Zobrazeno 1 - 10
of 176
pro vyhledávání: '"Mark F. Bocko"'
Publikováno v:
Journal of Creative Music Systems, Vol 1, Iss 1 (2016)
In this article we discuss the importance of temporal information in assessing musical similarity and we present a content-based approach that emphasizes the sequential repetition of perceptually relevant, expressive musical features. To examine thes
Externí odkaz:
https://doaj.org/article/2124550602d34609a8e4d4a36aa2dbf4
Publikováno v:
Journal of the Audio Engineering Society. 70:1027-1037
Publikováno v:
ICASSP 2023 - 2023 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP).
Publikováno v:
Journal of Sound and Vibration. 553:117671
Publikováno v:
Journal of the Audio Engineering Society. 69:27-39
Autor:
Mark F. Bocko, Sahar Hashemgeloogerdi
Publikováno v:
IEEE/ACM Transactions on Audio, Speech, and Language Processing. 28:1260-1269
Acoustic feedback is a persistent problem in hearing aids, which limits the achievable amplification and may severely degrade the sound quality by producing howling artifacts. A potential approach to feedback cancellation is to estimate the feedback
Autor:
Mohammad Kazemi, Mark F. Bocko
Publikováno v:
Scientific Reports, Vol 9, Iss 1, Pp 1-9 (2019)
Scientific Reports
Scientific Reports
Spin-orbit electronics (spin-orbitronics) has been widely discussed for enabling nonvolatile devices that store and process information with low power consumption. The potential of spin-orbitronics for memory and logic applications has been demonstra
Publikováno v:
Journal of the Audio Engineering Society. 67:531-539
Publikováno v:
The Journal of the Acoustical Society of America. 150:A348-A349
Analysis of the coherence properties of the harmonic partials of speech and music signals recorded in an acoustic space provides information about the impulse response of the space. When an acoustic signal is filtered by a space, the autocorrelation
Autor:
Sahar Hashemgeloogerdi, Mark F. Bocko
Publikováno v:
IEEE Signal Processing Letters. 25:368-372
In adaptive feedback cancellation, the feedback path must be modeled precisely using as few adaptive parameters as possible to reduce computational complexity and enable rapid convergence. To reduce the number of adaptive parameters, the feedback pat