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Datasets:
MTUCI
/
LRLspoof

Tasks:
Audio Classification
Modalities:
Image
Formats:
imagefolder
Languages:
Abkhaz
Armenian
Assamese
Size:
< 1K
ArXiv:
Tags:
antispoofing
Libraries:
Datasets
License:
Dataset card Data Studio Files
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@@ -74,4 +74,339 @@ tags:
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  pretty_name: LRL spoof
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  size_categories:
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  - 1M<n<10M
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- ---
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
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  pretty_name: LRL spoof
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  size_categories:
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  - 1M<n<10M
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+ ---
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+
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+ # LRLspoof: Low-Resource Language Spoofing Dataset
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+
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+ 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.
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+
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+
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+ **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.
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+
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+ **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.
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+
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+ ---
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+
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+ ## Overview
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+
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+ - **Purpose:** Benchmark and develop anti-spoofing / deepfake detection systems for under-resourced and multilingual settings.
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+ - **Content:** Synthetic speech utterances generated by various TTS models, with transcriptions.
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+ - **Structure:** One directory per **language**, under it one directory per **TTS model** (or model part). Each model folder contains:
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+ - **Audio:** `.wav` files (e.g. `1.wav`, `2.wav`, …).
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+ - **Transcriptions:** a `.txt` file (one sentence per line, aligned with the audio indices where applicable).
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+
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+ ---
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+
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+ ## Statistics
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+
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+ - **Number of languages:** 66
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+ - **Number of TTS systems:** 23
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+ - **Total hours:** 2732.17
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+
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+
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+
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+ Total audio duration (hours) by TTS model:
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+
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+ ![Duration by TTS model](duration_by_tts_model.png)
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+
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+ Total audio duration (hours) by language:
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+
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+ ![Duration by language](duration_by_language.png)
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+
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+
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+ **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.
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+
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+ | Model | MSRR (All) | PSRR (All) | MSRR (Low) | PSRR (Low) |
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+ |-------|------------|------------|------------|------------|
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+ | [AASIST3](https://huggingface.co/MTUCI/AASIST3) | 90.40 | 91.40 | 93.28 | 94.28 |
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+ | [DF Arena 1B](https://huggingface.co/Speech-Arena-2025/DF_Arena_1B_V_1) | 71.07 | 70.53 | 73.62 | 74.89 |
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+ | [DF Arena 500M](https://huggingface.co/Speech-Arena-2025/DF_Arena_500M_V_1) | 63.47 | 58.50 | 67.31 | 62.47 |
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+ | [Rest2TCNGuard](https://github.com/mtuciru/Res2TCNGuard) | 33.07 | 35.37 | 37.38 | 42.94 |
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+ | [ResCapsGuard](https://github.com/mtuciru/ResCapsGuard) | 41.29 | 40.56 | 40.81 | 40.65 |
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+ | [XSLS](https://github.com/QiShanZhang/SLSforASVspoof-2021-DF) | 36.04 | 34.85 | 39.66 | 39.97 |
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+ | [Wav2Vec+AASIST](https://github.com/TakHemlata/SSL_Anti-spoofing) | 45.62 | 43.48 | 50.09 | 49.34 |
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+ | [TCM-ADD](https://github.com/ductuantruong/tcm_add) | 45.93 | 43.20 | 51.30 | 49.66 |
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+ | [Nes2Net](https://github.com/Liu-Tianchi/Nes2Net) | 34.23 | 30.85 | 38.34 | 35.61 |
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+ | [wav2vec2-xls-r-1b-DeepFake-AI4TRUST](https://huggingface.co/DavidCombei/wav2vec2-xls-r-1b-DeepFake-AI4TRUST) | 26.79 | 26.07 | 30.28 | 30.14 |
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+ | [wav2vec2-xls-r-300m-deepfake-V1](https://huggingface.co/DavidCombei/wav2vec2-xls-r-300m-deepfake-V1) | 80.51 | 78.32 | 83.90 | 81.29 |
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+ | [Spectra-0](https://huggingface.co/MTUCI/spectra_0) | **97.11** | **97.47** | **96.67** | **97.23** |
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+
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+ ---
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+
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+ ## Dataset Structure
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+
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+ ```
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+ lrl_spoof/
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+ ├── <language_1>/ # e.g. english, polish, hindi
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+ │ ├── <model_1>/ # e.g. pipertts, kokoro_part1
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+ │ │ ├── 1.wav
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+ │ │ ├── 2.wav
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+ │ │ └── ...
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+ │ ├── <model_1>.txt # transcriptions for model_1 (when present)
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+ │ ├── <model_2>/
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+ │ └── ...
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+ ├── <language_2>/
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+ └── ...
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+ ```
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+
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+ - **Path to a given subset:** `lrl_spoof/<language>/<model>/` (audio) and `lrl_spoof/<language>/<model>.txt` (transcriptions, when present).
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+
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+ ---
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+
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+ ## Download, Combining Parts, and Unpacking
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+
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+ 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.
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+
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+ ### Combining parts
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+
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+ *[Add the exact filenames and commands you use. Example for Linux/macOS:]*
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+
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+ ```bash
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+ # Example: if parts are named lrl_spoof.tar.gz.part_aa, .part_ab, ...
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+ cat lrl_spoof.tar.gz.part_* > lrl_spoof.tar.gz
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+ ```
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+
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+ ### Unpacking
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+
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+ ```bash
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+ tar -xzf lrl_spoof.tar.gz
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+ ```
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+
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+
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+ ---
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+
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+ ## Contact
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+
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+ - **Email:** k.n.borodin@mtuci.ru
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+ - **Telegram channel:** https://t.me/korallll_ai
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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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+ If you use this dataset in your research, please cite the accompanying paper:
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+
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+ ```bibtex
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+ @misc{borodin2026spoofdetectorstravelevaluation,
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+ title={When Spoof Detectors Travel: Evaluation Across 66 Languages in the Low-Resource Language Spoofing Corpus},
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+ author={Kirill Borodin and Vasiliy Kudryavtsev and Maxim Maslov and Mikhail Gorodnichev and Grach Mkrtchian},
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+ year={2026},
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+ eprint={2603.02364},
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+ archivePrefix={arXiv},
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+ primaryClass={cs.SD},
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+ url={https://arxiv.org/abs/2603.02364},
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+ }
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+ ```
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+
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+
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+ ### Checksums
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+
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+ 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).
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+
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+ ```bash
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+ # Verify the combined archive
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+ sha256sum lrl_spoof.tar.gz
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+
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+ # Verify all parts (run in the directory containing the parts)
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+ sha256sum lrl_spoof.tar.gz.part_* > lrl_spoof_parts.sha256
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+ cat lrl_spoof_parts.sha256
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+ ```
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+
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+ After combining parts, verify the full archive with the checksum below. You can also verify each part before combining.
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+
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+ **Whole archive** (after combining parts into `lrl_spoof.tar.gz`):
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+
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+ ```
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+ lrl_spoof.tar.gz 624cba39b9c60d35ec90c9ee4450385ad885ca31c093e9a6de592f5f524e203b
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+ ```
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+
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+ **Per-part checksums** (SHA256 of each part file):
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+
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+ | Part file | SHA256 |
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+ |-----------|--------|
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+ | `lrl_spoof.tar.gz.part_aa` | ee37cb5a5de1dcc2226d2a1f7d1b986d81529fd0a6ceac354a13f184ec9a8df0 |
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+ | `lrl_spoof.tar.gz.part_ab` | 4704e5020710d4151fe986f510bec861d7ff5cc8e7ee2403c01dca7b0cf9ab74 |
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+ | `lrl_spoof.tar.gz.part_bq` | 13b67216fe92b3b7d1cc1525fde3881a0b1768a0ccacbedbd23aa31b57e0232a |
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+
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+
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+
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+
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+ ---
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+
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+ ## Languages and TTS Models
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+
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+ 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.
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+
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+ **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.
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+
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+ | Model | Language | Path in dataset | Link to model | Licence |
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+ |-------|----------|-----------------|----------------|------|
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+ | aHoTTS | catalan | `lrl_spoof/catalan/ahotts/` | https://github.com/hitz-zentroa/aHoTTS| Apache-2.0 |
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+ | Chatterbox | finnish | `lrl_spoof/finnish/chatterbox/` |https://github.com/resemble-ai/chatterbox | MIT |
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+ | Chatterbox | malasian | `lrl_spoof/malasian/chatterbox/` |https://github.com/resemble-ai/chatterbox | MIT |
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+ | Chatterbox | malayalam | `lrl_spoof/malayalam/chatterbox/` |https://github.com/resemble-ai/chatterbox | MIT |
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+ | Chatterbox | norwegian | `lrl_spoof/norwegian/chatterbox_part1/` |https://github.com/resemble-ai/chatterbox | MIT |
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+ | Chatterbox | norwegian | `lrl_spoof/norwegian/chatterbox_part2/` |https://github.com/resemble-ai/chatterbox | MIT |
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+ | Chatterbox | polish | `lrl_spoof/polish/chatterbox_part1/` |https://github.com/resemble-ai/chatterbox | MIT |
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+ | Chatterbox | polish | `lrl_spoof/polish/chatterbox_part2/` |https://github.com/resemble-ai/chatterbox | MIT |
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+ | Chatterbox | swahili | `lrl_spoof/swahili/chatterbox/` |https://github.com/resemble-ai/chatterbox | MIT |
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+ | Fun-CosyVoice 3.0 | japan | `lrl_spoof/japan/cosyvoice3/` |https://github.com/FunAudioLLM/CosyVoice |Apache-2.0 |
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+ | Fun-CosyVoice 3.0 | korean | `lrl_spoof/korean/cosyvoice3/` | https://github.com/FunAudioLLM/CosyVoice|Apache-2.0 |
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+ | eSpeak NG | armenian | `lrl_spoof/armenian/espeak/` |https://github.com/espeak-ng/espeak-ng | GPL-3.0 |
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+ | eSpeak NG | azerbaijanian | `lrl_spoof/azerbaijanian/espeak/` |https://github.com/espeak-ng/espeak-ng |GPL-3.0 |
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+ | eSpeak NG | bashkir | `lrl_spoof/bashkir/espeak/` |https://github.com/espeak-ng/espeak-ng |GPL-3.0 |
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+ | eSpeak NG | bulgarian | `lrl_spoof/bulgarian/espeak_part1/` |https://github.com/espeak-ng/espeak-ng |GPL-3.0 |
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+ | eSpeak NG | bulgarian | `lrl_spoof/bulgarian/espeak_part2/` |https://github.com/espeak-ng/espeak-ng |GPL-3.0 |
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+ | eSpeak NG | chuvash | `lrl_spoof/chuvash/espeak/` |https://github.com/espeak-ng/espeak-ng |GPL-3.0 |
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+ | eSpeak NG | georgian | `lrl_spoof/georgian/espeak/` |https://github.com/espeak-ng/espeak-ng |GPL-3.0 |
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+ | eSpeak NG | kazakh | `lrl_spoof/kazakh/espeak/` |https://github.com/espeak-ng/espeak-ng |GPL-3.0 |
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+ | eSpeak NG | kyrgyz | `lrl_spoof/kyrgyz/espeak/` |https://github.com/espeak-ng/espeak-ng |GPL-3.0 |
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+ | eSpeak NG | turkmen | `lrl_spoof/turkmen/espeak/` |https://github.com/espeak-ng/espeak-ng |GPL-3.0 |
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+ | IMS-Toucan | abkhazian | `lrl_spoof/abkhazian/ims_toucan/` | https://github.com/DigitalPhonetics/IMS-Toucan| Apache-2.0 |
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+ | IMS-Toucan | armenian | `lrl_spoof/armenian/ims_toucan/` |https://github.com/DigitalPhonetics/IMS-Toucan |Apache-2.0 |
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+ | IMS-Toucan | azerbaijanian | `lrl_spoof/azerbaijanian/ims_toucan/` | https://github.com/DigitalPhonetics/IMS-Toucan|Apache-2.0 |
308
+ | IMS-Toucan | bashkir | `lrl_spoof/bashkir/ims_toucan/` |https://github.com/DigitalPhonetics/IMS-Toucan |Apache-2.0 |
309
+ | IMS-Toucan | chuvash | `lrl_spoof/chuvash/ims_toucan/` |https://github.com/DigitalPhonetics/IMS-Toucan |Apache-2.0 |
310
+ | IMS-Toucan | czech | `lrl_spoof/czech/ims_toucan/` |https://github.com/DigitalPhonetics/IMS-Toucan |Apache-2.0 |
311
+ | IMS-Toucan | karachai_balkar | `lrl_spoof/karachai_balkar/ims_toucan/` |https://github.com/DigitalPhonetics/IMS-Toucan |Apache-2.0 |
312
+ | IMS-Toucan | lezgian | `lrl_spoof/lezgian/ims_toucan/` |https://github.com/DigitalPhonetics/IMS-Toucan |Apache-2.0 |
313
+ | IMS-Toucan | tuvan | `lrl_spoof/tuvan/ims_toucan/` |https://github.com/DigitalPhonetics/IMS-Toucan |Apache-2.0 |
314
+ | Indic-TTS | assamese | `lrl_spoof/assamese/indictts/` |https://github.com/AI4Bharat/Indic-TTS |MIT |
315
+ | Indic-TTS | bodo | `lrl_spoof/bodo/indictts/` |https://github.com/AI4Bharat/Indic-TTS |MIT |
316
+ | Indic-TTS | gujarati | `lrl_spoof/gujarati/indictts/` |https://github.com/AI4Bharat/Indic-TTS |MIT |
317
+ | Indic-TTS | hindi | `lrl_spoof/hindi/indictts/` |https://github.com/AI4Bharat/Indic-TTS |MIT |
318
+ | Indic-TTS | malayalam | `lrl_spoof/malayalam/indictts/` |https://github.com/AI4Bharat/Indic-TTS |MIT |
319
+ | Indic-TTS | manipuri | `lrl_spoof/manipuri/indictts/` |https://github.com/AI4Bharat/Indic-TTS |MIT |
320
+ | Indic-TTS | marathi | `lrl_spoof/marathi/indictts_part1/` |https://github.com/AI4Bharat/Indic-TTS |MIT |
321
+ | Indic-TTS | marathi | `lrl_spoof/marathi/indictts_part2/` |https://github.com/AI4Bharat/Indic-TTS |MIT |
322
+ | Indic-TTS | odia | `lrl_spoof/odia/indictts/` |https://github.com/AI4Bharat/Indic-TTS |MIT |
323
+ | Indic-TTS | rajasthani | `lrl_spoof/rajasthani/indictts/` |https://github.com/AI4Bharat/Indic-TTS |MIT |
324
+ | Indic-TTS | telugu | `lrl_spoof/telugu/indictts/` |https://github.com/AI4Bharat/Indic-TTS |MIT |
325
+ | Fast Pitch | english | `lrl_spoof/english/fastpitch/` |https://github.com/dan-wells/fastpitch | BSD-3-Clause |
326
+ | F5-TTS | chuvash | `lrl_spoof/chuvash/f5/` | https://huggingface.co/Misha24-10/F5-TTS_CHUVASH | CC BY-NC-4.0 |
327
+ | FishAudio S1 | polish | `lrl_spoof/polish/fishspeech/` |https://huggingface.co/fishaudio/s1-mini | CC BY-NC-SA-4.0 |
328
+ | Kokoro | brazilian | `lrl_spoof/brazilian/kokoro/` |https://github.com/hexgrad/kokoro |Apache-2.0 |
329
+ | Kokoro | english | `lrl_spoof/english/kokoro_part1/` |https://github.com/hexgrad/kokoro |Apache-2.0 |
330
+ | Kokoro | english | `lrl_spoof/english/kokoro_part2/` |https://github.com/hexgrad/kokoro |Apache-2.0 |
331
+ | Kokoro | french | `lrl_spoof/french/kokoro_part1/` |https://github.com/hexgrad/kokoro |Apache-2.0 |
332
+ | Kokoro | french | `lrl_spoof/french/kokoro_part2/` |https://github.com/hexgrad/kokoro |Apache-2.0 |
333
+ | Kokoro | french | `lrl_spoof/french/kokoro_part3/` |https://github.com/hexgrad/kokoro |Apache-2.0 |
334
+ | Kokoro | hindi | `lrl_spoof/hindi/kokoro/` |https://github.com/hexgrad/kokoro |Apache-2.0 |
335
+ | Kokoro | italian | `lrl_spoof/italian/kokoro/` |https://github.com/hexgrad/kokoro |Apache-2.0 |
336
+ | Kokoro | japan | `lrl_spoof/japan/kokoro/` |https://github.com/hexgrad/kokoro |Apache-2.0 |
337
+ | Matcha-TTS | kyrgyz | `lrl_spoof/kyrgyz/matcha/` |https://huggingface.co/kyrgyz-ai/akylai-tts-mini | MIT |
338
+ | MeloTTS | australian | `lrl_spoof/australian/melotts/` | https://github.com/myshell-ai/MeloTTS| MIT |
339
+ | MeloTTS | english | `lrl_spoof/english/melotts/` |https://github.com/myshell-ai/MeloTTS | MIT |
340
+ | MeloTTS | japan | `lrl_spoof/japan/melotts/` |https://github.com/myshell-ai/MeloTTS | MIT |
341
+ | MeloTTS | korean | `lrl_spoof/korean/melotts/` | https://github.com/myshell-ai/MeloTTS| MIT |
342
+ | MeloTTS | spanish | `lrl_spoof/spanish/melotts/` |https://github.com/myshell-ai/MeloTTS | MIT |
343
+ | MMS TTS | armenian | `lrl_spoof/armenian/mms_tts/` | https://huggingface.co/facebook/mms-tts-hyw| CC BY-NC-4.0 |
344
+ | MMS TTS | azerbaijanian | `lrl_spoof/azerbaijanian/mms_tts/` |https://huggingface.co/facebook/mms-tts-azb | CC BY-NC-4.0 |
345
+ | MMS TTS | bashkir | `lrl_spoof/bashkir/mms_tts/` |https://huggingface.co/facebook/mms-tts-bak |CC BY-NC-4.0 |
346
+ | MMS TTS | chuvash | `lrl_spoof/chuvash/mms_tts/` |https://huggingface.co/facebook/mms-tts-chv |CC BY-NC-4.0 |
347
+ | MMS TTS | dutch | `lrl_spoof/dutch/mms_tts/` |https://huggingface.co/facebook/mms-tts-nld |CC BY-NC-4.0 |
348
+ | MMS TTS | latvian | `lrl_spoof/latvian/mms_tts/` |https://huggingface.co/facebook/mms-tts-lav | CC BY-NC-4.0 |
349
+ | MMS TTS | yakut | `lrl_spoof/yakut/mms_tts/` |https://huggingface.co/facebook/mms-tts-sah | CC BY-NC-4.0 |
350
+ | OuteTTS | belarusian | `lrl_spoof/belarusian/outetts/` |https://huggingface.co/unsloth/Llama-OuteTTS-1.0-1B | CC BY-NC-SA-4.0|
351
+ | OuteTTS | georgian | `lrl_spoof/georgian/outetts/` |https://huggingface.co/unsloth/Llama-OuteTTS-1.0-1B | CC BY-NC-SA-4.0|
352
+ | OuteTTS | hungarian | `lrl_spoof/hungarian/outetts/` | https://huggingface.co/unsloth/Llama-OuteTTS-1.0-1B| CC BY-NC-SA-4.0|
353
+ | OuteTTS | lithuanian | `lrl_spoof/lithuanian/outetts/` | https://huggingface.co/unsloth/Llama-OuteTTS-1.0-1B| CC BY-NC-SA-4.0|
354
+ | OuteTTS | polish | `lrl_spoof/polish/outetts/` |https://huggingface.co/unsloth/Llama-OuteTTS-1.0-1B | CC BY-NC-SA-4.0|
355
+ | OuteTTS | russian | `lrl_spoof/russian/outetts/` |https://huggingface.co/unsloth/Llama-OuteTTS-1.0-1B | CC BY-NC-SA-4.0|
356
+ | Parler-TTS | english | `lrl_spoof/english/parlertts_part1/` | https://huggingface.co/parler-tts/parler-tts-mini-multilingual-v1.1|Apache-2.0 |
357
+ | Parler-TTS | english | `lrl_spoof/english/parlertts_part2/` |https://huggingface.co/parler-tts/parler-tts-mini-multilingual-v1.1 |Apache-2.0 |
358
+ | Parler-TTS | english | `lrl_spoof/english/parlertts_part3/` |https://huggingface.co/parler-tts/parler-tts-mini-multilingual-v1.1 |Apache-2.0 |
359
+ | Parler-TTS | french | `lrl_spoof/french/parlertts_part1/` | https://huggingface.co/parler-tts/parler-tts-mini-multilingual-v1.1|Apache-2.0 |
360
+ | Parler-TTS | french | `lrl_spoof/french/parlertts_part2/` | https://huggingface.co/parler-tts/parler-tts-mini-multilingual-v1.1 |Apache-2.0 |
361
+ | Parler-TTS | polish | `lrl_spoof/polish/parlertts/` |https://huggingface.co/parler-tts/parler-tts-mini-multilingual-v1.1 |Apache-2.0 |
362
+ | Piper | catalan | `lrl_spoof/catalan/pipertts/` |https://github.com/OHF-Voice/piper1-gpl | GPL-3.0 |
363
+ | Piper | czech | `lrl_spoof/czech/pipertts/` |https://github.com/OHF-Voice/piper1-gpl | GPL-3.0 |
364
+ | Piper | danish | `lrl_spoof/danish/pipertts/` |https://github.com/OHF-Voice/piper1-gpl | GPL-3.0 |
365
+ | Piper | farsi | `lrl_spoof/farsi/pipertts/` |https://github.com/OHF-Voice/piper1-gpl | GPL-3.0 |
366
+ | Piper | georgian | `lrl_spoof/georgian/pipertts/` |https://github.com/OHF-Voice/piper1-gpl | GPL-3.0 |
367
+ | Piper | icelandic | `lrl_spoof/icelandic/pipertts_part1/` |https://github.com/OHF-Voice/piper1-gpl |GPL-3.0 |
368
+ | Piper | icelandic | `lrl_spoof/icelandic/pipertts_part2/` |https://github.com/OHF-Voice/piper1-gpl |GPL-3.0 |
369
+ | Piper | icelandic | `lrl_spoof/icelandic/pipertts_part3/` |https://github.com/OHF-Voice/piper1-gpl |GPL-3.0 |
370
+ | Piper | indonesian | `lrl_spoof/indonesian/pipertts/` |https://github.com/OHF-Voice/piper1-gpl |GPL-3.0 |
371
+ | Piper | kazakh | `lrl_spoof/kazakh/pipertts_part1/` |https://github.com/OHF-Voice/piper1-gpl |GPL-3.0 |
372
+ | Piper | kazakh | `lrl_spoof/kazakh/pipertts_part2/` | https://github.com/OHF-Voice/piper1-gpl|GPL-3.0 |
373
+ | Piper | luxembourgish | `lrl_spoof/luxembourgish/pipertts/` | https://github.com/OHF-Voice/piper1-gpl|GPL-3.0 |
374
+ | Piper | nepali | `lrl_spoof/nepali/pipertts/` |https://github.com/OHF-Voice/piper1-gpl |GPL-3.0 |
375
+ | Piper | polish | `lrl_spoof/polish/pipertts/` |https://github.com/OHF-Voice/piper1-gpl |GPL-3.0 |
376
+ | Piper | slovenian | `lrl_spoof/slovenian/piper/` |https://github.com/OHF-Voice/piper1-gpl |GPL-3.0 |
377
+ | Piper | welsh | `lrl_spoof/welsh/pipertts/` |https://github.com/OHF-Voice/piper1-gpl |GPL-3.0 |
378
+ | Crimean Tatar (Qirimtatar) TTS | crimean | `lrl_spoof/crimean/qirimtatar_tts/` | https://github.com/robinhad/qirimtatar-tts| MIT |
379
+ | RHVoice | kyrgyz | `lrl_spoof/kyrgyz/rhvoice/` |https://github.com/RHVoice/RHVoice | GPL-2.0 |
380
+ | Silero TTS | avar | `lrl_spoof/avar/silero/` |https://github.com/snakers4/silero-models | CC BY-NC-SA 4.0 |
381
+ | Silero TTS | bulgarian | `lrl_spoof/bulgarian/silero_part1/` |https://github.com/snakers4/silero-models |CC BY-NC-SA 4.0 |
382
+ | Silero TTS | bulgarian | `lrl_spoof/bulgarian/silero_part2/` |https://github.com/snakers4/silero-models |CC BY-NC-SA 4.0 |
383
+ | Silero TTS | bulgarian | `lrl_spoof/bulgarian/silero_part3/` |https://github.com/snakers4/silero-models |CC BY-NC-SA 4.0 |
384
+ | Silero TTS | chechen | `lrl_spoof/chechen/silero_part1/` |https://github.com/snakers4/silero-models |CC BY-NC-SA 4.0 |
385
+ | Silero TTS | chechen | `lrl_spoof/chechen/silero_part2/` |https://github.com/snakers4/silero-models |CC BY-NC-SA 4.0 |
386
+ | Silero TTS | chuvash | `lrl_spoof/chuvash/silero_part1/` |https://github.com/snakers4/silero-models |CC BY-NC-SA 4.0 |
387
+ | Silero TTS | chuvash | `lrl_spoof/chuvash/silero_part2/` |https://github.com/snakers4/silero-models |CC BY-NC-SA 4.0 |
388
+ | Silero TTS | chuvash | `lrl_spoof/chuvash/silero_part3/` |https://github.com/snakers4/silero-models |CC BY-NC-SA 4.0 |
389
+ | Silero TTS | erzya | `lrl_spoof/erzya/silero/` |https://github.com/snakers4/silero-models |CC BY-NC-SA 4.0 |
390
+ | Silero TTS | kalmyk | `lrl_spoof/kalmyk/silero/` |https://github.com/snakers4/silero-models |CC BY-NC-SA 4.0 |
391
+ | Silero TTS | khakassky | `lrl_spoof/khakassky/silero/` |https://github.com/snakers4/silero-models |CC BY-NC-SA 4.0 |
392
+ | Silero TTS | mari | `lrl_spoof/mari/silero/` |https://github.com/snakers4/silero-models |CC BY-NC-SA 4.0 |
393
+ | Silero TTS | moksha | `lrl_spoof/moksha/silero_part1/` |https://github.com/snakers4/silero-models |CC BY-NC-SA 4.0 |
394
+ | Silero TTS | moksha | `lrl_spoof/moksha/silero_part2/` |https://github.com/snakers4/silero-models |CC BY-NC-SA 4.0 |
395
+ | Silero TTS | moksha | `lrl_spoof/moksha/silero_part3/` |https://github.com/snakers4/silero-models |CC BY-NC-SA 4.0 |
396
+ | Silero TTS | nogai | `lrl_spoof/nogai/silero/` |https://github.com/snakers4/silero-models |CC BY-NC-SA 4.0 |
397
+ | Silero TTS | ossetian | `lrl_spoof/ossetian/silero/` |https://github.com/snakers4/silero-models |CC BY-NC-SA 4.0 |
398
+ | Silero TTS | yakut | `lrl_spoof/yakut/silero/` |https://github.com/snakers4/silero-models |CC BY-NC-SA 4.0 |
399
+ | SpeechT5 | croatian | `lrl_spoof/croatian/speecht5_part1/` |https://huggingface.co/nikolab/speecht5_tts_hr | MIT |
400
+ | SpeechT5 | croatian | `lrl_spoof/croatian/speecht5_part2/` |https://huggingface.co/nikolab/speecht5_tts_hr | MIT |
401
+ | SpeechT5 | uzbek | `lrl_spoof/uzbek/speecht5/` |https://huggingface.co/Inomjonov/speecht5-finetuned-uzbek-1102 | MIT |
402
+ | TurkicTTS | azerbaijanian | `lrl_spoof/azerbaijanian/turkic_tts/` | https://github.com/IS2AI/TurkicTTS|CC BY-NC-SA 4.0 |
403
+ | TurkicTTS | bashkir | `lrl_spoof/bashkir/turkic_tts/` |https://github.com/IS2AI/TurkicTTS |CC BY-NC-SA 4.0 |
404
+ | TurkicTTS | kazakh | `lrl_spoof/kazakh/turkic_tts/` |https://github.com/IS2AI/TurkicTTS |CC BY-NC-SA 4.0 |
405
+ | TurkicTTS | tatar | `lrl_spoof/tatar/turkic_tts/` |https://github.com/IS2AI/TurkicTTS |CC BY-NC-SA 4.0 |
406
+ | TurkicTTS | uzbek | `lrl_spoof/uzbek/turkic_tts/` |https://github.com/IS2AI/TurkicTTS |CC BY-NC-SA 4.0 |
407
+ | TurkicTTS | yakut | `lrl_spoof/yakut/turkic_tts/` |https://github.com/IS2AI/TurkicTTS |CC BY-NC-SA 4.0 |
408
+ | XTTS-v2 | czech | `lrl_spoof/czech/xtts/` |https://huggingface.co/coqui/XTTS-v2 | coqui-public-model-license|
409
+ | XTTS-v2 | hungarian | `lrl_spoof/hungarian/xtts2/` | https://huggingface.co/coqui/XTTS-v2| coqui-public-model-license |
410
+ | XTTS-v2 | italian | `lrl_spoof/italian/xtts2/` |https://huggingface.co/coqui/XTTS-v2 | coqui-public-model-license |
411
+ | XTTS-v2 | russian | `lrl_spoof/russian/xtts/` | https://huggingface.co/coqui/XTTS-v2| coqui-public-model-license |
412
+ | Zonos | japan | `lrl_spoof/japan/zonos/` |https://github.com/Zyphra/Zonos | Apache-2.0 |