Publish TTS Voice Direction benchmark dataset

README.md

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+---
+pretty_name: TTS Voice Direction Benchmark
+language:
+  - en
+task_categories:
+  - text-to-speech
+tags:
+  - text-to-speech
+  - voice-direction
+  - voice-cloning
+  - benchmark
+---
+
+# TTS Voice Direction Benchmark
+
+🏆 [Leaderboard](https://breezeblue.ai/benchmarks/tts-voice-direction) | 🛠️ [Evaluation Suite](https://github.com/breezeblue-ai/tts-voice-direction-benchmark)
+
+TTS Voice Direction is a benchmark of **700 reference-conditioned speech
+generation tasks**. It evaluates whether a text-to-speech model can preserve a
+reference speaker while following a natural-language direction that controls
+how a new transcript is performed.
+
+The benchmark emphasizes practical voice acting beyond basic emotion control.
+It covers accent, acoustic delivery, vocal events, emotion, physiological
+state, communicative intent, role performance, multi-attribute composition,
+and temporal variation.
+
+## Dataset At A Glance
+
+- **700** English voice-direction tasks
+- **25** synthetic reference voices
+- **9** fine-grained direction categories
+- **3** macro categories
+- One reference audio, reference transcript, direction, and target transcript
+  per task
+- Four-digit output IDs from `0001` through `0700`
+
+## Taxonomy
+
+| Macro category | Fine-grained category | Cases |
+|---|---|---:|
+| Foundational Speech Control | Accent | 50 |
+| Foundational Speech Control | Acoustic Attributes | 100 |
+| Foundational Speech Control | Vocal Events | 50 |
+| Situational Voice Acting | Emotion | 150 |
+| Situational Voice Acting | Physiological State | 50 |
+| Situational Voice Acting | Communicative Intent | 50 |
+| Situational Voice Acting | Role | 100 |
+| Complex | Composition | 100 |
+| Complex | Variation | 50 |
+
+Foundational cases target directly controllable speech properties. Situational
+cases describe a high-level state, purpose, or role and require the model to
+realize an appropriate performance. Complex cases combine multiple controls or
+request a perceptible change over time.
+
+## Reference Voices
+
+All 25 reference voices are synthetic and sourced from the BreezeBlue Voice
+Library. Reference files are stored in `reference_audio/` and named
+`voice-01.wav` through `voice-25.wav`.
+
+The benchmark rotates directions across the reference set so that each model is
+tested on both instruction following and speaker preservation. Reference voice
+identity is evaluated separately from direction following.
+
+## Data Format
+
+Each line in `voice_direction_dataset.jsonl` is one task:
+
+```json
+{
+  "description_id": "0001",
+  "language": "en",
+  "macro_category": "foundational_speech_control",
+  "category": "accent",
+  "voice_id": "voice-15",
+  "ref_audio_path": "reference_audio/voice-15.wav",
+  "ref_audio_text": "Reference transcript...",
+  "description": "Use a moderate, consistent General American English accent throughout the line.",
+  "transcript": "Target transcript..."
+}
+```
+
+| Field | Description |
+|---|---|
+| `description_id` | Stable four-digit task ID |
+| `language` | Target transcript language; currently `en` |
+| `macro_category` | One of the three aggregation groups |
+| `category` | One of the nine fine-grained direction categories |
+| `voice_id` | Stable reference-voice identifier |
+| `ref_audio_path` | Reference audio path relative to the dataset file |
+| `ref_audio_text` | Transcript of the reference audio |
+| `description` | Natural-language voice-direction instruction |
+| `transcript` | Text to synthesize |
+
+## Running The Benchmark
+
+For every record:
+
+1. Condition the model on `ref_audio_path` and, when required by the model,
+   `ref_audio_text`.
+2. Use `description` as the voice-direction instruction.
+3. Synthesize the exact `transcript`.
+4. Save one audio file named after `description_id`, for example `0001.wav`.
+
+Do not use `macro_category` or `category` as additional model inputs. They are
+provided only for evaluation and analysis.
+
+## Evaluation
+
+The benchmark reports two complementary metrics:
+
+- **Voice Direction Score (VDS)** is a holistic 1-5 judge score for audible
+  fulfillment of the requested direction, requested degree or timing, semantic
+  preservation, and coherent execution.
+- **Speaker Similarity (SIM)** is cosine similarity between WavLM-Large ECAPA
+  embeddings of the generated and reference audio.
+
+Both metrics are aggregated in the same hierarchy: reference voices are
+macro-averaged within each fine-grained category, fine-grained categories are
+equally averaged within each macro category, and the three macro-category
+scores are equally averaged into the overall score.
+
+The self-contained judge prompts, evaluation scripts, speaker-embedding code,
+and metric documentation are available in the
+[evaluation suite](https://github.com/breezeblue-ai/tts-voice-direction-benchmark).