Datasets:
The dataset viewer is not available for this subset.
Exception: SplitsNotFoundError
Message: The split names could not be parsed from the dataset config.
Traceback: Traceback (most recent call last):
File "/usr/local/lib/python3.12/site-packages/datasets/inspect.py", line 286, in get_dataset_config_info
for split_generator in builder._split_generators(
^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/usr/local/lib/python3.12/site-packages/datasets/packaged_modules/webdataset/webdataset.py", line 82, in _split_generators
raise ValueError(
ValueError: The TAR archives of the dataset should be in WebDataset format, but the files in the archive don't share the same prefix or the same types.
The above exception was the direct cause of the following exception:
Traceback (most recent call last):
File "/src/services/worker/src/worker/job_runners/config/split_names.py", line 65, in compute_split_names_from_streaming_response
for split in get_dataset_split_names(
^^^^^^^^^^^^^^^^^^^^^^^^
File "/usr/local/lib/python3.12/site-packages/datasets/inspect.py", line 340, in get_dataset_split_names
info = get_dataset_config_info(
^^^^^^^^^^^^^^^^^^^^^^^^
File "/usr/local/lib/python3.12/site-packages/datasets/inspect.py", line 291, in get_dataset_config_info
raise SplitsNotFoundError("The split names could not be parsed from the dataset config.") from err
datasets.inspect.SplitsNotFoundError: The split names could not be parsed from the dataset config.Need help to make the dataset viewer work? Make sure to review how to configure the dataset viewer, and open a discussion for direct support.
LRLspoof: Low-Resource Language Spoofing Dataset
A large-scale speech deepfake / anti-spoofing dataset for low-resource and multilingual languages. The dataset contains synthetic (TTS-generated) speech from multiple text-to-speech systems across many languages, intended for training and evaluating audio deepfake detection and anti-spoofing models.
Languages: abkhazian, armenian, assamese, australian, avar, azerbaijanian, bashkir, belarusian, bodo, brazilian, bulgarian, catalan, chechen, chuvash, crimean, croatian, czech, danish, dutch, english, erzya, farsi, finnish, french, georgian, gujarati, hindi, hungarian, icelandic, indonesian, italian, japan, kalmyk, karachai_balkar, kazakh, khakassky, korean, kyrgyz, latvian, lezgian, lithuanian, luxembourgish, malasian, malayalam, manipuri, mari, marathi, moksha, nepali, nogai, norwegian, odia, ossetian, polish, rajasthani, russian, slovenian, spanish, swahili, tatar, telugu, turkmen, tuvan, uzbek, welsh, yakut.
Models: aHoTTS, Chatterbox, Crimean Tatar (Qirimtatar) TTS, eSpeak NG, Fast Pitch, F5-TTS, FishAudio S1, Fun-CosyVoice 3.0, IMS-Toucan, Indic-TTS, Kokoro, Matcha-TTS, MeloTTS, MMS TTS, OuteTTS, Parler-TTS, Piper, RHVoice, Silero TTS, SpeechT5, TurkicTTS, XTTS-v2, Zonos.
Overview
- Purpose: Benchmark and develop anti-spoofing / deepfake detection systems for under-resourced and multilingual settings.
- Content: Synthetic speech utterances generated by various TTS models, with transcriptions.
- Structure: One directory per language, under it one directory per TTS model (or model part). Each model folder contains:
- Audio:
.wavfiles (e.g.1.wav,2.wav, …). - Transcriptions: a
.txtfile (one sentence per line, aligned with the audio indices where applicable).
- Audio:
Statistics
- Number of languages: 66
- Number of TTS systems: 23
- Total hours: 2732.17
Total audio duration (hours) by TTS model:
Total audio duration (hours) by language:
Table 5. Summary SRR (%) aggregated across languages. MSRR (All): mean SRR across all languages; PSRR (All): pooled SRR across all languages; MSRR (Low): mean SRR across low-resource languages; PSRR (Low): pooled SRR across low-resource languages. Higher is better for all metrics.
| Model | MSRR (All) | PSRR (All) | MSRR (Low) | PSRR (Low) |
|---|---|---|---|---|
| AASIST3 | 90.40 | 91.40 | 93.28 | 94.28 |
| DF Arena 1B | 71.07 | 70.53 | 73.62 | 74.89 |
| DF Arena 500M | 63.47 | 58.50 | 67.31 | 62.47 |
| Rest2TCNGuard | 33.07 | 35.37 | 37.38 | 42.94 |
| ResCapsGuard | 41.29 | 40.56 | 40.81 | 40.65 |
| XSLS | 36.04 | 34.85 | 39.66 | 39.97 |
| Wav2Vec+AASIST | 45.62 | 43.48 | 50.09 | 49.34 |
| TCM-ADD | 45.93 | 43.20 | 51.30 | 49.66 |
| Nes2Net | 34.23 | 30.85 | 38.34 | 35.61 |
| wav2vec2-xls-r-1b-DeepFake-AI4TRUST | 26.79 | 26.07 | 30.28 | 30.14 |
| wav2vec2-xls-r-300m-deepfake-V1 | 80.51 | 78.32 | 83.90 | 81.29 |
| Spectra-0 | 97.11 | 97.47 | 96.67 | 97.23 |
Dataset Structure
lrl_spoof/
├── <language_1>/ # e.g. english, polish, hindi
│ ├── <model_1>/ # e.g. pipertts, kokoro_part1
│ │ ├── 1.wav
│ │ ├── 2.wav
│ │ └── ...
│ ├── <model_1>.txt # transcriptions for model_1 (when present)
│ ├── <model_2>/
│ └── ...
├── <language_2>/
└── ...
- Path to a given subset:
lrl_spoof/<language>/<model>/(audio) andlrl_spoof/<language>/<model>.txt(transcriptions, when present).
Download, Combining Parts, and Unpacking
The dataset is distributed as a compressed archive split into 15 GB parts (e.g. lrl_spoof.tar.gz.part_aa, lrl_spoof.tar.gz.part_ab, …). Download all parts from the dataset page on Hugging Face or ModelScope.
Combining parts
[Add the exact filenames and commands you use. Example for Linux/macOS:]
# Example: if parts are named lrl_spoof.tar.gz.part_aa, .part_ab, ...
cat lrl_spoof.tar.gz.part_* > lrl_spoof.tar.gz
Unpacking
tar -xzf lrl_spoof.tar.gz
Contact
- Email: k.n.borodin@mtuci.ru
- Telegram channel: https://t.me/korallll_ai
Citation
If you use this dataset in your research, please cite the accompanying paper:
@misc{borodin2026spoofdetectorstravelevaluation,
title={When Spoof Detectors Travel: Evaluation Across 66 Languages in the Low-Resource Language Spoofing Corpus},
author={Kirill Borodin and Vasiliy Kudryavtsev and Maxim Maslov and Mikhail Gorodnichev and Grach Mkrtchian},
year={2026},
eprint={2603.02364},
archivePrefix={arXiv},
primaryClass={cs.SD},
url={https://arxiv.org/abs/2603.02364},
}
Checksums
To ensure that your download is correct and not corrupted, you can verify SHA256 checksums with the sha256sum tool (available on Linux and most Unix-like systems).
# Verify the combined archive
sha256sum lrl_spoof.tar.gz
# Verify all parts (run in the directory containing the parts)
sha256sum lrl_spoof.tar.gz.part_* > lrl_spoof_parts.sha256
cat lrl_spoof_parts.sha256
After combining parts, verify the full archive with the checksum below. You can also verify each part before combining.
Whole archive (after combining parts into lrl_spoof.tar.gz):
lrl_spoof.tar.gz 624cba39b9c60d35ec90c9ee4450385ad885ca31c093e9a6de592f5f524e203b
Per-part checksums (SHA256 of each part file):
| Part file | SHA256 |
|---|---|
lrl_spoof.tar.gz.part_aa |
ee37cb5a5de1dcc2226d2a1f7d1b986d81529fd0a6ceac354a13f184ec9a8df0 |
lrl_spoof.tar.gz.part_ab |
4704e5020710d4151fe986f510bec861d7ff5cc8e7ee2403c01dca7b0cf9ab74 |
lrl_spoof.tar.gz.part_ac |
f4973e4bad14f772e7510bc9f8422f86f4538af017f4fb2b83e62500a52a8054 |
lrl_spoof.tar.gz.part_ad |
18c09449888f20a25346a5362c77c6aece27ffab1d017789c08fa96d8a9e545f |
lrl_spoof.tar.gz.part_ae |
46ed67962bdf454ca506d324a171894b1ab95c48a70e580d112e7aa0a28207c0 |
lrl_spoof.tar.gz.part_af |
b0a46aa45c13c54b6f29af2e1482236b785beb9f394fe4c397dd44536890a1be |
lrl_spoof.tar.gz.part_ag |
ab26e02c455caa1966edde60057102847b2d4383b63f6c7fbbc2f2d64b262d1b |
lrl_spoof.tar.gz.part_ah |
bd92dfdcfae766e3c2a9a3db164a97c573bd72f8caab980861fe7c602d75d8e3 |
lrl_spoof.tar.gz.part_ai |
ea7da360febfd76fbd7c024e080576bec0c1a4e95b1a42f193317c9fdbb8f968 |
lrl_spoof.tar.gz.part_aj |
335504f44b2c9e0747621517c752b4329f2ec9e99afe85886fc88ab93b43a147 |
lrl_spoof.tar.gz.part_ak |
8317f9cc2cc7eee4903dcf2238f44a5b13b57ca4bb76a73f475741b195ca05c4 |
lrl_spoof.tar.gz.part_al |
830690aa2d432ee8fd0fd6d8cdf603fc2da4988fe646bc9f5584443b5a9b4c8a |
lrl_spoof.tar.gz.part_am |
578d6206f12e73df83cb0dfd825e6d7b1975f44119d79b00c0039fb419d70767 |
lrl_spoof.tar.gz.part_an |
4d8b8fac6dd72b595e1a8786eb90a15827a8cdab89f3bdb7055d38f9b3c2c9d6 |
lrl_spoof.tar.gz.part_ao |
562e5ff609a1043fa08ee842fc71ab5c73988826acc33e5345631bf208570ef9 |
lrl_spoof.tar.gz.part_ap |
d13604b3e9055037e46166e708c19d07d01c8f6392d148d18cc0da85a0e5daf1 |
lrl_spoof.tar.gz.part_aq |
d3e61174f56a8b12b9473c2fcc4a0b4e747efc26de685bc1ddcc907ca8632f77 |
lrl_spoof.tar.gz.part_ar |
9240f7715d60edbe369fc4db1ee41422a05163f7ea9c8d00c911aa26d34bf2d3 |
lrl_spoof.tar.gz.part_as |
c7e385fc0d8578143b7e15862a2c3fc35f5ab96bdd2b5462448cbf7014eb28de |
lrl_spoof.tar.gz.part_at |
e6e6b42db89e06d7e72d2aa8a4046c31019aa38179c56dda38faf911d541fe3e |
lrl_spoof.tar.gz.part_au |
d492ddd786d0cb24eabbd16af215e87be2d6480b0d5fabf9f42c59bd5232b1bf |
lrl_spoof.tar.gz.part_av |
a8cb2118b3c7b2ed29aef831bd117ae6342b21424a37fb73ad38bba4c246bb75 |
lrl_spoof.tar.gz.part_aw |
4b2f4a9d9ebdbd41be88a296297fd4442c968d717903e5c1b2d867309569b03a |
lrl_spoof.tar.gz.part_ax |
1fb78e4aa022f313b375ef7f6cd1111e0ccdcea303be7baa28230de95937f153 |
lrl_spoof.tar.gz.part_ay |
00fcb87e7ac8c6057409b438c150ec8c0e32ccd1f01ca8f9f8c3ca8620b67f02 |
lrl_spoof.tar.gz.part_az |
a93904cf3e9ec2e6e1a0714748286f3215e2d32396ab08831f64f0e04450eae7 |
lrl_spoof.tar.gz.part_ba |
5541d5dd7e2d97b45b25881ace22e6d91359e14a7e7aabdd40f4d8665d9d6dcb |
lrl_spoof.tar.gz.part_bb |
0e853d7dcccee31aa88e9e087bdf909b87afa4cd76fd561505376375cb7ae42e |
lrl_spoof.tar.gz.part_bc |
03ba430fc61596dc4dfe35ddee8dd02d8e9878fa19e34ea8eb99a3d128df8e92 |
lrl_spoof.tar.gz.part_bd |
ed72149dcd57d80337148e414a38f7b477314f53ceac31e1c3eaa4d2f4876f35 |
lrl_spoof.tar.gz.part_be |
f078fd3816cb3962285a98a2241d1480c9b22e2ff86e15f760cf594abf1d9d2a |
lrl_spoof.tar.gz.part_bf |
517a03f070dfecc2aec3d366c75624b9bc7602f35708e3394e4f65e0c770b0ea |
lrl_spoof.tar.gz.part_bg |
50c8c12fc62c1e702ee07ca01ca793fce604ab06d7ae8ab4f5affbea26d0c32b |
lrl_spoof.tar.gz.part_bh |
754250885d5e901c2898df2149608430d16559f7d02889f66cda514ee7fbe95c |
lrl_spoof.tar.gz.part_bi |
90cb8439c7a966f146f905a94f8969538cd12e95aa304b1d03d31d71a7c12f2a |
lrl_spoof.tar.gz.part_bj |
03a3e8ee7b4b4264ffcf6a28d62863f78b3b360ebf3e80eb20251608f5e10828 |
lrl_spoof.tar.gz.part_bk |
0043a4ec8d26032a9cfc0cdb90786518c4fc523d9d5320caba7ed8b739251219 |
lrl_spoof.tar.gz.part_bl |
ad036e4cff44aab51addd99b3f44bbcd3e1b3a43b47da2e78fb2bd7b567c1b85 |
lrl_spoof.tar.gz.part_bm |
6ab7e4e597603d3dda0192f20fead863c3f3461535d2003c4e2ccf5ada3f5690 |
lrl_spoof.tar.gz.part_bn |
f9f17e350d23eb74a5cad5d7f4f07e8117d4a09f9fd6a474c9b67f97433c7fd8 |
lrl_spoof.tar.gz.part_bo |
093e585745282be049a5848cf3e599de1f8a80d3ed7068500eb5f0ecf815a7c0 |
lrl_spoof.tar.gz.part_bp |
c56dda5dd6d5f250bca14542652c26b57d666fb90d7522f6a4e83d3d055780e4 |
lrl_spoof.tar.gz.part_bq |
13b67216fe92b3b7d1cc1525fde3881a0b1768a0ccacbedbd23aa31b57e0232a |
Languages and TTS Models
Each row is one (model, language) subset. Paths are relative to the dataset root. Each subset may have a different licence (see the Licence column); use and redistribution of a subset must comply with the licence of the corresponding source TTS model.
Licences that restrict distribution: The following licences limit commercial or unrestricted redistribution. Subsets under these licences may be used only in accordance with their terms (typically non‑commercial use only): CC BY-NC-4.0 (F5-TTS, MMS TTS), CC BY-NC-SA 4.0 (FishAudio S1, OuteTTS, Silero TTS, TurkicTTS), and coqui-public-model-license (XTTS-v2). Subsets under GPL-2.0 or GPL-3.0 (e.g. eSpeak NG, Piper, RHVoice) allow distribution under copyleft terms (derivative works must be GPL-licensed). All other listed licences (e.g. Apache-2.0, MIT, BSD-3-Clause) are permissive and do not restrict distribution for research or open use.
| Model | Language | Path in dataset | Link to model | Licence |
|---|---|---|---|---|
| aHoTTS | catalan | lrl_spoof/catalan/ahotts/ |
https://github.com/hitz-zentroa/aHoTTS | Apache-2.0 |
| Chatterbox | finnish | lrl_spoof/finnish/chatterbox/ |
https://github.com/resemble-ai/chatterbox | MIT |
| Chatterbox | malasian | lrl_spoof/malasian/chatterbox/ |
https://github.com/resemble-ai/chatterbox | MIT |
| Chatterbox | malayalam | lrl_spoof/malayalam/chatterbox/ |
https://github.com/resemble-ai/chatterbox | MIT |
| Chatterbox | norwegian | lrl_spoof/norwegian/chatterbox_part1/ |
https://github.com/resemble-ai/chatterbox | MIT |
| Chatterbox | norwegian | lrl_spoof/norwegian/chatterbox_part2/ |
https://github.com/resemble-ai/chatterbox | MIT |
| Chatterbox | polish | lrl_spoof/polish/chatterbox_part1/ |
https://github.com/resemble-ai/chatterbox | MIT |
| Chatterbox | polish | lrl_spoof/polish/chatterbox_part2/ |
https://github.com/resemble-ai/chatterbox | MIT |
| Chatterbox | swahili | lrl_spoof/swahili/chatterbox/ |
https://github.com/resemble-ai/chatterbox | MIT |
| Fun-CosyVoice 3.0 | japan | lrl_spoof/japan/cosyvoice3/ |
https://github.com/FunAudioLLM/CosyVoice | Apache-2.0 |
| Fun-CosyVoice 3.0 | korean | lrl_spoof/korean/cosyvoice3/ |
https://github.com/FunAudioLLM/CosyVoice | Apache-2.0 |
| eSpeak NG | armenian | lrl_spoof/armenian/espeak/ |
https://github.com/espeak-ng/espeak-ng | GPL-3.0 |
| eSpeak NG | azerbaijanian | lrl_spoof/azerbaijanian/espeak/ |
https://github.com/espeak-ng/espeak-ng | GPL-3.0 |
| eSpeak NG | bashkir | lrl_spoof/bashkir/espeak/ |
https://github.com/espeak-ng/espeak-ng | GPL-3.0 |
| eSpeak NG | bulgarian | lrl_spoof/bulgarian/espeak_part1/ |
https://github.com/espeak-ng/espeak-ng | GPL-3.0 |
| eSpeak NG | bulgarian | lrl_spoof/bulgarian/espeak_part2/ |
https://github.com/espeak-ng/espeak-ng | GPL-3.0 |
| eSpeak NG | chuvash | lrl_spoof/chuvash/espeak/ |
https://github.com/espeak-ng/espeak-ng | GPL-3.0 |
| eSpeak NG | georgian | lrl_spoof/georgian/espeak/ |
https://github.com/espeak-ng/espeak-ng | GPL-3.0 |
| eSpeak NG | kazakh | lrl_spoof/kazakh/espeak/ |
https://github.com/espeak-ng/espeak-ng | GPL-3.0 |
| eSpeak NG | kyrgyz | lrl_spoof/kyrgyz/espeak/ |
https://github.com/espeak-ng/espeak-ng | GPL-3.0 |
| eSpeak NG | turkmen | lrl_spoof/turkmen/espeak/ |
https://github.com/espeak-ng/espeak-ng | GPL-3.0 |
| IMS-Toucan | abkhazian | lrl_spoof/abkhazian/ims_toucan/ |
https://github.com/DigitalPhonetics/IMS-Toucan | Apache-2.0 |
| IMS-Toucan | armenian | lrl_spoof/armenian/ims_toucan/ |
https://github.com/DigitalPhonetics/IMS-Toucan | Apache-2.0 |
| IMS-Toucan | azerbaijanian | lrl_spoof/azerbaijanian/ims_toucan/ |
https://github.com/DigitalPhonetics/IMS-Toucan | Apache-2.0 |
| IMS-Toucan | bashkir | lrl_spoof/bashkir/ims_toucan/ |
https://github.com/DigitalPhonetics/IMS-Toucan | Apache-2.0 |
| IMS-Toucan | chuvash | lrl_spoof/chuvash/ims_toucan/ |
https://github.com/DigitalPhonetics/IMS-Toucan | Apache-2.0 |
| IMS-Toucan | czech | lrl_spoof/czech/ims_toucan/ |
https://github.com/DigitalPhonetics/IMS-Toucan | Apache-2.0 |
| IMS-Toucan | karachai_balkar | lrl_spoof/karachai_balkar/ims_toucan/ |
https://github.com/DigitalPhonetics/IMS-Toucan | Apache-2.0 |
| IMS-Toucan | lezgian | lrl_spoof/lezgian/ims_toucan/ |
https://github.com/DigitalPhonetics/IMS-Toucan | Apache-2.0 |
| IMS-Toucan | tuvan | lrl_spoof/tuvan/ims_toucan/ |
https://github.com/DigitalPhonetics/IMS-Toucan | Apache-2.0 |
| Indic-TTS | assamese | lrl_spoof/assamese/indictts/ |
https://github.com/AI4Bharat/Indic-TTS | MIT |
| Indic-TTS | bodo | lrl_spoof/bodo/indictts/ |
https://github.com/AI4Bharat/Indic-TTS | MIT |
| Indic-TTS | gujarati | lrl_spoof/gujarati/indictts/ |
https://github.com/AI4Bharat/Indic-TTS | MIT |
| Indic-TTS | hindi | lrl_spoof/hindi/indictts/ |
https://github.com/AI4Bharat/Indic-TTS | MIT |
| Indic-TTS | malayalam | lrl_spoof/malayalam/indictts/ |
https://github.com/AI4Bharat/Indic-TTS | MIT |
| Indic-TTS | manipuri | lrl_spoof/manipuri/indictts/ |
https://github.com/AI4Bharat/Indic-TTS | MIT |
| Indic-TTS | marathi | lrl_spoof/marathi/indictts_part1/ |
https://github.com/AI4Bharat/Indic-TTS | MIT |
| Indic-TTS | marathi | lrl_spoof/marathi/indictts_part2/ |
https://github.com/AI4Bharat/Indic-TTS | MIT |
| Indic-TTS | odia | lrl_spoof/odia/indictts/ |
https://github.com/AI4Bharat/Indic-TTS | MIT |
| Indic-TTS | rajasthani | lrl_spoof/rajasthani/indictts/ |
https://github.com/AI4Bharat/Indic-TTS | MIT |
| Indic-TTS | telugu | lrl_spoof/telugu/indictts/ |
https://github.com/AI4Bharat/Indic-TTS | MIT |
| Fast Pitch | english | lrl_spoof/english/fastpitch/ |
https://github.com/dan-wells/fastpitch | BSD-3-Clause |
| F5-TTS | chuvash | lrl_spoof/chuvash/f5/ |
https://huggingface.co/Misha24-10/F5-TTS_CHUVASH | CC BY-NC-4.0 |
| FishAudio S1 | polish | lrl_spoof/polish/fishspeech/ |
https://huggingface.co/fishaudio/s1-mini | CC BY-NC-SA-4.0 |
| Kokoro | brazilian | lrl_spoof/brazilian/kokoro/ |
https://github.com/hexgrad/kokoro | Apache-2.0 |
| Kokoro | english | lrl_spoof/english/kokoro_part1/ |
https://github.com/hexgrad/kokoro | Apache-2.0 |
| Kokoro | english | lrl_spoof/english/kokoro_part2/ |
https://github.com/hexgrad/kokoro | Apache-2.0 |
| Kokoro | french | lrl_spoof/french/kokoro_part1/ |
https://github.com/hexgrad/kokoro | Apache-2.0 |
| Kokoro | french | lrl_spoof/french/kokoro_part2/ |
https://github.com/hexgrad/kokoro | Apache-2.0 |
| Kokoro | french | lrl_spoof/french/kokoro_part3/ |
https://github.com/hexgrad/kokoro | Apache-2.0 |
| Kokoro | hindi | lrl_spoof/hindi/kokoro/ |
https://github.com/hexgrad/kokoro | Apache-2.0 |
| Kokoro | italian | lrl_spoof/italian/kokoro/ |
https://github.com/hexgrad/kokoro | Apache-2.0 |
| Kokoro | japan | lrl_spoof/japan/kokoro/ |
https://github.com/hexgrad/kokoro | Apache-2.0 |
| Matcha-TTS | kyrgyz | lrl_spoof/kyrgyz/matcha/ |
https://huggingface.co/kyrgyz-ai/akylai-tts-mini | MIT |
| MeloTTS | australian | lrl_spoof/australian/melotts/ |
https://github.com/myshell-ai/MeloTTS | MIT |
| MeloTTS | english | lrl_spoof/english/melotts/ |
https://github.com/myshell-ai/MeloTTS | MIT |
| MeloTTS | japan | lrl_spoof/japan/melotts/ |
https://github.com/myshell-ai/MeloTTS | MIT |
| MeloTTS | korean | lrl_spoof/korean/melotts/ |
https://github.com/myshell-ai/MeloTTS | MIT |
| MeloTTS | spanish | lrl_spoof/spanish/melotts/ |
https://github.com/myshell-ai/MeloTTS | MIT |
| MMS TTS | armenian | lrl_spoof/armenian/mms_tts/ |
https://huggingface.co/facebook/mms-tts-hyw | CC BY-NC-4.0 |
| MMS TTS | azerbaijanian | lrl_spoof/azerbaijanian/mms_tts/ |
https://huggingface.co/facebook/mms-tts-azb | CC BY-NC-4.0 |
| MMS TTS | bashkir | lrl_spoof/bashkir/mms_tts/ |
https://huggingface.co/facebook/mms-tts-bak | CC BY-NC-4.0 |
| MMS TTS | chuvash | lrl_spoof/chuvash/mms_tts/ |
https://huggingface.co/facebook/mms-tts-chv | CC BY-NC-4.0 |
| MMS TTS | dutch | lrl_spoof/dutch/mms_tts/ |
https://huggingface.co/facebook/mms-tts-nld | CC BY-NC-4.0 |
| MMS TTS | latvian | lrl_spoof/latvian/mms_tts/ |
https://huggingface.co/facebook/mms-tts-lav | CC BY-NC-4.0 |
| MMS TTS | yakut | lrl_spoof/yakut/mms_tts/ |
https://huggingface.co/facebook/mms-tts-sah | CC BY-NC-4.0 |
| OuteTTS | belarusian | lrl_spoof/belarusian/outetts/ |
https://huggingface.co/unsloth/Llama-OuteTTS-1.0-1B | CC BY-NC-SA-4.0 |
| OuteTTS | georgian | lrl_spoof/georgian/outetts/ |
https://huggingface.co/unsloth/Llama-OuteTTS-1.0-1B | CC BY-NC-SA-4.0 |
| OuteTTS | hungarian | lrl_spoof/hungarian/outetts/ |
https://huggingface.co/unsloth/Llama-OuteTTS-1.0-1B | CC BY-NC-SA-4.0 |
| OuteTTS | lithuanian | lrl_spoof/lithuanian/outetts/ |
https://huggingface.co/unsloth/Llama-OuteTTS-1.0-1B | CC BY-NC-SA-4.0 |
| OuteTTS | polish | lrl_spoof/polish/outetts/ |
https://huggingface.co/unsloth/Llama-OuteTTS-1.0-1B | CC BY-NC-SA-4.0 |
| OuteTTS | russian | lrl_spoof/russian/outetts/ |
https://huggingface.co/unsloth/Llama-OuteTTS-1.0-1B | CC BY-NC-SA-4.0 |
| Parler-TTS | english | lrl_spoof/english/parlertts_part1/ |
https://huggingface.co/parler-tts/parler-tts-mini-multilingual-v1.1 | Apache-2.0 |
| Parler-TTS | english | lrl_spoof/english/parlertts_part2/ |
https://huggingface.co/parler-tts/parler-tts-mini-multilingual-v1.1 | Apache-2.0 |
| Parler-TTS | english | lrl_spoof/english/parlertts_part3/ |
https://huggingface.co/parler-tts/parler-tts-mini-multilingual-v1.1 | Apache-2.0 |
| Parler-TTS | french | lrl_spoof/french/parlertts_part1/ |
https://huggingface.co/parler-tts/parler-tts-mini-multilingual-v1.1 | Apache-2.0 |
| Parler-TTS | french | lrl_spoof/french/parlertts_part2/ |
https://huggingface.co/parler-tts/parler-tts-mini-multilingual-v1.1 | Apache-2.0 |
| Parler-TTS | polish | lrl_spoof/polish/parlertts/ |
https://huggingface.co/parler-tts/parler-tts-mini-multilingual-v1.1 | Apache-2.0 |
| Piper | catalan | lrl_spoof/catalan/pipertts/ |
https://github.com/OHF-Voice/piper1-gpl | GPL-3.0 |
| Piper | czech | lrl_spoof/czech/pipertts/ |
https://github.com/OHF-Voice/piper1-gpl | GPL-3.0 |
| Piper | danish | lrl_spoof/danish/pipertts/ |
https://github.com/OHF-Voice/piper1-gpl | GPL-3.0 |
| Piper | farsi | lrl_spoof/farsi/pipertts/ |
https://github.com/OHF-Voice/piper1-gpl | GPL-3.0 |
| Piper | georgian | lrl_spoof/georgian/pipertts/ |
https://github.com/OHF-Voice/piper1-gpl | GPL-3.0 |
| Piper | icelandic | lrl_spoof/icelandic/pipertts_part1/ |
https://github.com/OHF-Voice/piper1-gpl | GPL-3.0 |
| Piper | icelandic | lrl_spoof/icelandic/pipertts_part2/ |
https://github.com/OHF-Voice/piper1-gpl | GPL-3.0 |
| Piper | icelandic | lrl_spoof/icelandic/pipertts_part3/ |
https://github.com/OHF-Voice/piper1-gpl | GPL-3.0 |
| Piper | indonesian | lrl_spoof/indonesian/pipertts/ |
https://github.com/OHF-Voice/piper1-gpl | GPL-3.0 |
| Piper | kazakh | lrl_spoof/kazakh/pipertts_part1/ |
https://github.com/OHF-Voice/piper1-gpl | GPL-3.0 |
| Piper | kazakh | lrl_spoof/kazakh/pipertts_part2/ |
https://github.com/OHF-Voice/piper1-gpl | GPL-3.0 |
| Piper | luxembourgish | lrl_spoof/luxembourgish/pipertts/ |
https://github.com/OHF-Voice/piper1-gpl | GPL-3.0 |
| Piper | nepali | lrl_spoof/nepali/pipertts/ |
https://github.com/OHF-Voice/piper1-gpl | GPL-3.0 |
| Piper | polish | lrl_spoof/polish/pipertts/ |
https://github.com/OHF-Voice/piper1-gpl | GPL-3.0 |
| Piper | slovenian | lrl_spoof/slovenian/piper/ |
https://github.com/OHF-Voice/piper1-gpl | GPL-3.0 |
| Piper | welsh | lrl_spoof/welsh/pipertts/ |
https://github.com/OHF-Voice/piper1-gpl | GPL-3.0 |
| Crimean Tatar (Qirimtatar) TTS | crimean | lrl_spoof/crimean/qirimtatar_tts/ |
https://github.com/robinhad/qirimtatar-tts | MIT |
| RHVoice | kyrgyz | lrl_spoof/kyrgyz/rhvoice/ |
https://github.com/RHVoice/RHVoice | GPL-2.0 |
| Silero TTS | avar | lrl_spoof/avar/silero/ |
https://github.com/snakers4/silero-models | CC BY-NC-SA 4.0 |
| Silero TTS | bulgarian | lrl_spoof/bulgarian/silero_part1/ |
https://github.com/snakers4/silero-models | CC BY-NC-SA 4.0 |
| Silero TTS | bulgarian | lrl_spoof/bulgarian/silero_part2/ |
https://github.com/snakers4/silero-models | CC BY-NC-SA 4.0 |
| Silero TTS | bulgarian | lrl_spoof/bulgarian/silero_part3/ |
https://github.com/snakers4/silero-models | CC BY-NC-SA 4.0 |
| Silero TTS | chechen | lrl_spoof/chechen/silero_part1/ |
https://github.com/snakers4/silero-models | CC BY-NC-SA 4.0 |
| Silero TTS | chechen | lrl_spoof/chechen/silero_part2/ |
https://github.com/snakers4/silero-models | CC BY-NC-SA 4.0 |
| Silero TTS | chuvash | lrl_spoof/chuvash/silero_part1/ |
https://github.com/snakers4/silero-models | CC BY-NC-SA 4.0 |
| Silero TTS | chuvash | lrl_spoof/chuvash/silero_part2/ |
https://github.com/snakers4/silero-models | CC BY-NC-SA 4.0 |
| Silero TTS | chuvash | lrl_spoof/chuvash/silero_part3/ |
https://github.com/snakers4/silero-models | CC BY-NC-SA 4.0 |
| Silero TTS | erzya | lrl_spoof/erzya/silero/ |
https://github.com/snakers4/silero-models | CC BY-NC-SA 4.0 |
| Silero TTS | kalmyk | lrl_spoof/kalmyk/silero/ |
https://github.com/snakers4/silero-models | CC BY-NC-SA 4.0 |
| Silero TTS | khakassky | lrl_spoof/khakassky/silero/ |
https://github.com/snakers4/silero-models | CC BY-NC-SA 4.0 |
| Silero TTS | mari | lrl_spoof/mari/silero/ |
https://github.com/snakers4/silero-models | CC BY-NC-SA 4.0 |
| Silero TTS | moksha | lrl_spoof/moksha/silero_part1/ |
https://github.com/snakers4/silero-models | CC BY-NC-SA 4.0 |
| Silero TTS | moksha | lrl_spoof/moksha/silero_part2/ |
https://github.com/snakers4/silero-models | CC BY-NC-SA 4.0 |
| Silero TTS | moksha | lrl_spoof/moksha/silero_part3/ |
https://github.com/snakers4/silero-models | CC BY-NC-SA 4.0 |
| Silero TTS | nogai | lrl_spoof/nogai/silero/ |
https://github.com/snakers4/silero-models | CC BY-NC-SA 4.0 |
| Silero TTS | ossetian | lrl_spoof/ossetian/silero/ |
https://github.com/snakers4/silero-models | CC BY-NC-SA 4.0 |
| Silero TTS | yakut | lrl_spoof/yakut/silero/ |
https://github.com/snakers4/silero-models | CC BY-NC-SA 4.0 |
| SpeechT5 | croatian | lrl_spoof/croatian/speecht5_part1/ |
https://huggingface.co/nikolab/speecht5_tts_hr | MIT |
| SpeechT5 | croatian | lrl_spoof/croatian/speecht5_part2/ |
https://huggingface.co/nikolab/speecht5_tts_hr | MIT |
| SpeechT5 | uzbek | lrl_spoof/uzbek/speecht5/ |
https://huggingface.co/Inomjonov/speecht5-finetuned-uzbek-1102 | MIT |
| TurkicTTS | azerbaijanian | lrl_spoof/azerbaijanian/turkic_tts/ |
https://github.com/IS2AI/TurkicTTS | CC BY-NC-SA 4.0 |
| TurkicTTS | bashkir | lrl_spoof/bashkir/turkic_tts/ |
https://github.com/IS2AI/TurkicTTS | CC BY-NC-SA 4.0 |
| TurkicTTS | kazakh | lrl_spoof/kazakh/turkic_tts/ |
https://github.com/IS2AI/TurkicTTS | CC BY-NC-SA 4.0 |
| TurkicTTS | tatar | lrl_spoof/tatar/turkic_tts/ |
https://github.com/IS2AI/TurkicTTS | CC BY-NC-SA 4.0 |
| TurkicTTS | uzbek | lrl_spoof/uzbek/turkic_tts/ |
https://github.com/IS2AI/TurkicTTS | CC BY-NC-SA 4.0 |
| TurkicTTS | yakut | lrl_spoof/yakut/turkic_tts/ |
https://github.com/IS2AI/TurkicTTS | CC BY-NC-SA 4.0 |
| XTTS-v2 | czech | lrl_spoof/czech/xtts/ |
https://huggingface.co/coqui/XTTS-v2 | coqui-public-model-license |
| XTTS-v2 | hungarian | lrl_spoof/hungarian/xtts2/ |
https://huggingface.co/coqui/XTTS-v2 | coqui-public-model-license |
| XTTS-v2 | italian | lrl_spoof/italian/xtts2/ |
https://huggingface.co/coqui/XTTS-v2 | coqui-public-model-license |
| XTTS-v2 | russian | lrl_spoof/russian/xtts/ |
https://huggingface.co/coqui/XTTS-v2 | coqui-public-model-license |
| Zonos | japan | lrl_spoof/japan/zonos/ |
https://github.com/Zyphra/Zonos | Apache-2.0 |
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