelligence, Noise reduction, Engineering, Electrical engineering, VoltageTop concepts (fields/topics) attached by OpenAlex
- Cited by
-
11Total citation count in OpenAlex
- Citations by year (recent)
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2025: 2, 2024: 5, 2023: 4Per-year citation counts (last 5 years)
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26Number of works referenced by this work
- Related works (count)
-
10Other works algorithmically related by OpenAlex
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| primary_location.landing_page_url | https://doi.org/10.1109/ojits.2022.3147816 |
| publication_date | 2022-01-01 |
| publication_year | 2022 |
| referenced_works | https://openalex.org/W3135188703, https://openalex.org/W3174904875, https://openalex.org/W3175140823, https://openalex.org/W3097777922, https://openalex.org/W2128653836, https://openalex.org/W1995536493, https://openalex.org/W2121973264, https://openalex.org/W2078528584, https://openalex.org/W2963453742, https://openalex.org/W2897371647, https://openalex.org/W6756251360, https://openalex.org/W3044712972, https://openalex.org/W2605589342, https://openalex.org/W2962843322, https://openalex.org/W3122728801, https://openalex.org/W6739901393, https://openalex.org/W3129077738, https://openalex.org/W3095820034, https://openalex.org/W2964089206, https://openalex.org/W3161950572, https://openalex.org/W3096893582, https://openalex.org/W6737664043, https://openalex.org/W2963242190, https://openalex.org/W6631190155, https://openalex.org/W1552314771, https://openalex.org/W2963341071 |
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