Anti Noise Speech Recognition Based on Deep Learning in Wireless Communication Networks
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Publisher
Springer Nature Switzerland
Link
https://link.springer.com/content/pdf/10.1007/978-3-031-50543-0_11
Reference16 articles.
1. Michelsanti, D., Tan, Z.H., Zhang, S.X., et al.: An overview of deep-learning-based audio-visual speech enhancement and separation. IEEE/ACM Trans. Audio Speech Lang. Process. PP(99), 1 (2021)
2. Goehring, T., Archer-Boyd, A.W., Arenberg, J.G., et al.: The effect of increased channel interaction on speech perception with cochlear implants. Sci. Rep. 11(1), 1–9 (2021)
3. Datta, H., Hestvik, A., Vidal, N., et al.: Automaticity of speech processing in early bilingual adults and children– CORRIGENDUM. Bilingualism: Language and Cognition 24(2), 1 (2021)
4. Kapnoula, E.C., Mcmurray, B.: Individual differences in speech perception: evidence for gradiency in the face of category-driven perceptual warping. J. Acoustical Soc. Am. 149(4), A54–A54 (2021)
5. Kyaw, W.T., Sagisaka, Y.: Studies on association characteristics between vowels and visual colors using multiple speakers’ speech. Acoust. Sci. Technol.. Sci. Technol. 42(4), 161–169 (2021)
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