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Datasets:
leeoxiang
/
multi_lingo_data

Tasks:
Text-to-Speech
Audio-to-Audio
Modalities:
Audio
Tabular
Text
Languages:
English
Japanese
Korean
Size:
1K - 10K
License:
Dataset card Data Studio Files
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Wipe repo contents to prepare for re-upload

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  1. README.md +0 -96
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README.md DELETED
@@ -1,96 +0,0 @@
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- ---
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- pretty_name: Fish-Speech Cross-Lingual Voice-Cloning Prompts
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- license: cc-by-nc-4.0
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- language:
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- - zh
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- - en
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- - ja
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- - ko
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- task_categories:
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- - text-to-speech
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- - audio-to-audio
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- tags:
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- - tts
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- - text-to-speech
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- - voice-cloning
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- - cross-lingual
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- - fish-speech
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- - s2-pro
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- - synthetic
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- size_categories:
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- - 10K<n<100K
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- configs:
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- - config_name: default
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- data_files:
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- - split: train
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- path: metadata.csv
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- ---
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-
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- # Fish-Speech Cross-Lingual Voice-Cloning Prompts
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-
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- Cross-lingual TTS samples generated with **fish-speech S2-Pro**, intended
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- as reference prompts for second-stage same-language expansion and for
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- studying cross-lingual voice-cloning behavior of fish-speech.
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-
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- ## Contents
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-
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- - `audios_prompts/` — 14400 wavs, ~57.5 hours total
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- - `metadata.csv` — HuggingFace `audiofolder`-compatible index. `file_name`
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- column points at the wav path relative to dataset root. Load directly
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- with `datasets.load_dataset("audiofolder", data_dir="<root>")`.
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- - `records.jsonl` — one row per wav in JSONL form (same info as
42
- `metadata.csv` plus the raw manifest fields). Kept under a non-
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- `metadata.*` name so it does not conflict with the audiofolder
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- builder, which refuses to load a repo containing both
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- `metadata.csv` and `metadata.jsonl`.
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- - `references.jsonl` — the 1200 real Emilia speakers used as fish-speech
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- references (speaker_id, lang, text, duration, dnsmos, source_file, ref_id;
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- internal audio paths stripped)
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- - `texts/{zh,en,ja,ko}_text.jsonl` — source target texts fed to fish-speech
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- - `README.md` — this file
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-
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- ## Generation setup
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-
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- - Model: fish-speech S2-Pro
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- - Sampling: top_p=0.8, temperature=0.8, repetition_penalty=1.1
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- - Reference source: Emilia (zh/en/ja/ko subsets), filtered by
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- duration in [4s, 15s], DNSMOS ≥ 3.0, top-300 speakers per language by
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- DNSMOS → **1200 unique speakers**
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- - Per (speaker, target-lang), 3 random texts sampled from the target
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- language's text pool (deterministic per-speaker seed)
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- - Total = 1200 speakers × 4 target languages × 3 texts = 14,400 wavs
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-
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- ## Language-pair distribution
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-
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- | ref_lang → lang | count |
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- |---|---|
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- | en→en | 900 |
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- | en→ja | 900 |
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- | en→ko | 900 |
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- | en→zh | 900 |
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- | ja→en | 900 |
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- | ja→ja | 900 |
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- | ja→ko | 900 |
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- | ja→zh | 900 |
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- | ko→en | 900 |
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- | ko→ja | 900 |
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- | ko→ko | 900 |
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- | ko→zh | 900 |
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- | zh→en | 900 |
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- | zh→ja | 900 |
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- | zh→ko | 900 |
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- | zh→zh | 900 |
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-
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- ## Wav-path convention
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-
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- `file_name` in `metadata.csv` (and `wav_path` in `records.jsonl`) is
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- **relative to this dataset root**:
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- `audios_prompts/<ref_id>/<lang>/<text_id:03d>.wav`.
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-
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- ## Caveats
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-
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- - **Not filtered by ASR quality yet.** WER/CER not yet computed. Some
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- cross-lingual synthesis may have accent drift or text errors.
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- - Reference speakers come from Emilia; per-speaker duration in refs is
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- the single-utterance duration used as fish-speech prompt (~5–15 s).
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- - Sample rate 44.1 kHz (fish-speech native).
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
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