| --- |
| pretty_name: YodaLingua English TTS Arena — Model Outputs & Human Preferences |
| license: other |
| language: |
| - en |
| task_categories: |
| - text-to-speech |
| size_categories: |
| - 1K<n<10K |
| tags: |
| - audio |
| - text-to-speech |
| - tts |
| - voice-cloning |
| - human-preferences |
| - pairwise-ranking |
| - benchmark |
| - english |
| - leaderboard |
| configs: |
| - config_name: outputs |
| default: true |
| data_files: |
| - split: test |
| path: data/outputs/*.parquet |
| - config_name: judgments |
| data_files: |
| - split: train |
| path: data/judgments/*.parquet |
| - config_name: prompts |
| data_files: |
| - split: test |
| path: data/prompts/*.parquet |
| - config_name: model_summary |
| data_files: |
| - split: test |
| path: data/model_summary/*.parquet |
| --- |
| |
| # YodaLingua English TTS Arena |
|
|
| **1,080 generated clips · 18 TTS systems · |
| 301 anonymous pairwise judgments · 20 reference |
| speakers · 60 distinct prompts** |
|
|
| This is the public English snapshot of the |
| [YodaLingua multilingual TTS Arena](https://huggingface.co/spaces/Thomcles/yodalingua-tts-arena). |
| It pairs model outputs, shared zero-shot voice references, objective measurements, and |
| privacy-safe human preferences on the same frozen evaluation protocol. |
|
|
| ## Start here |
|
|
| The default **`outputs`** configuration has one row per model × prompt, so the viewer |
| opens on **1,080 playable generated clips**, not a 60-row prompt table. |
|
|
| ```python |
| from datasets import load_dataset |
| |
| outputs = load_dataset( |
| "Thomcles/YodaLingua-TTS-Arena-English", |
| "outputs", |
| split="test", |
| ) |
| judgments = load_dataset( |
| "Thomcles/YodaLingua-TTS-Arena-English", |
| "judgments", |
| split="train", |
| ) |
| ``` |
|
|
| | Configuration | Rows | Intended use | |
| |---|---:|---| |
| | `outputs` | 1,080 | Listen, filter by model/task, recompute metrics | |
| | `judgments` | 301 | Pairwise ranking and preference research | |
| | `prompts` | 60 | Shared texts and reference voices | |
| | `model_summary` | 72 | Ready-to-use objective and early preference summaries | |
|
|
| ## Evaluation design |
|
|
| - **Natural:** conversational rhythm, spontaneity, and varied sentence structure. |
| - **Expressive:** emotion, prosody, intention, and storytelling delivery. |
| - **Pronunciation:** proper nouns, rare words, loanwords, and difficult sequences. |
| - **Protocol:** 20 speakers × 3 unique prompts per speaker = 60 English trials per model. |
| - **Coverage:** 18 systems have complete English output coverage in this snapshot. |
| - **No cherry-picking:** model failures, repetitions, and hallucinations remain part of the data. |
|
|
| ## What you can build |
|
|
| - Compare TTS and zero-shot voice-cloning systems on identical inputs. |
| - Audit pronunciation, naturalness, expressiveness, cloning similarity, and failure modes. |
| - Recompute WER, CER, speaker similarity, and ranking methods. |
| - Train or test preference models, evaluators, and leaderboard tooling. |
| - Create internal model-selection reports while retaining exact benchmark provenance. |
|
|
| ## Configurations |
|
|
| ### `outputs` |
|
|
| Contains the generated FLAC bytes, target text, anonymized speaker ID, task, immutable |
| model revision or provider alias, model-specific license, inference timing, WER/CER |
| components, ASR transcript, and speaker similarity. `rtf` is generation time divided by |
| audio duration. API timing includes network/provider latency and is not a controlled L4 |
| comparison. |
|
|
| ### `judgments` |
|
|
| Contains only the trial/task, randomized A/B model identities, `a`, `b`, or `tie`, and |
| the preferred model when applicable. It deliberately excludes session/viewer identifiers, |
| IP or device information, comparison IDs, playback events, and exact timestamps. |
|
|
| ### `prompts` |
|
|
| Contains each reference FLAC and target text once. Speaker IDs are release-scoped, |
| deterministic pseudonyms; source video/channel identifiers are not published here. |
|
|
| ### `model_summary` |
| |
| Contains Overall, Natural, Expressive, and Pronunciation rows per model. Objective error |
| rates are corpus-weighted. Speaker similarity is the mean of successful trial scores. |
| Preference values use the same regularized Bradley–Terry method as the Arena. |
| |
| ## Human-preference limitations |
| |
| The judgments are from self-selected anonymous listening sessions, not a representative |
| panel of verified English speakers. Sessions are not people. Early ratings can move |
| substantially as votes accumulate; consult judgment counts and uncertainty fields. |
| Pair scheduling is adaptive, so the raw data is not an independently and identically |
| distributed sample. Use this snapshot for exploration and transparent research, not as |
| proof of a universal “best” model. |
| |
| ## Licensing |
| |
| The dataset-level license is **`other`** because generated outputs inherit different model |
| and provider terms. Every output and summary row includes `model_license`, |
| `model_repository`, and `model_revision`. **This dataset does not grant blanket commercial, |
| training, or redistribution rights for all audio.** Review the relevant model/provider |
| terms and the YodaLingua source dataset terms before reuse. |
|
|
| ## Provenance |
|
|
| - Arena snapshot: `arena-v3-api-complete-2026-09-16` |
| - Voting cohort: `5cc0b0e569fdad5debdb78b8c36d5a6b7e387a82e28e2acfb6d1b13e96e8f326` |
| - Private source revision: `727ef53ca1c5b37ac43e02beeb6a8332ec3dbda8` |
| - Benchmark code: <https://github.com/Thomcle/yodalingua-tts-benchmark> |
| - Live Arena: <https://huggingface.co/spaces/Thomcles/yodalingua-tts-arena> |
| - Methodology: <https://github.com/Thomcle/yodalingua-tts-benchmark/blob/main/docs/task-methodology-v3.md> |
|
|
| The public export is deterministic for a fixed catalog, source revision, vote database |
| snapshot, exporter version, and PyArrow version. File checksums and row counts are recorded |
| in `release.json`. |
|
|
| ## Citation |
|
|
| ```bibtex |
| @misc{yodalingua_tts_arena_english, |
| author = {YodaLingua contributors}, |
| title = {YodaLingua English TTS Arena: Model Outputs and Human Preferences}, |
| year = {2026}, |
| url = {https://huggingface.co/datasets/Thomcles/YodaLingua-TTS-Arena-English} |
| } |
| ``` |
|
|
