Official implementation of FCL-taco2: Fast, Controllable and Lightweight version of Tacotron2 @ ICASSP 2021

Overview

FCL-Taco2: Towards Fast, Controllable and Lightweight Text-to-Speech synthesis (ICASSP 2021) Paper | Demo

Block diagram of FCL-taco2, where the decoder generates mel-spectrograms in AR mode within each phoneme and is shared for all phonemes.

💬 Huawei Noah's Ark Lab is recruiting interns on speech processing fields, if you're interested, you're welcome to contact Dr. Deng: [email protected]

Training and inference scripts for FCL-taco2

Environment

  • python 3.6.10
  • torch 1.3.1
  • chainer 6.0.0
  • espnet 8.0.0
  • apex 0.1
  • numpy 1.19.1
  • kaldiio 2.15.1
  • librosa 0.8.0

Training and inference:

  • Step1. Data preparation & preprocessing
  1. Download LJSpeech

  2. Unpack downloaded LJSpeech-1.1.tar.bz2 to /xx/LJSpeech-1.1

  3. Obtain the forced alignment information by using Montreal forced aligner tool. Or you can download our alignment results, then unpack it to /xx/TextGrid

  4. Preprocess the dataset to extract mel-spectrograms, phoneme duration, pitch, energy and phoneme sequence by:

     python preprocessing.py --data-root /xx/LJSpeech-1.1 --textgrid-root /xx/TextGrid
    
  • Step2. Model training
  1. Training teacher model FCL-taco2-T:

     ./teacher_model_training.sh
    
  2. Training student model FCL-taco2-S:

     ./student_model_training.sh
    
  3. Parallel-WaveGAN vocoder training: follow instructions at here. You can also download the pre-trained PWG vocoder, and put the PWG model under the directory "vocoder".

  • Step3. Model evaluation
  1. FCL-taco2-T evaluation:

     ./inference_teacher.sh
    
  2. FCL-taco2-S evaluation:

     ./inference_student.sh
    

Citation

If the code is used in your research, please star our repo and cite our paper:

@inproceedings{wang2021fcl,
  title={Fcl-Taco2: Towards Fast, Controllable and Lightweight Text-to-Speech Synthesis},
  author={Wang, Disong and Deng, Liqun and Zhang, Yang and Zheng, Nianzu and Yeung, Yu Ting and Chen, Xiao and Liu, Xunying and Meng, Helen},
  booktitle={ICASSP 2021-2021 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP)},
  pages={5714--5718},
  year={2021},
  organization={IEEE}
}
Owner
Disong Wang
PhD student @ CUHK, focus on voice conversion, speech synthesis, speech recognition, etc.
Disong Wang
Face Mask Detection system based on computer vision and deep learning using OpenCV and Tensorflow/Keras

Face Mask Detection Face Mask Detection System built with OpenCV, Keras/TensorFlow using Deep Learning and Computer Vision concepts in order to detect

Chandrika Deb 1.4k Jan 03, 2023
ICCV2021 - A New Journey from SDRTV to HDRTV.

ICCV2021 - A New Journey from SDRTV to HDRTV.

XyChen 82 Dec 27, 2022
Implementation of temporal pooling methods studied in [ICIP'20] A Comparative Evaluation Of Temporal Pooling Methods For Blind Video Quality Assessment

Implementation of temporal pooling methods studied in [ICIP'20] A Comparative Evaluation Of Temporal Pooling Methods For Blind Video Quality Assessment

Zhengzhong Tu 5 Sep 16, 2022
[CVPR'21] Locally Aware Piecewise Transformation Fields for 3D Human Mesh Registration

Locally Aware Piecewise Transformation Fields for 3D Human Mesh Registration This repository contains the implementation of our paper Locally Aware Pi

sfwang 70 Dec 19, 2022
Semantic segmentation models, datasets and losses implemented in PyTorch.

Semantic Segmentation in PyTorch Semantic Segmentation in PyTorch Requirements Main Features Models Datasets Losses Learning rate schedulers Data augm

Yassine 1.3k Jan 07, 2023
Official implementation of Self-supervised Image-to-text and Text-to-image Synthesis

Self-supervised Image-to-text and Text-to-image Synthesis This is the official implementation of Self-supervised Image-to-text and Text-to-image Synth

6 Jul 31, 2022
Multi-Stage Spatial-Temporal Convolutional Neural Network (MS-GCN)

Multi-Stage Spatial-Temporal Convolutional Neural Network (MS-GCN) This code implements the skeleton-based action segmentation MS-GCN model from Autom

Benjamin Filtjens 8 Nov 29, 2022
Scale-aware Automatic Augmentation for Object Detection (CVPR 2021)

SA-AutoAug Scale-aware Automatic Augmentation for Object Detection Yukang Chen, Yanwei Li, Tao Kong, Lu Qi, Ruihang Chu, Lei Li, Jiaya Jia [Paper] [Bi

DV Lab 182 Dec 29, 2022
Fibonacci Method Gradient Descent

An implementation of the Fibonacci method for gradient descent, featuring a TKinter GUI for inputting the function / parameters to be examined and a matplotlib plot of the function and results.

Emma 1 Jan 28, 2022
Simulating Sycamore quantum circuits classically using tensor network algorithm.

Simulating the Sycamore quantum supremacy circuit This repo contains data we have obtained in simulating the Sycamore quantum supremacy circuits with

Feng Pan 46 Nov 17, 2022
A self-supervised 3D representation learning framework named viewpoint bottleneck.

Pointly-supervised 3D Scene Parsing with Viewpoint Bottleneck Paper Created by Liyi Luo, Beiwen Tian, Hao Zhao and Guyue Zhou from Institute for AI In

63 Aug 11, 2022
PyTorch implementation of Spiking Neural Networks trained on surrogate gradient & BPTT using snntorch.

snn-localization repo PyTorch implementation of Spiking Neural Networks trained on surrogate gradient & BPTT using snntorch. Install Dependencies Orig

Sami BARCHID 1 Jan 06, 2022
This project is the PyTorch implementation of our CVPR 2022 paper:

Requirements and Dependency Install PyTorch with CUDA (for GPU). (Experiments are validated on python 3.8.11 and pytorch 1.7.0) (For visualization if

Lei Huang 23 Nov 29, 2022
Python package to add text to images, textures and different backgrounds

nider Python package for text images generation and watermarking Free software: MIT license Documentation: https://nider.readthedocs.io. nider is an a

Vladyslav Ovchynnykov 131 Dec 30, 2022
PyTorch version repo for CSRNet: Dilated Convolutional Neural Networks for Understanding the Highly Congested Scenes

Study-CSRNet-pytorch This is the PyTorch version repo for CSRNet: Dilated Convolutional Neural Networks for Understanding the Highly Congested Scenes

0 Mar 01, 2022
SOLO and SOLOv2 for instance segmentation, ECCV 2020 & NeurIPS 2020.

SOLO: Segmenting Objects by Locations This project hosts the code for implementing the SOLO algorithms for instance segmentation. SOLO: Segmenting Obj

Xinlong Wang 1.5k Dec 31, 2022
Implementation of a protein autoregressive language model, but with autoregressive infilling objective (editing subsequences capability)

Protein GLM (wip) Implementation of a protein autoregressive language model, but with autoregressive infilling objective (editing subsequences capabil

Phil Wang 17 May 06, 2022
shufflev2-yolov5:lighter, faster and easier to deploy

shufflev2-yolov5: lighter, faster and easier to deploy. Evolved from yolov5 and the size of model is only 1.7M (int8) and 3.3M (fp16). It can reach 10+ FPS on the Raspberry Pi 4B when the input size

pogg 1.5k Jan 05, 2023
Tutoriais publicados nas nossas redes sociais para obtenção de dados, análises simples e outras tarefas relevantes no mercado financeiro.

Tutoriais Públicos Tutoriais publicados nas nossas redes sociais para obtenção de dados, análises simples e outras tarefas relevantes no mercado finan

Trading com Dados 68 Oct 15, 2022
multimodal transformer

This repo holds the code to perform experiments with the multimodal autoregressive probabilistic model Transflower. Overview of the repo It is structu

Guillermo Valle 68 Dec 13, 2022