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Found 13 papers, 5 papers with code
Conjugate Distribution Laws in Cultural Evolution via Statistical Learning
Many cultural traits characterizing intelligent behaviors are now thought to be transmitted through statistical learning, motivating us to study its effects on cultural evolution.
Physics and Society Biological Physics
Tatum-Level Drum Transcription Based on a Convolutional Recurrent Neural Network with Language Model-Based Regularized Training
This paper describes a neural drum transcription method that detects from music signals the onset times of drums at the $\textit{tatum}$ level, where tatum times are assumed to be estimated in advance.
Semi-supervised Neural Chord Estimation Based on a Variational Autoencoder with Latent Chord Labels and Features
In contrast, we propose a unified generative and discriminative approach in the framework of amortized variational inference.
Multi-Step Chord Sequence Prediction Based on Aggregated Multi-Scale Encoder-Decoder Network
In this paper, we postulate that this comes from the multi-scale structure of musical information and propose new architectures based on an iterative temporal aggregation of input labels.
Musical Rhythm Transcription Based on Bayesian Piece-Specific Score Models Capturing Repetitions
Focusing on rhythm, we formulate several classes of Bayesian Markov models of musical scores that describe repetitions indirectly using the sparse transition probabilities of notes or note patterns.
Statistical Learning and Estimation of Piano Fingering
We find that the methods based on high-order HMMs outperform the other methods in terms of estimation accuracies.
Statistical Piano Reduction Controlling Performance Difficulty
We present a statistical-modelling method for piano reduction, i. e. converting an ensemble score into piano scores, that can control performance difficulty.
Generative Statistical Models with Self-Emergent Grammar of Chord Sequences
Generative statistical models of chord sequences play crucial roles in music processing.
Note Value Recognition for Piano Transcription Using Markov Random Fields
This paper presents a statistical method for use in music transcription that can estimate score times of note onsets and offsets from polyphonic MIDI performance signals.
Rhythm Transcription of Polyphonic Piano Music Based on Merged-Output HMM for Multiple Voices
In a recent conference paper, we have reported a rhythm transcription method based on a merged-output hidden Markov model (HMM) that explicitly describes the multiple-voice structure of polyphonic music.
Real-Time Audio-to-Score Alignment of Music Performances Containing Errors and Arbitrary Repeats and Skips
We confirmed real-time operation of the algorithms with music scores of practical length (around 10000 notes) on a modern laptop and their tracking ability to the input performance within 0. 7 s on average after repeats/skips in clarinet performance data.
Outer-Product Hidden Markov Model and Polyphonic MIDI Score Following
We present a polyphonic MIDI score-following algorithm capable of following performances with arbitrary repeats and skips, based on a probabilistic model of musical performances.
A Stochastic Temporal Model of Polyphonic MIDI Performance with Ornaments
We study indeterminacies in realization of ornaments and how they can be incorporated in a stochastic performance model applicable for music information processing such as score-performance matching.
