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  1. README.md +175 -0
  2. data/de_de/LICENSE_css10-vits-neon +26 -0
  3. data/de_de/LICENSE_thorsten-vits +201 -0
  4. data/de_de/recording-metadata.csv +0 -0
  5. data/de_de/recording-transcripts.csv +0 -0
  6. data/de_de/splits/test.tar.gz +3 -0
  7. data/de_de/voice-metadata.csv +3 -0
  8. data/en_us/LICENSE_ljspeech-vits +201 -0
  9. data/en_us/LICENSE_ljspeech-vits-neon +26 -0
  10. data/en_us/recording-metadata.csv +0 -0
  11. data/en_us/recording-transcripts.csv +0 -0
  12. data/en_us/splits/test.tar.gz +3 -0
  13. data/en_us/voice-metadata.csv +3 -0
  14. data/es_419/LICENSE_css10-vits +26 -0
  15. data/es_419/recording-metadata.csv +0 -0
  16. data/es_419/recording-transcripts.csv +0 -0
  17. data/es_419/splits/test.tar.gz +3 -0
  18. data/es_419/voice-metadata.csv +2 -0
  19. data/fr_fr/LICENSE_css10-vits +26 -0
  20. data/fr_fr/recording-metadata.csv +0 -0
  21. data/fr_fr/recording-transcripts.csv +0 -0
  22. data/fr_fr/splits/test.tar.gz +3 -0
  23. data/fr_fr/voice-metadata.csv +2 -0
  24. data/it_it/LICENSE_mai_female-vits +202 -0
  25. data/it_it/LICENSE_mai_male-vits +202 -0
  26. data/it_it/recording-metadata.csv +0 -0
  27. data/it_it/recording-transcripts.csv +0 -0
  28. data/it_it/splits/test.tar.gz +3 -0
  29. data/it_it/voice-metadata.csv +3 -0
  30. data/nl_nl/LICENSE_css10-vits +26 -0
  31. data/nl_nl/recording-metadata.csv +0 -0
  32. data/nl_nl/recording-transcripts.csv +0 -0
  33. data/nl_nl/splits/test.tar.gz +3 -0
  34. data/nl_nl/voice-metadata.csv +2 -0
  35. data/pl_pl/LICENSE_mai_female-vits +26 -0
  36. data/pl_pl/recording-metadata.csv +0 -0
  37. data/pl_pl/recording-transcripts.csv +0 -0
  38. data/pl_pl/splits/test.tar.gz +3 -0
  39. data/pl_pl/voice-metadata.csv +2 -0
  40. data/sv_se/LICENSE_cv-vits +26 -0
  41. data/sv_se/recording-metadata.csv +0 -0
  42. data/sv_se/recording-transcripts.csv +0 -0
  43. data/sv_se/splits/test.tar.gz +3 -0
  44. data/sv_se/voice-metadata.csv +2 -0
  45. fleurs-hs-vits.py +158 -0
README.md ADDED
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+ ---
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+ license: cc-by-4.0
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+ task_categories:
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+ - audio-classification
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+ language:
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+ - de
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+ - en
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+ - es
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+ - fr
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+ - it
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+ - nl
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+ - pl
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+ - sv
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+ tags:
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+ - speech
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+ - speech-classifiation
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+ - text-to-speech
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+ - spoofing
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+ - multilingualism
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+
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+ pretty_name: FLEURS-HS VITS
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+ size_categories:
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+ - 10K<n<100K
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+ ---
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+
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+ # FLEURS-HS VITS
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+
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+ 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**.
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+
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+ This dataset is 1 of 3 used in the paper, the others being:
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+ - [FLEURS-HS](https://huggingface.co/datasets/realnetworks-kontxt/fleurs-hs)
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+ - the default train, dev and test sets
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+ - separated due to different licensing
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+ - [ARCTIC-HS](https://huggingface.co/datasets/realnetworks-kontxt/arctic-hs)
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+ - 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
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+
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+ ## Dataset Details
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+
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+ ### Dataset Description
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+
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+ The dataset features 8 languages originally seen in FLEURS:
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+
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+ - German
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+ - English
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+ - Spanish
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+ - French
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+ - Italian
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+ - Dutch
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+ - Polish
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+ - Swedish
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+
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+ The original FLEURS samples are used as `human` samples, while `synthetic` samples are generated using:
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+
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+ - [Google Cloud Text-To-Speech](https://cloud.google.com/text-to-speech)
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+ - [Azure Text-To-Speech](https://azure.microsoft.com/en-us/products/ai-services/text-to-speech)
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+ - [Amazon Polly](https://aws.amazon.com/polly/)
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+
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+ The resulting dataset features roughly twice the samples per language (every `human` sample usually has its `synthetic` counterpart).
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+
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+
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+ - **Curated by:** [KONTXT by RealNetworks](https://realnetworks.com/kontxt)
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+ - **Funded by:** [RealNetworks](https://realnetworks.com/)
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+ - **Language(s) (NLP):** English, German, Spanish, French, Italian, Dutch, Polish, Swedish
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+ - **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)
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+
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+ ### Dataset Sources
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+
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+ The original FLEURS dataset was downloaded from [HuggingFace](https://huggingface.co/datasets/google/fleurs).
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+
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+ - **FLEURS Repository:** [HuggingFace](https://huggingface.co/datasets/google/fleurs)
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+ - **FLEURS Paper:** [arXiv](https://arxiv.org/abs/2205.12446)
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+
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+ - **Paper:** Synthetic speech detection with Wav2Vec 2.0 in various language settings
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+
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+ ## Uses
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+
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+ This dataset is best used as a difficult test set. Each sample contains an `Audio` feature, and a label: `human` or `synthetic`.
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+
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+ ### Direct Use
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+
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+ The following snippet of code demonstrates loading the training split for English:
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+
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+ ```python
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+ from datasets import load_dataset
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+
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+ fleurs_hs = load_dataset(
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+ "realnetworks-kontxt/fleurs-hs-vits",
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+ "en_us",
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+ split="test",
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+ trust_remote_code=True,
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+ )
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+ ```
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+
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+ To load a different language, change `en_us` into one of the following:
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+ - `de_de` for German
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+ - `es_419` for Spanish
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+ - `fr_fr` for French
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+ - `it_it` for Italian
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+ - `nl_nl` for Dutch
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+ - `pl_pl` for Polish
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+ - `sv_se` for Swedish
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+
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+ This dataset only has a `test` split.
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+
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+ To load only the synthetic samples, append `_without-human` to the name. For example, `en_us` will load the test set also containing the original English FLEURS samples, while `en_us_without-human` will only load the synthetic VITS samples. This is useful if you simply want to include the VITS samples into the original FLEURS-HS test set without duplicating human samples.
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+
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+ 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).
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+
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+ ## Dataset Structure
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+
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+ The dataset data is contained in the [data directory](https://huggingface.co/datasets/realnetworks-kontxt/fleurs-hs-vits/tree/main/data).
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+
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+ There exists 1 directory per language.
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+
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+ Within those directories, there is a directory named `splits`; it contains 1 file per split:
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+ - `test.tar.gz`
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+
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+ Those `.tar.gz` files contain 2 or more directories:
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+ - `human`
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+ - 1 or more directories named after the VITS model being used, ex. `thorsten-vits`
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+
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+ Each of these directories contain `.wav` files. Keep in mind that these directories can't be merged as they share most of their file names. An identical file name implies a speaker-voice pair, ex. `human/123.wav` and `thorsten-vits/123.wav`.
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+
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+ 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:
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+ - `recording-metadata.csv`
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+ - contains the transcript ID, file name, split and gender of the original FLEURS samples
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+ - `recording-transcripts.csv`
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+ - contains the transcrpits of the original FLEURS samples
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+ - `voice-metadata.csv`
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+ - contains the groupation of TTS' used alongside the splits they were used for
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+
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+ ### Sample
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+
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+ A sample contains contains an Audio feature `audio`, and a string `label`.
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+
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+ ```
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+ {
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+ 'audio': {
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+ 'path': 'ljspeech-vits/1003119935936341070.wav',
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+ 'array': array([-0.00048828, -0.00106812, -0.00164795, ..., 0., 0., 0.]),
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+ 'sampling_rate': 16000
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+ },
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+ 'label': 'synthetic'
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+ }
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+ ```
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+
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+ ## Citation
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+
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+ 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.
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+
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+ **BibTeX:**
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+
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+ Note, the following BibTeX is incomplete - we'll update it once the actual one is known.
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+
155
+ ```
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+ @inproceedings{dropuljic-ssdww2v2ivls
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+ author={Dropuljić, Branimir and Šuflaj, Miljenko and Jertec, Andrej and Obadić, Leo}
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+ booktitle={2024 IEEE International Conference on Acoustics, Speech, and Signal Processing Workshops (ICASSPW)}
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+ title={Synthetic speech detection with Wav2Vec 2.0 in various language settings}
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+ year={2024}
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+ volume={}
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+ number={}
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+ pages={1-5}
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+ keywords={Synthetic speech detection;text-to-speech;wav2vec 2.0;spoofing attack;multilingualism}
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+ doi={}
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+ }
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+ ```
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+
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+ ## Dataset Card Authors
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+
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+ - [Miljenko Šuflaj](https://huggingface.co/suflaj)
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+
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+ ## Dataset Card Contact
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+
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+ - [Miljenko Šuflaj](mailto:[email protected])
data/de_de/LICENSE_css10-vits-neon ADDED
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+ * Redistributions of source code must retain the above copyright notice,
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data/de_de/LICENSE_thorsten-vits ADDED
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data/de_de/recording-metadata.csv ADDED
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+ version https://git-lfs.github.com/spec/v1
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+ All rights reserved.
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+
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+ Redistribution and use in source and binary forms, with or without
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+ modification, are permitted provided that the following conditions are met:
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+ * Redistributions of source code must retain the above copyright notice,
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+ * Redistributions in binary form must reproduce the above copyright
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11
+ documentation and/or other materials provided with the distribution.
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+ * Neither the name of Neon AI nor the names of its contributors may be
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+ used to endorse or promote products derived from this software without
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+ specific prior written permission.
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+
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+ THIS SOFTWARE IS PROVIDED BY THE COPYRIGHT HOLDERS AND CONTRIBUTORS "AS IS"
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+ AND ANY EXPRESS OR IMPLIED WARRANTIES, INCLUDING, BUT NOT LIMITED TO, THE
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+ IMPLIED WARRANTIES OF MERCHANTABILITY AND FITNESS FOR A PARTICULAR PURPOSE
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+ ARE DISCLAIMED. IN NO EVENT SHALL THE COPYRIGHT OWNER OR CONTRIBUTORS BE
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+ LIABLE FOR ANY DIRECT, INDIRECT, INCIDENTAL, SPECIAL, EXEMPLARY, OR
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+ CONSEQUENTIAL DAMAGES (INCLUDING, BUT NOT LIMITED TO, PROCUREMENT OF
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+ SUBSTITUTE GOODS OR SERVICES; LOSS OF USE, DATA, OR PROFITS; OR BUSINESS
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+ INTERRUPTION) HOWEVER CAUSED AND ON ANY THEORY OF LIABILITY, WHETHER IN
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+ ARISING IN ANY WAY OUT OF THE USE OF THIS SOFTWARE, EVEN IF ADVISED OF THE
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+ Redistribution and use in source and binary forms, with or without
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+ * Neither the name of Neon AI nor the names of its contributors may be
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+ All rights reserved.
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+ Redistribution and use in source and binary forms, with or without
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+ modification, are permitted provided that the following conditions are met:
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+ * Redistributions of source code must retain the above copyright notice,
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+ this list of conditions and the following disclaimer.
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+ * Redistributions in binary form must reproduce the above copyright
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+ documentation and/or other materials provided with the distribution.
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+ * Neither the name of Neon AI nor the names of its contributors may be
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+ THIS SOFTWARE IS PROVIDED BY THE COPYRIGHT HOLDERS AND CONTRIBUTORS "AS IS"
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+ SUBSTITUTE GOODS OR SERVICES; LOSS OF USE, DATA, OR PROFITS; OR BUSINESS
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+ Apache License
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data/it_it/LICENSE_mai_male-vits ADDED
@@ -0,0 +1,202 @@
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
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data/nl_nl/LICENSE_css10-vits ADDED
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1
+ Copyright (c) 2023, https://github.com/NeonGeckoCom
2
+ All rights reserved.
3
+
4
+ Redistribution and use in source and binary forms, with or without
5
+ modification, are permitted provided that the following conditions are met:
6
+
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+ * Redistributions of source code must retain the above copyright notice,
8
+ this list of conditions and the following disclaimer.
9
+ * Redistributions in binary form must reproduce the above copyright
10
+ notice, this list of conditions and the following disclaimer in the
11
+ documentation and/or other materials provided with the distribution.
12
+ * Neither the name of Neon AI nor the names of its contributors may be
13
+ used to endorse or promote products derived from this software without
14
+ specific prior written permission.
15
+
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+ THIS SOFTWARE IS PROVIDED BY THE COPYRIGHT HOLDERS AND CONTRIBUTORS "AS IS"
17
+ AND ANY EXPRESS OR IMPLIED WARRANTIES, INCLUDING, BUT NOT LIMITED TO, THE
18
+ IMPLIED WARRANTIES OF MERCHANTABILITY AND FITNESS FOR A PARTICULAR PURPOSE
19
+ ARE DISCLAIMED. IN NO EVENT SHALL THE COPYRIGHT OWNER OR CONTRIBUTORS BE
20
+ LIABLE FOR ANY DIRECT, INDIRECT, INCIDENTAL, SPECIAL, EXEMPLARY, OR
21
+ CONSEQUENTIAL DAMAGES (INCLUDING, BUT NOT LIMITED TO, PROCUREMENT OF
22
+ SUBSTITUTE GOODS OR SERVICES; LOSS OF USE, DATA, OR PROFITS; OR BUSINESS
23
+ INTERRUPTION) HOWEVER CAUSED AND ON ANY THEORY OF LIABILITY, WHETHER IN
24
+ CONTRACT, STRICT LIABILITY, OR TORT (INCLUDING NEGLIGENCE OR OTHERWISE)
25
+ ARISING IN ANY WAY OUT OF THE USE OF THIS SOFTWARE, EVEN IF ADVISED OF THE
26
+ POSSIBILITY OF SUCH DAMAGE.
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+ size 150617914
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+ tts_vendor,tts_name,tts_engine,tts_split,tts_gender,tts_group
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data/pl_pl/LICENSE_mai_female-vits ADDED
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1
+ Copyright (c) 2023, https://github.com/NeonGeckoCom
2
+ All rights reserved.
3
+
4
+ Redistribution and use in source and binary forms, with or without
5
+ modification, are permitted provided that the following conditions are met:
6
+
7
+ * Redistributions of source code must retain the above copyright notice,
8
+ this list of conditions and the following disclaimer.
9
+ * Redistributions in binary form must reproduce the above copyright
10
+ notice, this list of conditions and the following disclaimer in the
11
+ documentation and/or other materials provided with the distribution.
12
+ * Neither the name of Neon AI nor the names of its contributors may be
13
+ used to endorse or promote products derived from this software without
14
+ specific prior written permission.
15
+
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+ THIS SOFTWARE IS PROVIDED BY THE COPYRIGHT HOLDERS AND CONTRIBUTORS "AS IS"
17
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20
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21
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22
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23
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24
+ CONTRACT, STRICT LIABILITY, OR TORT (INCLUDING NEGLIGENCE OR OTHERWISE)
25
+ ARISING IN ANY WAY OUT OF THE USE OF THIS SOFTWARE, EVEN IF ADVISED OF THE
26
+ POSSIBILITY OF SUCH DAMAGE.
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data/pl_pl/splits/test.tar.gz ADDED
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+ size 306485532
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1
+ Copyright (c) 2023, https://github.com/NeonGeckoCom
2
+ All rights reserved.
3
+
4
+ Redistribution and use in source and binary forms, with or without
5
+ modification, are permitted provided that the following conditions are met:
6
+
7
+ * Redistributions of source code must retain the above copyright notice,
8
+ this list of conditions and the following disclaimer.
9
+ * Redistributions in binary form must reproduce the above copyright
10
+ notice, this list of conditions and the following disclaimer in the
11
+ documentation and/or other materials provided with the distribution.
12
+ * Neither the name of Neon AI nor the names of its contributors may be
13
+ used to endorse or promote products derived from this software without
14
+ specific prior written permission.
15
+
16
+ THIS SOFTWARE IS PROVIDED BY THE COPYRIGHT HOLDERS AND CONTRIBUTORS "AS IS"
17
+ AND ANY EXPRESS OR IMPLIED WARRANTIES, INCLUDING, BUT NOT LIMITED TO, THE
18
+ IMPLIED WARRANTIES OF MERCHANTABILITY AND FITNESS FOR A PARTICULAR PURPOSE
19
+ ARE DISCLAIMED. IN NO EVENT SHALL THE COPYRIGHT OWNER OR CONTRIBUTORS BE
20
+ LIABLE FOR ANY DIRECT, INDIRECT, INCIDENTAL, SPECIAL, EXEMPLARY, OR
21
+ CONSEQUENTIAL DAMAGES (INCLUDING, BUT NOT LIMITED TO, PROCUREMENT OF
22
+ SUBSTITUTE GOODS OR SERVICES; LOSS OF USE, DATA, OR PROFITS; OR BUSINESS
23
+ INTERRUPTION) HOWEVER CAUSED AND ON ANY THEORY OF LIABILITY, WHETHER IN
24
+ CONTRACT, STRICT LIABILITY, OR TORT (INCLUDING NEGLIGENCE OR OTHERWISE)
25
+ ARISING IN ANY WAY OUT OF THE USE OF THIS SOFTWARE, EVEN IF ADVISED OF THE
26
+ POSSIBILITY OF SUCH DAMAGE.
data/sv_se/recording-metadata.csv ADDED
The diff for this file is too large to render. See raw diff
 
data/sv_se/recording-transcripts.csv ADDED
The diff for this file is too large to render. See raw diff
 
data/sv_se/splits/test.tar.gz ADDED
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+ version https://git-lfs.github.com/spec/v1
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+ oid sha256:1049da055daec26339f1aaafea84108b15eb683129d201e79332a4e27800ed3c
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+ size 354153656
data/sv_se/voice-metadata.csv ADDED
@@ -0,0 +1,2 @@
 
 
 
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+ tts_vendor,tts_name,tts_engine,tts_split,tts_gender,tts_group
2
+ coqui,,tts_models/sv/cv/vits,test,female,0
fleurs-hs-vits.py ADDED
@@ -0,0 +1,158 @@
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
1
+ # Copyright 2024 RealNetworks
2
+
3
+ # Licensed under the Apache License, Version 2.0 (the "License");
4
+ # you may not use this file except in compliance with the License.
5
+ # You may obtain a copy of the License at
6
+
7
+ # http://www.apache.org/licenses/LICENSE-2.0
8
+
9
+ # Unless required by applicable law or agreed to in writing, software
10
+ # distributed under the License is distributed on an "AS IS" BASIS,
11
+ # WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
12
+ # See the License for the specific language governing permissions and
13
+ # limitations under the License.
14
+
15
+
16
+ from pathlib import Path
17
+ from typing import (
18
+ Any,
19
+ Dict,
20
+ Iterable,
21
+ List,
22
+ Tuple,
23
+ )
24
+
25
+ from datasets import (
26
+ Audio,
27
+ BuilderConfig,
28
+ DatasetInfo,
29
+ Features,
30
+ GeneratorBasedBuilder,
31
+ Split,
32
+ SplitGenerator,
33
+ Value,
34
+ )
35
+ from datasets.download.download_manager import (
36
+ ArchiveIterable,
37
+ DownloadManager,
38
+ )
39
+
40
+
41
+ class FLEURSHSVITSConfig(BuilderConfig):
42
+ def __init__(
43
+ self,
44
+ name,
45
+ **kwargs,
46
+ ):
47
+ super(
48
+ FLEURSHSVITSConfig,
49
+ self,
50
+ ).__init__(
51
+ name=name,
52
+ **kwargs,
53
+ )
54
+
55
+ if self.name.endswith("_without-human"):
56
+ self.without_human = True
57
+ self.language = "_".join(self.name.split("_")[:-1])
58
+ else:
59
+ self.without_human = False
60
+ self.language = self.name
61
+
62
+
63
+ class FLEURSHSVITSDataset(GeneratorBasedBuilder):
64
+ DEFAULT_CONFIG_NAME = "en_us_without-human"
65
+
66
+ BUILDER_CONFIGS = [
67
+ FLEURSHSVITSConfig(name=name)
68
+ for name in (
69
+ "de_de",
70
+ "en_us",
71
+ "es_419",
72
+ "fr_fr",
73
+ "it_it",
74
+ "nl_nl",
75
+ "pl_pl",
76
+ "sv_se",
77
+ "de_de_without-human",
78
+ "en_us_without-human",
79
+ "es_419_without-human",
80
+ "fr_fr_without-human",
81
+ "it_it_without-human",
82
+ "nl_nl_without-human",
83
+ "pl_pl_without-human",
84
+ "sv_se_without-human",
85
+ )
86
+ ]
87
+
88
+ def get_audio_archive_path(
89
+ self,
90
+ ) -> Path:
91
+ return Path("data") / self.config.language / "splits" / "test.tar.gz"
92
+
93
+ def _info(self) -> DatasetInfo:
94
+ return DatasetInfo(
95
+ description="FLEURS Human-Synthetic VITS test dataset",
96
+ features=Features(
97
+ {
98
+ "audio": Audio(sampling_rate=16000),
99
+ "label": Value("string"),
100
+ }
101
+ ),
102
+ supervised_keys=None,
103
+ homepage="https://huggingface.co/datasets/realnetworks-kontxt/fleurs-hs-vits",
104
+ license="CC BY 4.0",
105
+ citation="\n".join(
106
+ (
107
+ "@inproceedings{dropuljic-ssdww2v2ivls",
108
+ "author={Dropuljić, Branimir and Šuflaj, Miljenko and Jertec, Andrej and Obadić, Leo}",
109
+ "booktitle={2024 IEEE International Conference on Acoustics, Speech, and Signal Processing Workshops (ICASSPW)}",
110
+ "title={Synthetic speech detection with Wav2Vec 2.0 in various language settings}",
111
+ "year={2024}",
112
+ "volume={}",
113
+ "number={}",
114
+ "pages={1-5}",
115
+ "keywords={Synthetic speech detection;text-to-speech;wav2vec 2.0;spoofing attack;multilingualism}",
116
+ "doi={}", # TODO: Add DOI once known
117
+ "}",
118
+ )
119
+ ),
120
+ )
121
+
122
+ def _split_generators(
123
+ self,
124
+ download_manager: DownloadManager,
125
+ ) -> List[SplitGenerator]:
126
+ archive_iterable = self.get_audio_archive_path()
127
+ archive_iterable = download_manager.download(archive_iterable)
128
+ archive_iterable = download_manager.iter_archive(archive_iterable)
129
+
130
+ return [
131
+ SplitGenerator(
132
+ name=Split.TEST,
133
+ gen_kwargs={
134
+ "archive_iterable": archive_iterable,
135
+ },
136
+ ),
137
+ ]
138
+
139
+ def _generate_examples(
140
+ self,
141
+ archive_iterable: ArchiveIterable,
142
+ ) -> Iterable[Tuple[int, Dict[str, Any]]]:
143
+ current_index = 0
144
+ for audio_path, audio_file in archive_iterable:
145
+ label = "human" if Path(audio_path).parent.name == "human" else "synthetic"
146
+
147
+ if not self.config.without_human or label == "human":
148
+ audio = {
149
+ "path": audio_path,
150
+ "bytes": audio_file.read(),
151
+ }
152
+
153
+ yield current_index, {
154
+ "audio": audio,
155
+ "label": label,
156
+ }
157
+
158
+ current_index += 1