From daymade-audio
Generates Chinese/Japanese speech via StepFun's stepaudio-2.5-tts with natural-language emotion/prosody control. Handles v2 migration, censorship blocks, and batch voice line generation.
How this skill is triggered — by the user, by Claude, or both
Slash command
/daymade-audio:stepfun-ttsThe summary Claude sees in its skill listing — used to decide when to auto-load this skill
Generate Chinese / Japanese speech with `stepaudio-2.5-tts` (released 2026-04, verified 2026-04-23). Contextual TTS — emotion and prosody go through natural-language description, not fixed labels.
Generate Chinese / Japanese speech with stepaudio-2.5-tts (released 2026-04, verified 2026-04-23). Contextual TTS — emotion and prosody go through natural-language description, not fixed labels.
Companion: for transcription with
stepaudio-2.5-asr(the sibling model), use thestepfun-asrskill — they share an API key but live on different endpoints with different body shapes.
Why this skill exists — StepAudio 2.5 has two non-obvious pitfalls that cost hours if you don't know them:
stepaudio-2.5-tts rejects voice_label (the step-tts-2 way). Emotion/prosody now goes through instruction (natural-language description, ≤200 chars) and inline () parentheses inside the text itself.censorship_block. Your rewrite options are in references/migration_from_v2.md.API key lives in $STEPFUN_API_KEY (preferred) or ${CLAUDE_PLUGIN_DATA}/config.json (fallback for cross-session persistence). All bundled scripts try env first, then config.
First-time setup (one-liner):
mkdir -p "${CLAUDE_PLUGIN_DATA}" && cat > "${CLAUDE_PLUGIN_DATA}/config.json" <<EOF
{"api_key": "<paste key here>"}
EOF
If the user hasn't set a key, ask them to paste it (don't guess / don't use a placeholder). StepFun API keys are available at https://platform.stepfun.com/ → API Keys. Use a Normal key, not a Plan key (Plan keys are restricted to text models and silently fail on audio endpoints).
| User wants... | Script | Key detail |
|---|---|---|
| Synthesize 1–500 char Chinese with emotion | scripts/tts_generate.py | Use instruction for mood, () for inline prosody |
| Synthesize long text (500–1000 char) | scripts/tts_generate.py | 1000 char is the hard cap; split at semantic boundaries above that |
| Batch-generate game/app voice lines | scripts/tts_generate.py --batch <jsonl> | Handle censorship_block fallback individually |
| A/B compare two TTS models | scripts/ab_compare.sh | Compares duration/size across two directories |
Migrate from step-tts-2 | see references/migration_from_v2.md | voice_label.emotion → instruction rewrite + censorship list |
python3 scripts/tts_generate.py --text "你好" --out /tmp/hello.mp3 --instruction "温暖的希望感". For fine-grained control read the "Contextual TTS" section below.step-tts-2 → stepaudio-2.5-tts: read references/migration_from_v2.md end-to-end before touching code. It has the INSTRUCTION_MAP, the SKIP_CENSORED list pattern, and the output-directory-strategy for non-destructive A/B.The headline feature of stepaudio-2.5-tts is that you stop mapping emotions to fixed tags and start describing what you want in natural language. Two layers:
Global context (instruction parameter) — sets the overall tone for the entire utterance. ≤200 chars. Think of it like giving stage direction to a voice actor.
instruction: "克制的悲伤,语气低沉柔弱,像快要消失一样"
Inline context (() parentheses inside input) —句内 directives. Parenthesised content is consumed as directions and is NOT read aloud. Use for precise control of pauses, breath, emphasis, or mid-sentence emotion shifts.
input: "(试探着问)你好吗?(开心地)太好了!(突然沉下来)不过...我快要消失了。"
Examples that worked in practice (from 2026-04-23 verification):
instruction: "活泼俏皮,像是在撒娇,带点嘴硬" — visibly speeds up delivery vs neutralinstruction: "耳语声,气声很重,几乎听不清" — produces audible whisper/breathinput: "你好(停顿一下)我是蕾格(轻声)今天(加重)的天气真不错。" — inline directives all respectedWhat stepaudio-2.5-tts will NOT accept — voice_label parameter. Error: voice_label is not supported for v2 models. This is the #1 migration gotcha from step-tts-2.
| Error response | Actual cause | Fix |
|---|---|---|
"voice_label is not supported for v2 models" | Sent voice_label to stepaudio-2.5-tts | Remove voice_label; put the same intent into instruction as natural language |
"The content you provided or machine outputted is blocked." type: censorship_block | Sensitive word (死 / 消失 / etc.) | Rewrite the phrase OR fall back to step-tts-2 for that specific line (mixed-model is fine) |
| Silent audio truncation (input > 1000 chars) | Hard cap exceeded | Split at semantic boundaries; don't truncate mid-sentence |
More in references/known_issues.md.
references/api_reference.md — exact request/response JSON for /v1/audio/speech, all fields, error responses. Read when writing raw HTTP calls instead of using the bundled scripts.references/migration_from_v2.md — complete playbook for moving a step-tts-2 project to stepaudio-2.5-tts. Has the emotion→instruction rewrite table, the A/B directory strategy, decision checkpoints, and the 2026-04 speed/quality trade-off data (stepaudio-2.5-tts is ~20% slower than step-tts-2; audible prosody improvement). Read before any migration work.references/known_issues.md — censorship patterns, TTS duration inflation, v2-family parameter naming gotcha, 1000-char hard cap. Read when debugging anomalous output or evaluating whether to adopt.voice/zh_v25/), never overwrite the production corpus. The migration playbook shows why.censorship_block, don't fail the batch. Log the skipped IDs, continue. Mixed-model fallback (step-tts-2 for the skipped 2) is normal.instruction + inline (). Do not write a branch that conditionally emits voice_label.stepaudio-2.5-tts contextual synthesis: ~5.8 元 / 万字符Re-verify at https://platform.stepfun.com/docs/zh/guides/pricing/details before quoting to stakeholders.
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