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# data_prep
This directory contains the following data preparation scripts:
1. MFA data preparation: Code for extracting phone alignments by Montréal Forced Aligner (MFA)
2. Style prompt data preparation: Code for preparing synthetic annotations of style prompts.
## 0. Download LibriTTS_R
Before running any scripts, be sure to put the [LibriTTS-R](https://www.openslr.org/141/) dataset to `./LibriTTS_R`. You must have the following directory structure:
```
LibriTTS_R/
├── BOOKS.txt
├── CHAPTERS.txt
├── LICENSE.txt
├── NOTE.txt
├── README_librispeech.txt
├── README_libritts.txt
├── README_libritts_r.txt
├── SPEAKERS.txt
├── dev-clean
├── dev-other
├── reader_book.tsv
├── speakers.tsv
├── test-clean
├── test-other
├── train-clean-100
├── train-clean-360
└── train-other-500
```
## 1. MFA data preparation
### Setup for MFA
```
conda install -c conda-forge montreal-forced-aligner
```
```
mfa model download dictionary english_us_arpa
mfa model download acoustic english_us_arpa
```
### Usage
Please check `runall_mfa.sh` for the usage.
Note that running MFA for all the utterances in LibriTTS-R takes a long time (likely a few days).
### Directory structure
After all the data preparation steps, the following directories will be created:
- `libritts_r_per_spk_cleaned`
- `${spk}`
- `textgrid`: text grid files
- `wav24k`: 24kHz wav files
```
├── 100
│ ├── textgrid
│ └── wav24k
├── 1001
│ ├── textgrid
│ └── wav24k
├── 1006
│ ├── textgrid
│ └── wav24k
...
```
## 2. Style prompt data preparation
Code for estimating per-utterance style tags (e.g., low pitch, normal pitch and high pitch) from the data statistics.
### Usage
Please check `runall_style_prompt_tags.sh` for the usage.
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