voiceclap-emolia-flattened

SNAC-tokenized, flattened + augmented build of the English block of laion/voiceclap-data's emolia subset (shards 314-1033, 720 shards, CC-BY-4.0) -- ~9,750 hours, ~3.5M audio clips, real per-clip transcript + rich voice/emotion metadata (EmoNet-style 55-dim annotation, DNSMOS quality score, free-text emotion_caption, ~14 structured voice/tone/recording-context field groups).

Why this exists

Directly named by Huu (relayed via Discord exchange with spirit-from-germany, 2026-08-04) as the kind of scale needed for listen<->speak coherence: "50k hours is a start... better 200k or more. Emolia plus podcasts." At ~9,750 hours this is ~27x more audio than this project's entire emotional-roleplay-finetuning-dataset source, and (unlike that source, which is German-dominant) the shard range used here was verified English-only before building.

Tasks (6 per row, non-LLM -- field reuse + templates, no LLM augmentation)

• A TTS: 1-2 short attribute sentences (hash-picked from speaker_voice/style_performance/style_casual/style_authority) + [Language: English] + Say: "{text}" -> <speak>.
• B ASR: <listen>{audio}</listen> + question-pool -> {text} (real transcript).
• C1/C2/C3 voice/tone/recording description, each a different field group (C1=speaker_voice, C2=timbre_*+prosody_*, C3=recording_context+ physical_production) -> text.
• D imagine voice, text-only (no audio): {text} -> 1 attribute sentence.
• E dominant emotion: argmax over a curated 39-dim subset of the 55-dim emotion_annotation (excludes non-emotion axes like Age/Gender/ Background_Noise/Recording_Quality/bipolar vocal-quality scales), mapped through a fixed lookup table -> short emotion phrase.
• F TTS via the rich register: same shape as A, but voice-directed using the dense free-text emotion_caption instead of A's terse attribute sentences (Say: "{text}" still required -- emotion_caption alone describes voice quality, not the literal words to speak).

Tiering: dnsmos >= 3.5 -> chatml tier, else base (dataset-native substitute for the roleplay source's adherence_score, since emolia has no such field).

Format (task A shown, base tier)

USER: {1-2 attribute sentences} [Language: English] Say: "{text}"
ASSISTANT:
<think>
</think>
<speak>...snac tokens (7 tok/12.5Hz frame)...</speak>

Base

laion/voiceclap-data (CC-BY-4.0), emolia subset, English shards 314-1033 only. Audio SNAC-tokenized (hubertsiuzdak/snac_24khz, full 3-level 7 tok/frame speak-format, same offsets as laion_emotional_roleplay/dailytalk_multiturn).