Composers may not provide instructions for playing their works, especially for instrument solos, and therefore, different musicians may give very different interpretations of the same work. Such differences usually lead to time, amplitude, or frequency variations of musical notes in a phrase in the signal point of view. This paper proposes a frame-based recursive regularization method for time-dependent analysis of each note presenting in solo violin recordings. The system of equations evolves when a new frame is added and an old frame is dropped to track the varying characteristics of violin playing. This method is compared with a time-dependent non-negative matrix factorization method. The complete recordings of both BWV 1005 No. 3 played by Kuijken and 24 Caprices op. 1 no. 24 in A minor played by Paganini are used for the transcription experiment, where the proposed method performs strongly. The analysis results of a short passage extracted from BWV 1005 No. 3 performed by three famous violinists reveal numerous differences in the styles and performances of these violinists.
Multicore processor provides large computation capability but also involves the complicate parallel programming. One of major considerations in parallel programming is the performance. Traditional design methodologies which usually start a design on a selected platform spend a lot of effort and time on tuning performance and debugging. When platform is changed even with different number of cores, considerable redesign effort is required. Hence a flexible design methodology is necessary.In this paper, a design methodology is presented for video codec, by using MPEG-4 SP decoder as an example, on multicore processor. The parallelisms of MPEG-4 decoder are discussed and exposed with the dataflow model. The dataflow model provides a high-level abstraction of underlying hardware. Computation and communication of MPEG-4 decoder are separated and represented as modules and channels, respectively. It is possible to synthesize the model targeting to either dedicate hardware or software on multiprocessor. To map the high level dataflow model to Cell processor, the mapping flow, including offline profiling, task allocation and runtime libraries, are developed. According to the profiling results, the allocation algorithm could allocate tasks on multiprocessors as balanced as possible. An efficient synchronization mechanism on Cell processor is also proposed. We also discuss the impact of the model and the mapping flow corresponding to decoding speed. The results show that the proposed methodology gets considerable performance boost when the number of cores is increased.
scite is a Brooklyn-based organization that helps researchers better discover and understand research articles through Smart Citations–citations that display the context of the citation and describe whether the article provides supporting or contrasting evidence. scite is used by students and researchers from around the world and is funded in part by the National Science Foundation and the National Institute on Drug Abuse of the National Institutes of Health.
hi@scite.ai
10624 S. Eastern Ave., Ste. A-614
Henderson, NV 89052, USA
Copyright © 2024 scite LLC. All rights reserved.
Made with 💙 for researchers
Part of the Research Solutions Family.