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Readme, code structure, refactoring.
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| ## Code Structure | ||
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| ``` | ||
| Root | ||
| ║ | ||
| ╠═ train.py <- main file used for training of models | ||
| ╠═ synthesize.py <- file for synthesis of spectrograms using checkpoints | ||
| ╠═ gta.py <- script for generating ground-truth-aligned spectrograms | ||
| ╠═ utils | ||
| ║ ├── __init__.py <- various useful rutines: build model, move to GPU, mask by lengths | ||
| ║ ├── audio.py <- functions for audio processing, e.g., loading, spectrograms, mfcc, ... | ||
| ║ ├── logging.py <- Tensorboard logger, logs spectrograms, alignments, audios, texts, ... | ||
| ║ ├── samplers.py <- batch samplers to produce balanced batches w.r.t languages, speakers | ||
| ║ └── text.py <- text rutines: conversion to IDs, punctuation stripping, phonemicization | ||
| ╠═ params | ||
| ║ ├── params <- definition of default hyperparameters and their description | ||
| ║ ├── singles <- multiple files with parameter settings for training of monolingual models | ||
| ║ └── ... <- multiple files with parameter settings for training of multilingual models | ||
| ╠═ notebooks | ||
| ║ ├── analyze.ipynb <- basic dataset analysis for inspection of its properties and data distributions, with plots | ||
| ║ ├── audio_test.ipynb <- experiments with audio processing and synthesis | ||
| ║ ├── encoder_analyze.ipynb <- analysis of encoder outputs, speaker and language embeddings with plots | ||
| ║ ├── code_switching_demo.ipynb <- code-switching synthesis demo | ||
| ║ └── multi_training_demo.ipynb <- multilingual training demo | ||
| ╠═ modules | ||
| ║ ├── attention.py <- attention modules: location-sensitive att., forward att., and base class | ||
| ║ ├── cbhg.py <- CBGH module known from Tacotron 1 with simple highway layer (not convolutional) | ||
| ║ ├── classifier.py <- adversarial classifier with gradient reversal layer, cosine similarity classifier | ||
| ║ ├── encoder.py <- multiple encoder architectures: convolutional, recurrent, generated, separate, shared | ||
| ║ ├── generated.py <- meta-generated layers: 1d convolution, batch normalization | ||
| ║ ├── layers.py <- regularized LSTMs (dropout, zoneout), convolutional block and highway convolutional blocks | ||
| ║ └── tacotron2.py <- implementation of Tacotron 2 with all its modules and loss functions | ||
| ╠═ evaluation | ||
| ║ ├── code-switched <- code-switching evaluation sentences | ||
| ║ ├── in-domain <- in-domain (i.e., from CSS10) monolingual evaluation sentences | ||
| ║ ├── out-domain <- in-domain (i.e., from Wikipedia) monolingual evaluation sentences in ten languages | ||
| ║ ├── asr_request.py <- script for scraping transcription of given audios from Google Cloud ASR | ||
| ║ ├── cer_computer.py <- script for calculating character error rate between transcripts pairs | ||
| ║ └── mcd_request.py <- script for getting mel cepstral distortion between two spectrograms (includes DTW) | ||
| ╠═ dataset_prepare | ||
| ║ ├── mecab_convertor.py <- romanization of Japanese script | ||
| ║ ├── pinyin_convertor.py <- romanization of Chinese script | ||
| ║ ├── normalize_comvoi.sh <- basic shell script for downloading, extracting and cleaning od some Common Voice data | ||
| ║ ├── normalize_css10.sh <- set of regular expressions for cleaning CSS10 dataset transcripts | ||
| ║ └── normalize_mailabs.sh <- probably not complete set of reg. exp.s for cleaning M-AILABS dataset transcripts | ||
| ╠═ dataset | ||
| ║ ├── dataset.py <- TTS dataset, contains mel and linear spec., texts, phonemes, speaker and language IDs and a | ||
| ║ │ function for generating proper meta-files and spectrograms for some datasets (see loaders.py) | ||
| ║ └── loaders.py <- methods for loading popular TTS datasets into standardized python list (see dataset.py above) | ||
| ╚═ data | ||
| ├── comvoi_clean | ||
| │ ├── all.txt <- prepared meta-file for cleaned Common Voice dataset | ||
| │ └── silence.sh <- script for removal of leading or trailing "silence" of Common Voice audios | ||
| ├── css10 | ||
| │ ├── train.txt <- prepared meta-file for training set of cleaned CSS10 dataset | ||
| │ └── val.txt <- prepared meta-file for validation set of cleaned CSS10 dataset | ||
| ├── css_comvoi | ||
| │ ├── train.txt <- prepared meta-file for training set of dataset which is mixture of CSS10 and CV | ||
| │ └── val.txt <- prepared meta-file for validation set of dataset which is mixture of CSS10 and CV | ||
| └── prepare_css_spectrograms.py <- ad-hoc script for generating linear and mel spectrograms, see README.md | ||
| ``` |
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