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Found 38 papers, 18 papers with code
Removing Speaker Information from Speech Representation using Variable-Length Soft Pooling
Recently, there have been efforts to encode the linguistic information of speech using a self-supervised framework for speech synthesis.
Learning Semantic Information from Raw Audio Signal Using Both Contextual and Phonetic Representations
We propose a framework to learn semantics from raw audio signals using two types of representations, encoding contextual and phonetic information respectively.
Music Auto-Tagging with Robust Music Representation Learned via Domain Adversarial Training
Music auto-tagging is crucial for enhancing music discovery and recommendation.
DDD: A Perceptually Superior Low-Response-Time DNN-based Declipper
Clipping is a common nonlinear distortion that occurs whenever the input or output of an audio system exceeds the supported range.
Inverse Nonlinearity Compensation of Hyperelastic Deformation in Dielectric Elastomer for Acoustic Actuation
This paper delves into the analysis of nonlinear deformation induced by dielectric actuation in pre-stressed ideal dielectric elastomers.
Combinatorial music generation model with song structure graph analysis
In this work, we propose a symbolic music generation model with the song structure graph analysis network.
Beat-Aligned Spectrogram-to-Sequence Generation of Rhythm-Game Charts
In the heart of "rhythm games" - games where players must perform actions in sync with a piece of music - are "charts", the directives to be given to players.
Exploiting Time-Frequency Conformers for Music Audio Enhancement
With the proliferation of video platforms on the internet, recording musical performances by mobile devices has become commonplace.
Self-refining of Pseudo Labels for Music Source Separation with Noisy Labeled Data
Music source separation (MSS) faces challenges due to the limited availability of correctly-labeled individual instrument tracks.
Debiased Automatic Speech Recognition for Dysarthric Speech via Sample Reweighting with Sample Affinity Test
Since ERM utilizes the averaged performance on the data samples regardless of a group such as healthy or dysarthric speakers, ASR systems are unaware of the performance disparities across the groups.
Show Me the Instruments: Musical Instrument Retrieval from Mixture Audio
The Single-Instrument Encoder is trained to classify the instruments used in single-track audio, and we take its penultimate layer's activation as the instrument embedding.
MedleyVox: An Evaluation Dataset for Multiple Singing Voices Separation
Second, to overcome the absence of existing multi-singing datasets for a training purpose, we present a strategy for construction of multiple singing mixtures using various single-singing datasets.
Semi-supervised learning for continuous emotional intensity controllable speech synthesis with disentangled representations
However, the emotional latent space generated from the existing models is difficult to control the continuous emotional intensity because of the entanglement of features like emotions, speakers, etc.
Music Mixing Style Transfer: A Contrastive Learning Approach to Disentangle Audio Effects
We propose an end-to-end music mixing style transfer system that converts the mixing style of an input multitrack to that of a reference song.
Pop2Piano : Pop Audio-based Piano Cover Generation
Piano covers of pop music are enjoyed by many people.
Neural Fourier Shift for Binaural Speech Rendering
We present a neural network for rendering binaural speech from given monaural audio, position, and orientation of the source.
Exploring Train and Test-Time Augmentations for Audio-Language Learning
In this paper, we aim to unveil the impact of data augmentation in audio-language multi-modal learning, which has not been explored despite its importance.
Ranked #2 on
Audio to Text Retrieval
on AudioCaps
Exploiting Negative Preference in Content-based Music Recommendation with Contrastive Learning
Advanced music recommendation systems are being introduced along with the development of machine learning.
Representation Selective Self-distillation and wav2vec 2.0 Feature Exploration for Spoof-aware Speaker Verification
Our study allows us to analyze which attribute of speech signals is advantageous for the CM systems.
Global HRTF Interpolation via Learned Affine Transformation of Hyper-conditioned Features
Especially for the data-driven approaches, existing HRTF datasets differ in spatial sampling distributions of source positions, posing a major problem when generalizing the method across multiple datasets.
End-to-end Music Remastering System Using Self-supervised and Adversarial Training
Mastering is an essential step in music production, but it is also a challenging task that has to go through the hands of experienced audio engineers, where they adjust tone, space, and volume of a song.
Neural Analysis and Synthesis: Reconstructing Speech from Self-Supervised Representations
We present a neural analysis and synthesis (NANSY) framework that can manipulate voice, pitch, and speed of an arbitrary speech signal.
Reverb Conversion of Mixed Vocal Tracks Using an End-to-end Convolutional Deep Neural Network
This method enables us to apply the reverb of the reference track to the source track to which the effect is desired.
Real-time Denoising and Dereverberation with Tiny Recurrent U-Net
Modern deep learning-based models have seen outstanding performance improvement with speech enhancement tasks.
Neural Audio Fingerprint for High-specific Audio Retrieval based on Contrastive Learning
Most of existing audio fingerprinting systems have limitations to be used for high-specific audio retrieval at scale.
Exploiting Multi-Modal Features From Pre-trained Networks for Alzheimer's Dementia Recognition
In this work, we exploit various multi-modal features extracted from pre-trained networks to recognize Alzheimer's Dementia using a neural network, with a small dataset provided by the ADReSS Challenge at INTERSPEECH 2020.
From Inference to Generation: End-to-end Fully Self-supervised Generation of Human Face from Speech
We analyze the extent to which the network can naturally disentangle two latent factors that contribute to the generation of a face image - one that comes directly from a speech signal and the other that is not related to it - and explore whether the network can learn to generate natural human face image distribution by modeling these factors.
VirtuosoNet: A Hierarchical RNN-based System for Modeling Expressive Piano Performance
In this paper, we present our application of deep neural network to modeling piano performance, which imitates the expressive control of tempo, dynamics, articulations and pedaling from pianists.
Disentangling Timbre and Singing Style with Multi-singer Singing Synthesis System
In this study, we define the identity of the singer with two independent concepts - timbre and singing style - and propose a multi-singer singing synthesis system that can model them separately.
Sound Audio and Speech Processing
Adversarially Trained End-to-end Korean Singing Voice Synthesis System
In this paper, we propose an end-to-end Korean singing voice synthesis system from lyrics and a symbolic melody using the following three novel approaches: 1) phonetic enhancement masking, 2) local conditioning of text and pitch to the super-resolution network, and 3) conditional adversarial training.
Sound Audio and Speech Processing
Phase-aware Speech Enhancement with Deep Complex U-Net
Most deep learning-based models for speech enhancement have mainly focused on estimating the magnitude of spectrogram while reusing the phase from noisy speech for reconstruction.
Sequential Skip Prediction with Few-shot in Streamed Music Contents
This paper provides an outline of the algorithms submitted for the WSDM Cup 2019 Spotify Sequential Skip Prediction Challenge (team name: mimbres).
Ranked #1 on
Sequential skip prediction
on MSSD
Music Source Separation Using Stacked Hourglass Networks
In this paper, we propose a simple yet effective method for multiple music source separation using convolutional neural networks.
Sound Audio and Speech Processing
Chord Generation from Symbolic Melody Using BLSTM Networks
Generating a chord progression from a monophonic melody is a challenging problem because a chord progression requires a series of layered notes played simultaneously.
Audio Cover Song Identification using Convolutional Neural Network
To do this, we first build the CNN using as an input a cross-similarity matrix generated from a pair of songs.
Lyrics-to-Audio Alignment by Unsupervised Discovery of Repetitive Patterns in Vowel Acoustics
Most of the previous approaches to lyrics-to-audio alignment used a pre-developed automatic speech recognition (ASR) system that innately suffered from several difficulties to adapt the speech model to individual singers.
Automatic Speech Recognition
Automatic Speech Recognition (ASR)
+1
Deep convolutional neural networks for predominant instrument recognition in polyphonic music
We train our network from fixed-length music excerpts with a single-labeled predominant instrument and estimate an arbitrary number of predominant instruments from an audio signal with a variable length.
A Deep Bag-of-Features Model for Music Auto-Tagging
Feature learning and deep learning have drawn great attention in recent years as a way of transforming input data into more effective representations using learning algorithms.
