Datasets:

realnetworks-kontxt
/

fleurs-hs-vits

	---
	license: cc-by-4.0
	task_categories:
	- audio-classification
	language:
	- de
	- en
	- es
	- fr
	- it
	- nl
	- pl
	- sv
	tags:
	- speech
	- speech-classifiation
	- text-to-speech
	- spoofing
	- multilingualism

	pretty_name: FLEURS-HS VITS
	size_categories:
	- 10K<n<100K
	---

	# FLEURS-HS VITS

	An extension of the [FLEURS](https://huggingface.co/datasets/google/fleurs) dataset for synthetic speech detection using text-to-speech, featured in the paper Synthetic speech detection with Wav2Vec 2.0 in various language settings.

	This dataset is 1 of 3 used in the paper, the others being:
	- [FLEURS-HS](https://huggingface.co/datasets/realnetworks-kontxt/fleurs-hs)
	- the default train, dev and test sets
	- separated due to different licensing
	- [ARCTIC-HS](https://huggingface.co/datasets/realnetworks-kontxt/arctic-hs)
	- extension of the [CMU_ARCTIC](http://festvox.org/cmu_arctic/) and [L2-ARCTIC](https://psi.engr.tamu.edu/l2-arctic-corpus/) sets in a similar manner

	## Dataset Details

	### Dataset Description

	The dataset features 8 languages originally seen in FLEURS:

	- German
	- English
	- Spanish
	- French
	- Italian
	- Dutch
	- Polish
	- Swedish

	The `synthetic` samples are generated using:

	- [Google Cloud Text-To-Speech](https://cloud.google.com/text-to-speech)
	- [Azure Text-To-Speech](https://azure.microsoft.com/en-us/products/ai-services/text-to-speech)
	- [Amazon Polly](https://aws.amazon.com/polly/)

	Only the test VITS samples are provided. For every VITS voice, which is in practice specific model weights, one sample per transcript is provided.


	- Curated by: [KONTXT by RealNetworks](https://realnetworks.com/kontxt)
	- Funded by: [RealNetworks](https://realnetworks.com/)
	- Language(s) (NLP): English, German, Spanish, French, Italian, Dutch, Polish, Swedish
	- License: [Apache 2.0](https://www.apache.org/licenses/LICENSE-2.0) for the code, [CC BY 4.0](https://creativecommons.org/licenses/by/4.0/) for the dataset (but various licenses depending on the source for VITS samples)

	### Dataset Sources

	The original FLEURS dataset was downloaded from [HuggingFace](https://huggingface.co/datasets/google/fleurs).

	- FLEURS Repository: [HuggingFace](https://huggingface.co/datasets/google/fleurs)
	- FLEURS Paper: [arXiv](https://arxiv.org/abs/2205.12446)

	- Paper: Synthetic speech detection with Wav2Vec 2.0 in various language settings

	## Uses

	This dataset is best used as a difficult test set. Each sample contains an `Audio` feature, and a label, which is always `synthetic`; this dataset does not include any human samples.

	### Direct Use

	The following snippet of code demonstrates loading the training split for English:

	```python
	from datasets import load_dataset

	fleurs_hs = load_dataset(
	"realnetworks-kontxt/fleurs-hs-vits",
	"en_us",
	split="test",
	trust_remote_code=True,
	)
	```

	To load a different language, change `en_us` into one of the following:
	- `de_de` for German
	- `es_419` for Spanish
	- `fr_fr` for French
	- `it_it` for Italian
	- `nl_nl` for Dutch
	- `pl_pl` for Polish
	- `sv_se` for Swedish

	This dataset only has a `test` split.

	The `trust_remote_code=True` parameter is necessary because this dataset uses a custom loader. To check out which code is being ran, check out the [loading script](./fleurs-hs-vits.py).

	## Dataset Structure

	The dataset data is contained in the [data directory](https://huggingface.co/datasets/realnetworks-kontxt/fleurs-hs-vits/tree/main/data).

	There exists 1 directory per language.

	Within that directory, there is a directory named `splits`; it contains 1 file per split:
	- `test.tar.gz`

	That `.tar.gz` file contains 1 or more directories, named after the VITS model being used: ex. `thorsten-vits`

	Each of these directories contain `.wav` files. Each `.wav` file is named after the ID of its transcript. Keep in mind that these directories can't be merged as they share their file names. An identical file name implies a speaker-voice pair, ex. `human/123.wav` and `thorsten-vits/123.wav`.

	Finally, back to the language directory, it contains 3 metadata files, which are not used in the loaded dataset, but might be useful to researchers:
	- `recording-metadata.csv`
	- contains the transcript ID, file name, split and gender of the original FLEURS samples
	- `recording-transcripts.csv`
	- contains the transcrpits of the original FLEURS samples
	- `voice-metadata.csv`
	- contains the groupation of TTS' used alongside the splits they were used for

	### Sample

	A sample contains contains an Audio feature `audio`, and a string `label`.

	```
	{
	'audio': {
	'path': 'ljspeech-vits/1660.wav',
	'array': array([0.00119019, 0.00109863, 0.00106812, ..., 0., 0., 0.]),
	'sampling_rate': 16000
	},
	'label': 'synthetic'
	}
	```

	## Citation

	The dataset is featured alongside our paper, Synthetic speech detection with Wav2Vec 2.0 in various language settings, which will be published on IEEE International Conference on Acoustics, Speech, and Signal Processing Workshops (ICASSPW). We'll provide links once it's available online.

	BibTeX:

	Note, the following BibTeX is incomplete - we'll update it once the actual one is known.

	```
	@inproceedings{dropuljic-ssdww2v2ivls
	author={Dropuljić, Branimir and Šuflaj, Miljenko and Jertec, Andrej and Obadić, Leo}
	booktitle={2024 IEEE International Conference on Acoustics, Speech, and Signal Processing Workshops (ICASSPW)}
	title={Synthetic speech detection with Wav2Vec 2.0 in various language settings}
	year={2024}
	volume={}
	number={}
	pages={1-5}
	keywords={Synthetic speech detection;text-to-speech;wav2vec 2.0;spoofing attack;multilingualism}
	doi={}
	}
	```

	## Dataset Card Authors

	- [Miljenko Šuflaj](https://huggingface.co/suflaj)

	## Dataset Card Contact

	- [Miljenko Šuflaj](mailto:msuflaj@realnetworks.com)