ayousanz/css10-ljspeech-multilingual
CSS10 + LJSpeech Multilingual Dataset A unified multilingual speech dataset combining CSS10 (10 languages) and LJSpeech (English) in a consistent LJSpeech format. Dataset Description This dataset merges: CSS10: A collection of single-speaker speech datasets for 10 languages LJSpeech: High-quality English speech dataset (Linda Johnson) All audio files are provided in a consistent format suitable for TTS training. Languages and Statistics… See the full description on the dataset page: https://huggingface.co/datasets/ayousanz/css10-ljspeech-multilingual.
CSS10 + LJSpeech Multilingual Dataset
A unified multilingual speech dataset combining CSS10 (10 languages) and LJSpeech (English) in a consistent LJSpeech format.
Dataset Description
This dataset merges:
- CSS10: A collection of single-speaker speech datasets for 10 languages
- LJSpeech: High-quality English speech dataset (Linda Johnson)
All audio files are provided in a consistent format suitable for TTS training.
Languages and Statistics
Total: 76,859 utterances, ~140 hours, 11 speakers
File Structure
├── README.md # This file
├── metadata.csv # Standard LJSpeech format (id|text)
├── metadata_multispeaker.csv # With speaker info (speaker|id|text)
├── dataset_stats.json # Dataset statistics
├── speaker_info.json # Speaker mapping and descriptions
├── audio_durations.csv # Audio duration information
└── wavs.zip # All audio files (77,296 files)Metadata Formats
1. Standard LJSpeech Format (metadata.csv)
id|text
de|Hanake hatte allen Körperschmuck...
en_LJ001-0001|Printing, in the only sense...2. Multi-speaker Format (metadata_multispeaker.csv)
speaker|id|text
CSS10_de|de|Hanake hatte allen Körperschmuck...
LJSpeech|en_LJ001-0001|Printing, in the only sense...Usage
Loading the Dataset
import pandas as pd
import zipfile
from pathlib import Path
# Extract audio files
with zipfile.ZipFile("wavs.zip", "r") as zip_ref:
zip_ref.extractall(".")
# Load metadata
metadata = pd.read_csv("metadata.csv", sep="|", names=["id", "text"])
# Load multi-speaker metadata
metadata_ms = pd.read_csv("metadata_multispeaker.csv",
sep="|", names=["speaker", "id", "text"])For TTS Training (Piper)
# Single speaker training (filter by language)
python -m piper_train.preprocess \
--input-dir . \
--output-dir output \
--dataset-format ljspeech \
--sample-rate 22050
# Multi-speaker training
python -m piper_train.preprocess \
--input-dir . \
--output-dir output \
--dataset-format multispeaker \
--metadata-file metadata_multispeaker.csv \
--sample-rate 22050File Naming Convention
- CSS10 files:
{language_code}_{original_id}.wav(e.g.,ja_BASIC5000_0001.wav) - LJSpeech files:
en_{original_id}.wav(e.g.,en_LJ001-0001.wav)
License
This dataset combines:
- CSS10: CC BY-SA 4.0
- LJSpeech: Public Domain
Please refer to the original datasets for detailed license information.
Citation
If you use this dataset, please cite both original sources:
@misc{css10,
author = {Kyubyong Park and Thomas Mulc},
title = {CSS10: A Collection of Single Speaker Speech Datasets for 10 Languages},
year = {2019},
publisher = {Interspeech},
}
@misc{ljspeech17,
author = {Keith Ito and Linda Johnson},
title = {The LJ Speech Dataset},
howpublished = {\url{https://keithito.com/LJ-Speech-Dataset/}},
year = {2017}
}Acknowledgments
- CSS10 dataset creators and contributors
- Keith Ito for the LJSpeech dataset
- The css10-ljspeech dataset for providing CSS10 in LJSpeech format
