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Found 23 papers, 15 papers with code
Differentiable All-pole Filters for Time-varying Audio Systems
Infinite impulse response filters are an essential building block of many time-varying audio systems, such as audio effects and synthesisers.
The Song Describer Dataset: a Corpus of Audio Captions for Music-and-Language Evaluation
We introduce the Song Describer dataset (SDD), a new crowdsourced corpus of high-quality audio-caption pairs, designed for the evaluation of music-and-language models.
Zero-Shot Duet Singing Voices Separation with Diffusion Models
In this paper, we examine this problem in the context of duet singing voices separation, and propose a method to enforce the coherency of singer identity by splitting the mixture into overlapping segments and performing posterior sampling in an auto-regressive manner, conditioning on the previous segment.
Fast Diffusion GAN Model for Symbolic Music Generation Controlled by Emotions
Diffusion models have shown promising results for a wide range of generative tasks with continuous data, such as image and audio synthesis.
Composer Style-specific Symbolic Music Generation Using Vector Quantized Discrete Diffusion Models
The diffusion model is trained to generate intermediate music sequences consisting of codebook indexes, which are then decoded to symbolic music using the VQ-VAE's decoder.
The Role of Communication and Reference Songs in the Mixing Process: Insights from Professional Mix Engineers
Effective music mixing requires technical and creative finesse, but clear communication with the client is crucial.
Singing Voice Synthesis Using Differentiable LPC and Glottal-Flow-Inspired Wavetables
This paper introduces GlOttal-flow LPC Filter (GOLF), a novel method for singing voice synthesis (SVS) that exploits the physical characteristics of the human voice using differentiable digital signal processing.
The Responsibility Problem in Neural Networks with Unordered Targets
We discuss the discontinuities that arise when mapping unordered objects to neural network outputs of fixed permutation, referred to as the responsibility problem.
Mesostructures: Beyond Spectrogram Loss in Differentiable Time-Frequency Analysis
Computer musicians refer to mesostructures as the intermediate levels of articulation between the microstructure of waveshapes and the macrostructure of musical forms.
Rigid-Body Sound Synthesis with Differentiable Modal Resonators
Physical models of rigid bodies are used for sound synthesis in applications from virtual environments to music production.
Conditioning and Sampling in Variational Diffusion Models for Speech Super-Resolution
Moreover, by coupling the proposed sampling method with an unconditional DM, i. e., a DM with no auxiliary inputs to its noise predictor, we can generalize it to a wide range of SR setups.
Sinusoidal Frequency Estimation by Gradient Descent
Sinusoidal parameter estimation is a fundamental task in applications from spectral analysis to time-series forecasting.
Contrastive Audio-Language Learning for Music
In this work, we explore cross-modal learning in an attempt to bridge audio and language in the music domain.
DoReMi: First glance at a universal OMR dataset
While we do not assume to have solved the main challenges in OMR, this dataset opens a new course of discussions that would ultimately aid that goal.
Neural Waveshaping Synthesis
We present the Neural Waveshaping Unit (NEWT): a novel, lightweight, fully causal approach to neural audio synthesis which operates directly in the waveform domain, with an accompanying optimisation (FastNEWT) for efficient CPU inference.
A Modulation Front-End for Music Audio Tagging
Modulation filter bank representations that have been actively researched as a basis for timbre perception have the potential to facilitate the extraction of perceptually salient features.
A novel dataset for the identification of computer generated melodies in the CSMT challenge
The aim of the dataset is to examine whether it is possible to distinguish computer generated melodies by learning the feature of generated melodies.
Optical Music Recognition: State of the Art and Major Challenges
In this paper, we review relevant works in OMR, including fundamental methods and significant outcomes, and highlight different stages of the OMR pipeline.
A Critical Look at the Applicability of Markov Logic Networks for Music Signal Analysis
In this paper, we analyse some proposed examples of MLNs for musical analysis and consider their practical disadvantages when compared to formulating the same musical dependence relationships as (dynamic) Bayesian networks.
A Feature Learning Siamese Model for Intelligent Control of the Dynamic Range Compressor
In this paper, a siamese DNN model is proposed to learn the characteristics of the audio dynamic range compressor (DRC).
A Tutorial on Deep Learning for Music Information Retrieval
Following their success in Computer Vision and other areas, deep learning techniques have recently become widely adopted in Music Information Retrieval (MIR) research.
A Comparison of Audio Signal Preprocessing Methods for Deep Neural Networks on Music Tagging
In this paper, we empirically investigate the effect of audio preprocessing on music tagging with deep neural networks.
Transfer learning for music classification and regression tasks
In this paper, we present a transfer learning approach for music classification and regression tasks.
