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Wave-U-Net: A Multi-Scale Neural Network for End-to-End Audio Source Separation
TLDR
The Wave-U-Net is proposed, an adaptation of the U-Net to the one-dimensional time domain, which repeatedly resamples feature maps to compute and combine features at different time scales and indicates that its architecture yields a performance comparable to a state-of-the-art spectrogram-based U- net architecture, given the same data.
ONSET DETECTION REVISITED
Various methods have been proposed for detecting the onset times of musical notes in audio signals. We examine recent work on onset detection using spectral features such as the magnitude, phase and
Automatic Extraction of Tempo and Beat From Expressive Performances
TLDR
It is shown that estimating the perceptual salience of rhythmic events significantly improves the results of a computer program which is able to estimate the tempo and the times of musical beats in expressively performed music.
An experimental comparison of audio tempo induction algorithms
TLDR
One conclusion is that robust tempo induction entails the processing of frame features rather than that of onset lists, and a new "redundant" approach to tempo induction is proposed, inspired by knowledge of human perceptual mechanisms.
Evaluation of the Audio Beat Tracking System BeatRoot
TLDR
Improvements to the original BeatRoot system and a large-scale evaluation and analysis of the system's performance are described, with results compared with other evaluations such as the MIREX 2006 Audio Beat Tracking Evaluation.
LIVE TRACKING OF MUSICAL PERFORMANCES USING ON-LINE TIME WARPING
TLDR
A novel on-line time warping algorithm which has linear time and space costs, and performs incremental alignment of two series as one is received in real time, which is applied to the alignment of audio signals in order to follow musical performances of arbitrary length.
Evaluating Rhythmic descriptors for Musical Genre Classification
TLDR
This article considers a specific set of rhythmic descriptors for which it provides procedures of automatic extraction from audio signals and concludes on the particular relevance of the tempo and a set of 15 MFCC-like descriptors.
An End-to-End Neural Network for Polyphonic Piano Music Transcription
TLDR
An efficient variant of beam search is presented that improves performance and reduces run-times by an order of magnitude, making the model suitable for real-time applications.
PYIN: A fundamental frequency estimator using probabilistic threshold distributions
TLDR
The Probabilistic YIN (PYIN) algorithm is proposed, a modification of the well-known YIN algorithm for fundamental frequency (F0) estimation that is modified to output multiple pitch candidates with associated probabilities from a prior distribution on the YIN threshold parameter.
Approximate Note Transcription for the Improved Identification of Difficult Chords
TLDR
This paper seeks to find chroma features that are more suitable for usage in a musically-motivated model by performing a prior approximate transcription using an existing technique to solve non-negative least squares problems (NNLS).
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