Zobrazeno 1 - 10
of 12
pro vyhledávání: '"Majid Mirbagheri"'
Publikováno v:
Journal of Materials Research. 37:3575-3586
Publikováno v:
ICASSP 2023 - 2023 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP).
Publikováno v:
Journal of Materials Engineering and Performance. 31:3535-3549
Publikováno v:
IEEE/ACM Transactions on Audio, Speech, and Language Processing. 26:415-421
Linear time-varying (LTV) regression models play a central role in input–output analysis of many real-world dynamical systems. Most existing models for such systems consider either a switching dynamics with a discrete latent variable driving the sy
Autor:
Tyler Kekona, Adrian K. C. Lee, Rose Sloan, Bradley Ekin, Chunxi Liu, Majid Mirbagheri, Daniel McCloy, Preethi Jyothi, Paul Hager, Amit Das, Edmund C. Lalor, Giovanni M. Di Liberto, Vimal Manohar, Nancy F. Chen, Mark Hasegawa-Johnson, Hao Tang
Publikováno v:
IEEE/ACM Transactions on Audio, Speech, and Language Processing. 25:50-63
In many under-resourced languages it is possible to find text, and it is possible to find speech, but transcribed speech suitable for training automatic speech recognition ASR is unavailable. In the absence of native transcripts, this paper proposes
Publikováno v:
ICASSP
Auditory selective attention plays a central role in the human capacity to reliably process complex sounds in multi-source environments. Stimulus reconstruction has been widely used for the investigation of selective auditory attention using multicha
Publikováno v:
Interspeech 2012.
Autor:
Sri Harish Mallidi, Yuancheng Luo, Padmanabhan Rajan, Dmitry N. Zotkin, Sridhar Krishna Nemala, Ramani Duraiswami, Balaji Vasan Srinivasan, Xinhui Zhou, Shihab A. Shamma, Hynek Hermansky, Mounya Elhilali, Sriram Ganapathy, Samuel Thomas, Gsvs Sivaram, Daniel Garcia-Romero, Majid Mirbagheri, Thomas Janu, Nima Mesgarani
Publikováno v:
ICASSP
In recent years, there have been significant advances in the field of speaker recognition that has resulted in very robust recognition systems. The primary focus of many recent developments have shifted to the problem of recognizing speakers in adver
Publikováno v:
ICASSP
Linear-Nonlinear regression models play a fundamental role in characterizing nonlinear systems. In this paper, we propose a method to estimate the linear transform in such models equivalent to a subspace of a small dimension in the input space that i