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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.
Detection and Classification of Acoustic Scenes and Events: Outcome of the DCASE 2016 Challenge
TLDR
The emergence of deep learning as the most popular classification method is observed, replacing the traditional approaches based on Gaussian mixture models and support vector machines.
Detection and classification of acoustic scenes and events: An IEEE AASP challenge
TLDR
An overview of systems submitted to the public evaluation challenge on acoustic scene classification and detection of sound events within a scene as well as a detailed evaluation of the results achieved by those systems are provided.
Automatic music transcription: challenges and future directions
TLDR
Limits of current transcription methods are analyzed and promising directions for future research are identified, including the integration of information from multiple algorithms and different musical aspects.
Detection and Classification of Acoustic Scenes and Events
TLDR
The state of the art in automatically classifying audio scenes, and automatically detecting and classifyingaudio events is reported on.
Automatic Music Transcription: An Overview
TLDR
The capability of transcribing music audio into music notation is a fascinating example of human intelligence and comprises several subtasks, including multipitch estimation (MPE), onset and offset detection, instrument recognition, beat and rhythm tracking, interpretation of expressive timing and dynamics, and score typesetting.
A Shift-Invariant Latent Variable Model for Automatic Music Transcription
TLDR
Results demonstrate that the proposed probabilistic model for multiple-instrument automatic music transcription outperforms leading approaches from the transcription literature, using several error metrics.
A database and challenge for acoustic scene classification and event detection
TLDR
This paper introduces a newly-launched public evaluation challenge dealing with two closely related tasks of the field: acoustic scene classification and event detection.
An Attack/Decay Model for Piano Transcription
We demonstrate that piano transcription performance for a known piano can be improved by explicitly modelling piano acoustical features. The proposed method is based on non-negative matrix
Roadmap for Music Information ReSearch
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