Audio Synthesis
44 papers with code • 1 benchmarks • 2 datasets
Benchmarks
These leaderboards are used to track progress in Audio Synthesis
| Trend | Dataset | Best Model | Paper | Code | Compare |
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Libraries
Use these libraries to find Audio Synthesis models and implementations
Trinity Speech-Gesture Dataset
Most implemented papers
An Empirical Evaluation of Generic Convolutional and Recurrent Networks for Sequence Modeling
locuslab/TCN
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Our results indicate that a simple convolutional architecture outperforms canonical recurrent networks such as LSTMs across a diverse range of tasks and datasets, while demonstrating longer effective memory.
Tacotron: Towards End-to-End Speech Synthesis
CorentinJ/Real-Time-Voice-Cloning
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A text-to-speech synthesis system typically consists of multiple stages, such as a text analysis frontend, an acoustic model and an audio synthesis module.
Adversarial Audio Synthesis
chrisdonahue/wavegan
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ICLR 2019
Audio signals are sampled at high temporal resolutions, and learning to synthesize audio requires capturing structure across a range of timescales.
Efficient Neural Audio Synthesis
CorentinJ/Real-Time-Voice-Cloning
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ICML 2018
The small number of weights in a Sparse WaveRNN makes it possible to sample high-fidelity audio on a mobile CPU in real time.
DiffWave: A Versatile Diffusion Model for Audio Synthesis
lmnt-com/diffwave
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ICLR 2021
In this work, we propose DiffWave, a versatile diffusion probabilistic model for conditional and unconditional waveform generation.
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.
Neural Audio Synthesis of Musical Notes with WaveNet Autoencoders
facebookresearch/SING
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ICML 2017
Generative models in vision have seen rapid progress due to algorithmic improvements and the availability of high-quality image datasets.
GANSynth: Adversarial Neural Audio Synthesis
tensorflow/magenta
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ICLR 2019
Efficient audio synthesis is an inherently difficult machine learning task, as human perception is sensitive to both global structure and fine-scale waveform coherence.
CSDI: Conditional Score-based Diffusion Models for Probabilistic Time Series Imputation
ermongroup/csdi
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NeurIPS 2021
In this paper, we propose Conditional Score-based Diffusion models for Imputation (CSDI), a novel time series imputation method that utilizes score-based diffusion models conditioned on observed data.
Deep Voice: Real-time Neural Text-to-Speech
NVIDIA/nv-wavenet
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ICML 2017
We present Deep Voice, a production-quality text-to-speech system constructed entirely from deep neural networks.
