Pinned Repositories
AccoMontage2
Chord and accompaniment generator, pure python package that generate chord progression and accompaniment according to given melodies. Code for paper AccoMontage2: A Complete Harmonization and Accompaniment Arrangement System.
denoiser
Real Time Speech Enhancement in the Waveform Domain (Interspeech 2020)We provide a PyTorch implementation of the paper Real Time Speech Enhancement in the Waveform Domain. In which, we present a causal speech enhancement model working on the raw waveform that runs in real-time on a laptop CPU. The proposed model is based on an encoder-decoder architecture with skip-connections. It is optimized on both time and frequency domains, using multiple loss functions. Empirical evidence shows that it is capable of removing various kinds of background noise including stationary and non-stationary noises, as well as room reverb. Additionally, we suggest a set of data augmentation techniques applied directly on the raw waveform which further improve model performance and its generalization abilities.
NeuralSVB
Learning the Beauty in Songs: Neural Singing Voice Beautifier; ACL 2022 (Main conference); Official code
ParallelWaveGAN
Unofficial Parallel WaveGAN (+ MelGAN & Multi-band MelGAN & HiFi-GAN & StyleMelGAN) with Pytorch
person_detect
SpeechAlgorithms
Speech Algorithms Collections
megatts2
Unoffical implementation of Megatts2
WeTextProcessing
Text Normalization & Inverse Text Normalization
AccoMontage-3
Code and demo for paper: Zhao et al., AccoMontage-3: Full-Band Accompaniment Arrangement via Sequential Style Transfer and Multi-Track Function Prior.
1319224734's Repositories
1319224734/AccoMontage2
Chord and accompaniment generator, pure python package that generate chord progression and accompaniment according to given melodies. Code for paper AccoMontage2: A Complete Harmonization and Accompaniment Arrangement System.
1319224734/denoiser
Real Time Speech Enhancement in the Waveform Domain (Interspeech 2020)We provide a PyTorch implementation of the paper Real Time Speech Enhancement in the Waveform Domain. In which, we present a causal speech enhancement model working on the raw waveform that runs in real-time on a laptop CPU. The proposed model is based on an encoder-decoder architecture with skip-connections. It is optimized on both time and frequency domains, using multiple loss functions. Empirical evidence shows that it is capable of removing various kinds of background noise including stationary and non-stationary noises, as well as room reverb. Additionally, we suggest a set of data augmentation techniques applied directly on the raw waveform which further improve model performance and its generalization abilities.
1319224734/NeuralSVB
Learning the Beauty in Songs: Neural Singing Voice Beautifier; ACL 2022 (Main conference); Official code
1319224734/ParallelWaveGAN
Unofficial Parallel WaveGAN (+ MelGAN & Multi-band MelGAN & HiFi-GAN & StyleMelGAN) with Pytorch
1319224734/person_detect
1319224734/SpeechAlgorithms
Speech Algorithms Collections