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Audio Generation

10 papers with code · Audio

Audio generation (synthesis) is the task of generating raw audio such as speech.

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Greatest papers with code

GANSynth: Adversarial Neural Audio Synthesis

ICLR 2019 tensorflow/magenta

Efficient audio synthesis is an inherently difficult machine learning task, as human perception is sensitive to both global structure and fine-scale waveform coherence.

AUDIO GENERATION

WaveNet: A Generative Model for Raw Audio

12 Sep 2016buriburisuri/speech-to-text-wavenet

This paper introduces WaveNet, a deep neural network for generating raw audio waveforms.

AUDIO GENERATION SPEECH SYNTHESIS

Generating Long Sequences with Sparse Transformers

Preprint 2019 openai/sparse_attention

Transformers are powerful sequence models, but require time and memory that grows quadratically with the sequence length.

AUDIO GENERATION IMAGE GENERATION LANGUAGE MODELLING

Adversarial Audio Synthesis

ICLR 2019 chrisdonahue/wavegan

Audio signals are sampled at high temporal resolutions, and learning to synthesize audio requires capturing structure across a range of timescales.

AUDIO GENERATION IMAGE GENERATION

SampleRNN: An Unconditional End-to-End Neural Audio Generation Model

22 Dec 2016soroushmehr/sampleRNN_ICLR2017

In this paper we propose a novel model for unconditional audio generation based on generating one audio sample at a time.

AUDIO GENERATION

Conditional WaveGAN

27 Sep 2018acheketa/cwavegan

Generative models are successfully used for image synthesis in the recent years.

AUDIO GENERATION

Smoothed Dilated Convolutions for Improved Dense Prediction

27 Aug 2018divelab/dilated

Unlike existing models, which explore solutions by focusing on a block of cascaded dilated convolutional layers, our methods address the gridding artifacts by smoothing the dilated convolution itself.

AUDIO GENERATION MACHINE TRANSLATION OBJECT DETECTION SEMANTIC SEGMENTATION

Blow: a single-scale hyperconditioned flow for non-parallel raw-audio voice conversion

3 Jun 2019joansj/blow

End-to-end models for raw audio generation are a challenge, specially if they have to work with non-parallel data, which is a desirable setup in many situations.

AUDIO GENERATION

Generative timbre spaces: regularizing variational auto-encoders with perceptual metrics

Conference 2018 acids-ircam/variational-timbre

Based on this, we introduce a method for descriptor-based synthesis and show that we can control the descriptors of an instrument while keeping its timbre structure.

AUDIO CLASSIFICATION AUDIO GENERATION MUSIC INFORMATION RETRIEVAL MUSIC MODELING

Assisted Sound Sample Generation with Musical Conditioning in Adversarial Auto-Encoders

12 Apr 2019acids-ircam/Timbre_MoVE

Its training data subsets can directly be visualized in the 3D latent representation.

AUDIO GENERATION