Acoustic modeling using a shallow CNN-HTSVM architecture (2017)
- Authors:
- USP affiliated authors: MELLO, RODRIGO FERNANDES DE - ICMC ; ALUISIO, SANDRA MARIA - ICMC
- Unidade: ICMC
- DOI: 10.1109/BRACIS.2017.62
- Subjects: REDES NEURAIS; APRENDIZADO COMPUTACIONAL; RECONHECIMENTO DE VOZ
- Keywords: speech recognition; convolutional neural networks; acoustic modeling; shallow learning; hierarchical classification; support vector machines
- Language: Inglês
- Imprenta:
- Publisher: IEEE
- Publisher place: Piscataway
- Date published: 2017
- Source:
- Título: Proceedings
- Volume/Número/Paginação/Ano: 978153862407
- Conference titles: Brazilian Conference on Intelligent Systems - BRACIS
- Este periódico é de acesso aberto
- Este artigo NÃO é de acesso aberto
-
ABNT
SHULBY, Christopher Dane et al. Acoustic modeling using a shallow CNN-HTSVM architecture. 2017, Anais.. Piscataway: IEEE, 2017. Disponível em: https://doi.org/10.1109/BRACIS.2017.62. Acesso em: 28 fev. 2026. -
APA
Shulby, C. D., Ferreira, M. D., Mello, R. F. de, & Aluísio, S. M. (2017). Acoustic modeling using a shallow CNN-HTSVM architecture. In Proceedings. Piscataway: IEEE. doi:10.1109/BRACIS.2017.62 -
NLM
Shulby CD, Ferreira MD, Mello RF de, Aluísio SM. Acoustic modeling using a shallow CNN-HTSVM architecture [Internet]. Proceedings. 2017 ;[citado 2026 fev. 28 ] Available from: https://doi.org/10.1109/BRACIS.2017.62 -
Vancouver
Shulby CD, Ferreira MD, Mello RF de, Aluísio SM. Acoustic modeling using a shallow CNN-HTSVM architecture [Internet]. Proceedings. 2017 ;[citado 2026 fev. 28 ] Available from: https://doi.org/10.1109/BRACIS.2017.62 - Theoretical learning guarantees applied to acoustic modeling
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Informações sobre o DOI: 10.1109/BRACIS.2017.62 (Fonte: oaDOI API)
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