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Filtros : "RAMIREZ, MIGUEL ARJONA" Removido: "PALAVRAS-CHAVE" Limpar

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  • Artigo de periodico

    Analysis of oral exams with speaker diarization and speech emotion recognition: a case study (2023)

    Beccaro, Wesley; Arjona Ramírez, Miguel ; Liaw, William; Guimarães, Heitor Rodrigues

    Source: IEEE Transactions on Education. Unidade: EP

    Subjects: RECONHECIMENTO DE VOZ, EMOÇÕES

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      BECCARO, Wesley et al. Analysis of oral exams with speaker diarization and speech emotion recognition: a case study. IEEE Transactions on Education, p. 1-13, 2023Tradução . . Disponível em: https://doi.org/10.1109/TE.2023.3321155. Acesso em: 14 jun. 2025.

    • APA

      Beccaro, W., Arjona Ramírez, M., Liaw, W., & Guimarães, H. R. (2023). Analysis of oral exams with speaker diarization and speech emotion recognition: a case study. IEEE Transactions on Education, 1-13. doi:10.1109/TE.2023.3321155

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      Beccaro W, Arjona Ramírez M, Liaw W, Guimarães HR. Analysis of oral exams with speaker diarization and speech emotion recognition: a case study [Internet]. IEEE Transactions on Education. 2023 ; 1-13.[citado 2025 jun. 14 ] Available from: https://doi.org/10.1109/TE.2023.3321155

    • Vancouver

      Beccaro W, Arjona Ramírez M, Liaw W, Guimarães HR. Analysis of oral exams with speaker diarization and speech emotion recognition: a case study [Internet]. IEEE Transactions on Education. 2023 ; 1-13.[citado 2025 jun. 14 ] Available from: https://doi.org/10.1109/TE.2023.3321155

  • Artigo de periodico

    Differentiable measures for speech spectral modeling (2022)

    Arjona Ramírez, Miguel ; Beccaro, Wesley; Zegarra Rodriguez, Demóstenes ; Rosa, Renata Lopes

    Source: IEEE Access. Unidade: EP

    Subjects: MÉTODOS DE PREVISÃO E CORREÇÃO, ANÁLISE ESPECTRAL

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      ARJONA RAMÍREZ, Miguel et al. Differentiable measures for speech spectral modeling. IEEE Access, v. 10, p. 17609-17618, 2022Tradução . . Disponível em: https://doi.org/10.1109/ACCESS.2022.3150728. Acesso em: 14 jun. 2025.

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      Arjona Ramírez, M., Beccaro, W., Zegarra Rodriguez, D., & Rosa, R. L. (2022). Differentiable measures for speech spectral modeling. IEEE Access, 10, 17609-17618. doi:10.1109/ACCESS.2022.3150728

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      Arjona Ramírez M, Beccaro W, Zegarra Rodriguez D, Rosa RL. Differentiable measures for speech spectral modeling [Internet]. IEEE Access. 2022 ;10 17609-17618.[citado 2025 jun. 14 ] Available from: https://doi.org/10.1109/ACCESS.2022.3150728

    • Vancouver

      Arjona Ramírez M, Beccaro W, Zegarra Rodriguez D, Rosa RL. Differentiable measures for speech spectral modeling [Internet]. IEEE Access. 2022 ;10 17609-17618.[citado 2025 jun. 14 ] Available from: https://doi.org/10.1109/ACCESS.2022.3150728

  • Artigo de periodico

    Evaluation of 1D and 2D deep convolutional neural networks for driving event recognition (2022)

    Escottá, Álvaro Teixeira; Beccaro, Wesley; Arjona Ramírez, Miguel

    Source: Sensors. Unidade: EP

    Subjects: REDES NEURAIS, ANÁLISE DE SÉRIES TEMPORAIS, APRENDIZAGEM PROFUNDA

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      ESCOTTÁ, Álvaro Teixeira e BECCARO, Wesley e ARJONA RAMÍREZ, Miguel. Evaluation of 1D and 2D deep convolutional neural networks for driving event recognition. Sensors, v. 22, n. 11, 2022Tradução . . Disponível em: https://doi.org/10.3390/s22114226. Acesso em: 14 jun. 2025.

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      Escottá, Á. T., Beccaro, W., & Arjona Ramírez, M. (2022). Evaluation of 1D and 2D deep convolutional neural networks for driving event recognition. Sensors, 22( 11). doi:10.3390/s22114226

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      Escottá ÁT, Beccaro W, Arjona Ramírez M. Evaluation of 1D and 2D deep convolutional neural networks for driving event recognition [Internet]. Sensors. 2022 ; 22( 11):[citado 2025 jun. 14 ] Available from: https://doi.org/10.3390/s22114226

    • Vancouver

      Escottá ÁT, Beccaro W, Arjona Ramírez M. Evaluation of 1D and 2D deep convolutional neural networks for driving event recognition [Internet]. Sensors. 2022 ; 22( 11):[citado 2025 jun. 14 ] Available from: https://doi.org/10.3390/s22114226

  • Trabalho de evento

    A perceptual loss based complex neural beamforming for ambix 3D speech enhancement (2022)

    Guimarães, Heitor Rodrigues; Beccaro, Wesley; Arjona Ramírez, Miguel

    Source: L3DAS22: proceedings. Conference titles: Machine Learning for 3D Audio Signal Processing Virtual. Unidade: EP

    Subjects: APRENDIZAGEM PROFUNDA, REDES COMPLEXAS, PROCESSAMENTO DE VOZ

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      GUIMARÃES, Heitor Rodrigues e BECCARO, Wesley e ARJONA RAMÍREZ, Miguel. A perceptual loss based complex neural beamforming for ambix 3D speech enhancement. 2022, Anais.. [S.l.: s.n.], 2022. Disponível em: https://repositorio.usp.br/directbitstream/81d47ead-b3ba-41e9-be82-ed7c85fe0f67/A%20perceptual%20loss%20based%20complex%20neural%20beamforming%20for%20ambix%203D%20Speech%20enhancement.pdf. Acesso em: 14 jun. 2025.

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      Guimarães, H. R., Beccaro, W., & Arjona Ramírez, M. (2022). A perceptual loss based complex neural beamforming for ambix 3D speech enhancement. In L3DAS22: proceedings. [S.l.: s.n.]. Recuperado de https://repositorio.usp.br/directbitstream/81d47ead-b3ba-41e9-be82-ed7c85fe0f67/A%20perceptual%20loss%20based%20complex%20neural%20beamforming%20for%20ambix%203D%20Speech%20enhancement.pdf

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      Guimarães HR, Beccaro W, Arjona Ramírez M. A perceptual loss based complex neural beamforming for ambix 3D speech enhancement [Internet]. L3DAS22: proceedings. 2022 ;[citado 2025 jun. 14 ] Available from: https://repositorio.usp.br/directbitstream/81d47ead-b3ba-41e9-be82-ed7c85fe0f67/A%20perceptual%20loss%20based%20complex%20neural%20beamforming%20for%20ambix%203D%20Speech%20enhancement.pdf

    • Vancouver

      Guimarães HR, Beccaro W, Arjona Ramírez M. A perceptual loss based complex neural beamforming for ambix 3D speech enhancement [Internet]. L3DAS22: proceedings. 2022 ;[citado 2025 jun. 14 ] Available from: https://repositorio.usp.br/directbitstream/81d47ead-b3ba-41e9-be82-ed7c85fe0f67/A%20perceptual%20loss%20based%20complex%20neural%20beamforming%20for%20ambix%203D%20Speech%20enhancement.pdf

  • Trabalho de evento

    Selection of beamforming in 5G MIMO scenarios using machine learning approach (2022)

    Silva, Douglas Henrique; Ribeiro, David Augusto; Arjona Ramírez, Miguel ; Rosa, Renata Lopes ; Chaudhary, Sushank; Zegarra Rodriguez, Demóstenes

    Source: ECTI-CON. Conference titles: 2022 International Conference on Electrical Engineering/Electronics, Computer, Telecommunications and Information Technology. Unidade: EP

    Subjects: APRENDIZADO COMPUTACIONAL, INTELIGÊNCIA ARTIFICIAL, ALGORITMOS, REDES E COMUNICAÇÃO DE DADOS

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      SILVA, Douglas Henrique et al. Selection of beamforming in 5G MIMO scenarios using machine learning approach. 2022, Anais.. Piscataway: IEEE, 2022. Disponível em: https://doi.org/10.1109/ECTI-CON54298.2022.9795421. Acesso em: 14 jun. 2025.

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      Silva, D. H., Ribeiro, D. A., Arjona Ramírez, M., Rosa, R. L., Chaudhary, S., & Zegarra Rodriguez, D. (2022). Selection of beamforming in 5G MIMO scenarios using machine learning approach. In ECTI-CON. Piscataway: IEEE. doi:10.1109/ECTI-CON54298.2022.9795421

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      Silva DH, Ribeiro DA, Arjona Ramírez M, Rosa RL, Chaudhary S, Zegarra Rodriguez D. Selection of beamforming in 5G MIMO scenarios using machine learning approach [Internet]. ECTI-CON. 2022 ;[citado 2025 jun. 14 ] Available from: https://doi.org/10.1109/ECTI-CON54298.2022.9795421

    • Vancouver

      Silva DH, Ribeiro DA, Arjona Ramírez M, Rosa RL, Chaudhary S, Zegarra Rodriguez D. Selection of beamforming in 5G MIMO scenarios using machine learning approach [Internet]. ECTI-CON. 2022 ;[citado 2025 jun. 14 ] Available from: https://doi.org/10.1109/ECTI-CON54298.2022.9795421

  • Artigo de periodico

    Incorporating wireless communication parameters into the E-Model algorithm (2021)

    Zegarra Rodriguez, Demóstenes ; Carrillo, Dick; Arjona Ramírez, Miguel ; Nardelli, Pedro H. J.; Möller, Sebastian

    Source: IEEE/ACM Transactions on Audio, Speech, and Language Processing. Unidade: EP

    Subjects: WIRELESS, ALGORITMOS

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      ZEGARRA RODRIGUEZ, Demóstenes et al. Incorporating wireless communication parameters into the E-Model algorithm. IEEE/ACM Transactions on Audio, Speech, and Language Processing, v. 29, p. 956-968, 2021Tradução . . Disponível em: https://doi.org/10.1109/TASLP.2021.3057955. Acesso em: 14 jun. 2025.

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      Zegarra Rodriguez, D., Carrillo, D., Arjona Ramírez, M., Nardelli, P. H. J., & Möller, S. (2021). Incorporating wireless communication parameters into the E-Model algorithm. IEEE/ACM Transactions on Audio, Speech, and Language Processing, 29, 956-968. doi:10.1109/TASLP.2021.3057955

    • NLM

      Zegarra Rodriguez D, Carrillo D, Arjona Ramírez M, Nardelli PHJ, Möller S. Incorporating wireless communication parameters into the E-Model algorithm [Internet]. IEEE/ACM Transactions on Audio, Speech, and Language Processing. 2021 ;29 956-968.[citado 2025 jun. 14 ] Available from: https://doi.org/10.1109/TASLP.2021.3057955

    • Vancouver

      Zegarra Rodriguez D, Carrillo D, Arjona Ramírez M, Nardelli PHJ, Möller S. Incorporating wireless communication parameters into the E-Model algorithm [Internet]. IEEE/ACM Transactions on Audio, Speech, and Language Processing. 2021 ;29 956-968.[citado 2025 jun. 14 ] Available from: https://doi.org/10.1109/TASLP.2021.3057955

  • Artigo de periodico

    Enhanced routing algorithm based on reinforcement machine learning: a case of voIP service (2021)

    Militani, Davi Ribeiro; Moraes, Hermes Pimenta de; Rosa, Renata Lopes; Zegarra Rodriguez, Demóstenes ; Arjona Ramírez, Miguel ; Wuttisittikulkij, Lunchakorn

    Source: Sensors. Unidade: EP

    Subjects: APRENDIZADO COMPUTACIONAL, INSTRUÇÃO PROGRAMADA

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      MILITANI, Davi Ribeiro et al. Enhanced routing algorithm based on reinforcement machine learning: a case of voIP service. Sensors, v. 21, n. 2, p. 504-536, 2021Tradução . . Disponível em: https://doi.org/10.3390/s21020504. Acesso em: 14 jun. 2025.

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      Militani, D. R., Moraes, H. P. de, Rosa, R. L., Zegarra Rodriguez, D., Arjona Ramírez, M., & Wuttisittikulkij, L. (2021). Enhanced routing algorithm based on reinforcement machine learning: a case of voIP service. Sensors, 21( 2), 504-536. doi:10.3390/s21020504

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      Militani DR, Moraes HP de, Rosa RL, Zegarra Rodriguez D, Arjona Ramírez M, Wuttisittikulkij L. Enhanced routing algorithm based on reinforcement machine learning: a case of voIP service [Internet]. Sensors. 2021 ;21( 2): 504-536.[citado 2025 jun. 14 ] Available from: https://doi.org/10.3390/s21020504

    • Vancouver

      Militani DR, Moraes HP de, Rosa RL, Zegarra Rodriguez D, Arjona Ramírez M, Wuttisittikulkij L. Enhanced routing algorithm based on reinforcement machine learning: a case of voIP service [Internet]. Sensors. 2021 ;21( 2): 504-536.[citado 2025 jun. 14 ] Available from: https://doi.org/10.3390/s21020504

  • Artigo de periodico

    Q-Meter: quality monitoring system for telecommunication services based on sentiment analysis using deep learning (2021)

    Vieira, Samuel Terra; Rosa, Renata Lopes; Zegarra Rodriguez, Demóstenes ; Arjona Ramírez, Miguel ; Saadi, Muhammad; Wuttisittikulkij, Lunchakorn

    Source: Sensors. Unidade: EP

    Subjects: TELECOMUNICAÇÕES, REDES SOCIAIS

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      VIEIRA, Samuel Terra et al. Q-Meter: quality monitoring system for telecommunication services based on sentiment analysis using deep learning. Sensors, v. 21, n. 5, p. 1-18, 2021Tradução . . Disponível em: https://doi.org/10.3390/s21051880. Acesso em: 14 jun. 2025.

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      Vieira, S. T., Rosa, R. L., Zegarra Rodriguez, D., Arjona Ramírez, M., Saadi, M., & Wuttisittikulkij, L. (2021). Q-Meter: quality monitoring system for telecommunication services based on sentiment analysis using deep learning. Sensors, 21( 5), 1-18. doi:10.3390/s21051880

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      Vieira ST, Rosa RL, Zegarra Rodriguez D, Arjona Ramírez M, Saadi M, Wuttisittikulkij L. Q-Meter: quality monitoring system for telecommunication services based on sentiment analysis using deep learning [Internet]. Sensors. 2021 ;21( 5): 1-18.[citado 2025 jun. 14 ] Available from: https://doi.org/10.3390/s21051880

    • Vancouver

      Vieira ST, Rosa RL, Zegarra Rodriguez D, Arjona Ramírez M, Saadi M, Wuttisittikulkij L. Q-Meter: quality monitoring system for telecommunication services based on sentiment analysis using deep learning [Internet]. Sensors. 2021 ;21( 5): 1-18.[citado 2025 jun. 14 ] Available from: https://doi.org/10.3390/s21051880

  • Artigo de periodico

    Generative adversarial networks in human emotion synthesis: a review (2020)

    Hajarolasvadi, Noushin; Arjona Ramírez, Miguel ; Beccaro, Wesley; Demirel, Hasan

    Source: IEEE Access. Unidades: EP, IO

    Assunto: PROCESSAMENTO DE IMAGENS

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      HAJAROLASVADI, Noushin et al. Generative adversarial networks in human emotion synthesis: a review. IEEE Access, v. 8, p. 218499-218529, 2020Tradução . . Disponível em: https://doi.org/10.1109/ACCESS.2020.3042328. Acesso em: 14 jun. 2025.

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      Hajarolasvadi, N., Arjona Ramírez, M., Beccaro, W., & Demirel, H. (2020). Generative adversarial networks in human emotion synthesis: a review. IEEE Access, 8, 218499-218529. doi:10.1109/ACCESS.2020.3042328

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      Hajarolasvadi N, Arjona Ramírez M, Beccaro W, Demirel H. Generative adversarial networks in human emotion synthesis: a review [Internet]. IEEE Access. 2020 ; 8 218499-218529.[citado 2025 jun. 14 ] Available from: https://doi.org/10.1109/ACCESS.2020.3042328

    • Vancouver

      Hajarolasvadi N, Arjona Ramírez M, Beccaro W, Demirel H. Generative adversarial networks in human emotion synthesis: a review [Internet]. IEEE Access. 2020 ; 8 218499-218529.[citado 2025 jun. 14 ] Available from: https://doi.org/10.1109/ACCESS.2020.3042328

  • Artigo de periodico

    Adaptive Cognitive System Applied to WSN Decisions at Nodes with a Fuzzy Logic Approach (2016)

    Wagner, Marcel Stefan; Arjona Ramírez, Miguel ; Zucchi, Wagner Luiz

    Source: IJCSNT. Unidade: EP

    Subjects: LÓGICA FUZZY, WIRELESS, CONTROLE ADAPTATIVO, INTELIGÊNCIA ARTIFICIAL

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      WAGNER, Marcel Stefan e ARJONA RAMÍREZ, Miguel e ZUCCHI, Wagner Luiz. Adaptive Cognitive System Applied to WSN Decisions at Nodes with a Fuzzy Logic Approach. IJCSNT, v. 5, n. 1, p. 1-16, 2016Tradução . . Disponível em: http://ijcsnt.info/papers/IJCSNT_5_1_01.pdf. Acesso em: 14 jun. 2025.

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      Wagner, M. S., Arjona Ramírez, M., & Zucchi, W. L. (2016). Adaptive Cognitive System Applied to WSN Decisions at Nodes with a Fuzzy Logic Approach. IJCSNT, 5( 1), 1-16. Recuperado de http://ijcsnt.info/papers/IJCSNT_5_1_01.pdf

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      Wagner MS, Arjona Ramírez M, Zucchi WL. Adaptive Cognitive System Applied to WSN Decisions at Nodes with a Fuzzy Logic Approach [Internet]. IJCSNT. 2016 ; 5( 1): 1-16.[citado 2025 jun. 14 ] Available from: http://ijcsnt.info/papers/IJCSNT_5_1_01.pdf

    • Vancouver

      Wagner MS, Arjona Ramírez M, Zucchi WL. Adaptive Cognitive System Applied to WSN Decisions at Nodes with a Fuzzy Logic Approach [Internet]. IJCSNT. 2016 ; 5( 1): 1-16.[citado 2025 jun. 14 ] Available from: http://ijcsnt.info/papers/IJCSNT_5_1_01.pdf

  • Artigo de periodico

    Nonnegative temporal decomposition regularization with an augmented Llagrangian (2016)

    Arjona Ramírez, Miguel

    Source: Signal Processing Letters, IEEE. Unidade: EP

    Assunto: FRAMEWORKS

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      ARJONA RAMÍREZ, Miguel. Nonnegative temporal decomposition regularization with an augmented Llagrangian. Signal Processing Letters, IEEE, v. 23, n. 5, p. 663-667, 2016Tradução . . Disponível em: https://doi.org/10.1109/LSP.2016.2544921. Acesso em: 14 jun. 2025.

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      Arjona Ramírez, M. (2016). Nonnegative temporal decomposition regularization with an augmented Llagrangian. Signal Processing Letters, IEEE, 23( 5), 663-667. doi:10.1109/LSP.2016.2544921

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      Arjona Ramírez M. Nonnegative temporal decomposition regularization with an augmented Llagrangian [Internet]. Signal Processing Letters, IEEE. 2016 ; 23( 5): 663-667.[citado 2025 jun. 14 ] Available from: https://doi.org/10.1109/LSP.2016.2544921

    • Vancouver

      Arjona Ramírez M. Nonnegative temporal decomposition regularization with an augmented Llagrangian [Internet]. Signal Processing Letters, IEEE. 2016 ; 23( 5): 663-667.[citado 2025 jun. 14 ] Available from: https://doi.org/10.1109/LSP.2016.2544921

  • Trabalho de evento

    Adaptive cognitive system applied on Wireless sensor networks nodes decisions (2015)

    Wagner, Marcel Stefan; Zucchi, Wagner Luiz ; Arjona Ramírez, Miguel

    Conference titles: International conference on Communicatin Systems and Network Technologies - CSNT. Unidade: EP

    Subjects: COGNIÇÃO, CONTROLE ADAPTATIVO, WIRELESS

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      WAGNER, Marcel Stefan e ZUCCHI, Wagner Luiz e ARJONA RAMÍREZ, Miguel. Adaptive cognitive system applied on Wireless sensor networks nodes decisions. 2015, Anais.. Gwalior: IEEE, 2015. Disponível em: https://doi.org/10.1109/CSNT.2015.65. Acesso em: 14 jun. 2025.

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      Wagner, M. S., Zucchi, W. L., & Arjona Ramírez, M. (2015). Adaptive cognitive system applied on Wireless sensor networks nodes decisions. In . Gwalior: IEEE. doi:10.1109/CSNT.2015.65

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      Wagner MS, Zucchi WL, Arjona Ramírez M. Adaptive cognitive system applied on Wireless sensor networks nodes decisions [Internet]. 2015 ;[citado 2025 jun. 14 ] Available from: https://doi.org/10.1109/CSNT.2015.65

    • Vancouver

      Wagner MS, Zucchi WL, Arjona Ramírez M. Adaptive cognitive system applied on Wireless sensor networks nodes decisions [Internet]. 2015 ;[citado 2025 jun. 14 ] Available from: https://doi.org/10.1109/CSNT.2015.65

  • Artigo de periodico

    Time-frequency voiced and unvoiced excitation models for harmonic speech systems (2014)

    Arjona Ramírez, Miguel

    Source: Journal of Communication and Information Systems. Unidade: EP

    Subjects: FREQUÊNCIA DO SOM, FREQUÊNCIA DO SOM

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      ARJONA RAMÍREZ, Miguel. Time-frequency voiced and unvoiced excitation models for harmonic speech systems. Journal of Communication and Information Systems, v. 29, n. 1, p. 63-69, 2014Tradução . . Disponível em: https://doi.org/10.14209/jcis.2014.6. Acesso em: 14 jun. 2025.

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      Arjona Ramírez, M. (2014). Time-frequency voiced and unvoiced excitation models for harmonic speech systems. Journal of Communication and Information Systems, 29( 1), 63-69. doi:10.14209/jcis.2014.6

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      Arjona Ramírez M. Time-frequency voiced and unvoiced excitation models for harmonic speech systems [Internet]. Journal of Communication and Information Systems. 2014 ; 29( 1): 63-69.[citado 2025 jun. 14 ] Available from: https://doi.org/10.14209/jcis.2014.6

    • Vancouver

      Arjona Ramírez M. Time-frequency voiced and unvoiced excitation models for harmonic speech systems [Internet]. Journal of Communication and Information Systems. 2014 ; 29( 1): 63-69.[citado 2025 jun. 14 ] Available from: https://doi.org/10.14209/jcis.2014.6

  • Artigo de periodico

    Prediction Transform GMM Vector Quantization for Wideband LSFs (2014)

    Arjona Ramírez, Miguel

    Source: Journal of Communication and Information Systems. Unidade: EP

    Assunto: VETORES

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      ARJONA RAMÍREZ, Miguel. Prediction Transform GMM Vector Quantization for Wideband LSFs. Journal of Communication and Information Systems, v. 29, n. 1, p. 56-62, 2014Tradução . . Disponível em: https://doi.org/10.14209/jcis.2014.5. Acesso em: 14 jun. 2025.

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      Arjona Ramírez, M. (2014). Prediction Transform GMM Vector Quantization for Wideband LSFs. Journal of Communication and Information Systems, 29( 1), 56-62. doi:10.14209/jcis.2014.5

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      Arjona Ramírez M. Prediction Transform GMM Vector Quantization for Wideband LSFs [Internet]. Journal of Communication and Information Systems. 2014 ; 29( 1): 56-62.[citado 2025 jun. 14 ] Available from: https://doi.org/10.14209/jcis.2014.5

    • Vancouver

      Arjona Ramírez M. Prediction Transform GMM Vector Quantization for Wideband LSFs [Internet]. Journal of Communication and Information Systems. 2014 ; 29( 1): 56-62.[citado 2025 jun. 14 ] Available from: https://doi.org/10.14209/jcis.2014.5

  • Trabalho de evento

    Gaussian mixture models with class-dependent features for speech emotion recognition (2014)

    Iriya, Rafael; Arjona Ramírez, Miguel

    Conference titles: Workshop on Statistical Signal Processing- SSP. Unidade: EP

    Subjects: RECONHECIMENTO DE VOZ, CONTROLE ADAPTATIVO

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      IRIYA, Rafael e ARJONA RAMÍREZ, Miguel. Gaussian mixture models with class-dependent features for speech emotion recognition. 2014, Anais.. Australia: IEEE, 2014. Disponível em: https://doi.org/10.1109/SSP.2014.6884680. Acesso em: 14 jun. 2025.

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      Iriya, R., & Arjona Ramírez, M. (2014). Gaussian mixture models with class-dependent features for speech emotion recognition. In . Australia: IEEE. doi:10.1109/SSP.2014.6884680

    • NLM

      Iriya R, Arjona Ramírez M. Gaussian mixture models with class-dependent features for speech emotion recognition [Internet]. 2014 ;[citado 2025 jun. 14 ] Available from: https://doi.org/10.1109/SSP.2014.6884680

    • Vancouver

      Iriya R, Arjona Ramírez M. Gaussian mixture models with class-dependent features for speech emotion recognition [Internet]. 2014 ;[citado 2025 jun. 14 ] Available from: https://doi.org/10.1109/SSP.2014.6884680

  • Trabalho de evento

    Intra-Predictive Switched Split Vector Quantization of Speech Spectra (2014)

    Arjona Ramírez, Miguel

    Source: Proceedings. Conference titles: IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP). Unidade: EP

    Subjects: SISTEMAS DINÂMICOS, VETORES

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      ARJONA RAMÍREZ, Miguel. Intra-Predictive Switched Split Vector Quantization of Speech Spectra. 2014, Anais.. USA: IEEE, 2014. . Acesso em: 14 jun. 2025.

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      Arjona Ramírez, M. (2014). Intra-Predictive Switched Split Vector Quantization of Speech Spectra. In Proceedings. USA: IEEE.

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      Arjona Ramírez M. Intra-Predictive Switched Split Vector Quantization of Speech Spectra. Proceedings. 2014 ;[citado 2025 jun. 14 ]

    • Vancouver

      Arjona Ramírez M. Intra-Predictive Switched Split Vector Quantization of Speech Spectra. Proceedings. 2014 ;[citado 2025 jun. 14 ]

  • Trabalho de evento

    Nonnegative factorization of sequences of speech and music spectra (2014)

    Arjona Ramírez, Miguel

    Conference titles: International Telecommunications Symposium (ITS). Unidade: EP

    Assunto: PROCESSAMENTO DE SINAIS

    Acesso à fonteDOIHow to cite
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    • ABNT

      ARJONA RAMÍREZ, Miguel. Nonnegative factorization of sequences of speech and music spectra. 2014, Anais.. São Paulo: IEEE, 2014. Disponível em: https://doi.org/10.1109/ITS.2014.6948021. Acesso em: 14 jun. 2025.

    • APA

      Arjona Ramírez, M. (2014). Nonnegative factorization of sequences of speech and music spectra. In . São Paulo: IEEE. doi:10.1109/ITS.2014.6948021

    • NLM

      Arjona Ramírez M. Nonnegative factorization of sequences of speech and music spectra [Internet]. 2014 ;[citado 2025 jun. 14 ] Available from: https://doi.org/10.1109/ITS.2014.6948021

    • Vancouver

      Arjona Ramírez M. Nonnegative factorization of sequences of speech and music spectra [Internet]. 2014 ;[citado 2025 jun. 14 ] Available from: https://doi.org/10.1109/ITS.2014.6948021

  • Trabalho de evento

    Decorrelating transforms for spectral vector quantization (2013)

    Arjona Ramírez, Miguel

    Source: Proceedings. Conference titles: International Conference on Digital Signal Processing-DSP. Unidade: EP

    Assunto: PROCESSAMENTO DE SINAIS

    Acesso à fonteDOIHow to cite
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    • ABNT

      ARJONA RAMÍREZ, Miguel. Decorrelating transforms for spectral vector quantization. 2013, Anais.. Santorini, Greece: IEEE, 2013. Disponível em: https://doi.org/10.1109/ICDSP.2013.6622682. Acesso em: 14 jun. 2025.

    • APA

      Arjona Ramírez, M. (2013). Decorrelating transforms for spectral vector quantization. In Proceedings. Santorini, Greece: IEEE. doi:10.1109/ICDSP.2013.6622682

    • NLM

      Arjona Ramírez M. Decorrelating transforms for spectral vector quantization [Internet]. Proceedings. 2013 ;[citado 2025 jun. 14 ] Available from: https://doi.org/10.1109/ICDSP.2013.6622682

    • Vancouver

      Arjona Ramírez M. Decorrelating transforms for spectral vector quantization [Internet]. Proceedings. 2013 ;[citado 2025 jun. 14 ] Available from: https://doi.org/10.1109/ICDSP.2013.6622682

  • Artigo de periodico

    Intra-predictive switched split vector quantization of speech spectra (2013)

    Arjona Ramírez, Miguel

    Source: IEEE Signal Processing Letters. Unidade: EP

    Assunto: VETORES

    Acesso à fonteDOIHow to cite
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    • ABNT

      ARJONA RAMÍREZ, Miguel. Intra-predictive switched split vector quantization of speech spectra. IEEE Signal Processing Letters, v. 20, n. 8, p. 791-794, 2013Tradução . . Disponível em: https://doi.org/10.1109/LSP.2013.2267391. Acesso em: 14 jun. 2025.

    • APA

      Arjona Ramírez, M. (2013). Intra-predictive switched split vector quantization of speech spectra. IEEE Signal Processing Letters, 20( 8), 791-794. doi:10.1109/LSP.2013.2267391

    • NLM

      Arjona Ramírez M. Intra-predictive switched split vector quantization of speech spectra [Internet]. IEEE Signal Processing Letters. 2013 ; 20( 8): 791-794.[citado 2025 jun. 14 ] Available from: https://doi.org/10.1109/LSP.2013.2267391

    • Vancouver

      Arjona Ramírez M. Intra-predictive switched split vector quantization of speech spectra [Internet]. IEEE Signal Processing Letters. 2013 ; 20( 8): 791-794.[citado 2025 jun. 14 ] Available from: https://doi.org/10.1109/LSP.2013.2267391

  • Curadoria

    Congresso de Engenharia de Áudio da AES-Brasil, 11. Convenção Nacional AES Brasil, 17 (2013)

    Faria, Regis Rossi Alves (cur); Queiroz, Marcelo Gomes de (cur) ; Arjona Ramírez, Miguel (cur) ; Burt, Phillip Mark Seymour (cur)

    Unidades: IME, EP, FFCLRP

    Subjects: PROCESSAMENTO DE SINAIS ACÚSTICOS (CONGRESSOS), COMPUTAÇÃO MUSICAL (CONGRESSOS), ACÚSTICA (CONGRESSOS)

    How to cite
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    • ABNT

      Congresso de Engenharia de Áudio da AES-Brasil, 11. Convenção Nacional AES Brasil, 17. . Rio de Janeiro: Sociedade de Engenharia de Áudio. . Acesso em: 14 jun. 2025. , 2013

    • APA

      Congresso de Engenharia de Áudio da AES-Brasil, 11. Convenção Nacional AES Brasil, 17. (2013). Congresso de Engenharia de Áudio da AES-Brasil, 11. Convenção Nacional AES Brasil, 17. Rio de Janeiro: Sociedade de Engenharia de Áudio.

    • NLM

      Congresso de Engenharia de Áudio da AES-Brasil, 11. Convenção Nacional AES Brasil, 17. 2013 ;[citado 2025 jun. 14 ]

    • Vancouver

      Congresso de Engenharia de Áudio da AES-Brasil, 11. Convenção Nacional AES Brasil, 17. 2013 ;[citado 2025 jun. 14 ]

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