The simulation works have accelerated the procedures of re-engineering and understanding of the electric hearing. Channel vocoders with noise or sine-wave carriers are mostly popular among the methods. Many acoustic modelling methods have been developed for simulation purposes, e.g., to predict the performance of a novel sound coding strategy. Simulating the electric hearing process of CI users through NH listeners is an important step in CI research and development. The electric hearing mimics the normal acoustic hearing (NH), but with a different physical interface to the neural system, which limits the performance of CI devices. In this unique way, deaf people can (re)gain a sense of hearing and consequent speech communication abilities. Modern cochlear implants (CIs) generate electric current pulsatile stimuli from real-time incoming to stimulate residual auditory nerves of deaf ears. As such, it is a useful resource for a wide variety of MIR applications, from those that target the complete audio-to-score Automatic Music Transcription task, to others that target more specific aspects (e.g., key signature estimation and beat or downbeat tracking from both MIDI and audio representations). The dataset itself is, to our knowledge, the largest that includes an alignment of music scores to MIDI and audio performance data. Musical transcriptions manual#ASAP has been obtained thanks to a new annotation workflow that combines score analysis and alignment algorithms, with the goal of reducing the time for manual annotation. Scores and performances are aligned with downbeat, beat, time signature, and key signature annotations. The scores are provided as paired MusicXML files and quantized MIDI files, and the performances as paired MIDI files and partially as audio recordings. In this paper we present Aligned Scores and Performances (ASAP): a new dataset of 222 digital musical scores aligned with 1068 performances (more than 92 hours) of Western classical piano music. Musical transcriptions how to#We show how to combine the improved Shuffle-Exchange network with convolutional layers, establishing it as a useful building block in long sequence processing applications. It surpasses the Shuffle-Exchange network on the LAMBADA language modelling task and achieves state-of-the-art performance on the MusicNet dataset for music transcription while being efficient in the number of parameters. The proposed architecture not only scales to longer sequences but also converges faster and provides better accuracy. In this paper, we present a simple and lightweight variant of the Shuffle-Exchange network, which is based on a residual network employing GELU and Layer Normalization. The model, however, is quite complex, involving a sophisticated gating mechanism derived from the Gated Recurrent Unit. The recently introduced neural Shuffle-Exchange network offers a computation-efficient alternative, enabling the modelling of long-range dependencies in O(n log n) time. Finally, we propose future work to be extended on the dataset.Īttention is a commonly used mechanism in sequence processing, but it is of O(n^2) complexity which prevents its application to long sequences. We analyze the statistics in different aspects to demonstrate the variety of PTs played in HuQin subcategories and perform preliminary experiments to show the potential applications of the dataset in various MIR tasks and cross-cultural music studies. Then we introduce the dataset creation methodology and highlight the annotation principles featuring PTs. We systematically describe the HuQin PT taxonomy based on musicological theory and practical use cases. In this paper, we present a multimodal performance dataset of HuQin music that contains audio-visual recordings of 11,992 single PT clips and 57 annotated musical pieces of classical excerpts. The complex applied techniques make HuQin music a challenging source for fundamental MIR tasks such as pitch analysis, transcription and score-audio alignment. Playing techniques(PTs) embodied in various playing styles add abundant emotional coloring and aesthetic feelings to HuQin performance. HuQin is a family of traditional Chinese bowed string instruments.
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