Stepfun TTS
Generate Chinese / Japanese speech with StepFun's Contextual TTS — default `stepaudio-2.5-tts` (blind-judged better on neutral/emotive preset voices), `stepaudio-3-tts` for whisper & inline-prosody cases (where it won the same blind test). Replaces step-tts-2's `voice_label` with natural-language `instruction` (200 chars on 2.5, 500 on v3) plus inline `()` parentheses for句内 prosody. Use when the user wants emotional / prosody control over voice synthesis (whisper, pause, stress, mood pivot mid-sentence), batch-generates game / app voice lines, migrates from `step-tts-2` or `stepaudio-2.5-tts` (the `voice_label → instruction` breaking change), or needs cloned voices (复刻音色:克隆合成禁用 v3——克隆丢失,走 stepaudio-2.5-tts/step-tts-2). Triggers on 阶跃 TTS, StepAudio 合成, stepaudio-3-tts, stepaudio-2.5-tts, 语音合成, 配音, 文本转语音, TTS 升级, 迁移 step-tts-2. For transcription with the sibling stepaudio-3-asr-max model, use the stepfun-asr skill instead.
- Skill ID
- daymade/claude-code-skills/stepfun-tts
- Publisher
- daymade
- Repository
- claude-code-skills
- Installs
- 0
- Files
- 6
- Synced
- Sep 23, 2026
Open any RiverX project, open the Skills panel in the chat, and search for this identifier. The files are fetched from the source repository at install time.
daymade/claude-code-skills/stepfun-ttsInstalls these files- SKILL.md
- references/api_reference.md
- references/known_issues.md
- references/migration_from_v2.md
- scripts/ab_compare.sh
- scripts/tts_generate.py
What this skill tells the agent
StepFun Contextual TTS (default stepaudio-2.5-tts)
Generate Chinese / Japanese speech with StepFun's Contextual TTS — emotion and prosody go through natural-language description, not fixed labels. Default model is `stepaudio-2.5-tts` (what the bundled script uses): in a 2026-09-16 blind A/B on our own cases, 2.5 won the neutral / jiao / lively-girl pairs 3:2. Pick `stepaudio-3-tts` when the line is whisper or heavy inline-`()` prosody — v3 won exactly those two pairs; v3 also raises the instruction cap to 500 chars (2.5 is 200). ⚠️ Never synthesize cloned voices with v3 — v3 speech 接受复刻音色 ID 不报错但静默回退默认女声——根因 = 阶跃复刻链路整体停在 2.5 家族(复刻创建 API 只收 2.5/step-tts-2/step-tts-mini,v3 不在列;v3 合成侧复刻未发布)。两代创建的克隆在 v3 上全丢:step-tts-2 克隆 SIM 0.272、2.5 创建的新克隆 SIM 0.195(锚 0.773),2.5 同 ID 0.743/0.678。
Companion: for transcription withstepaudio-3-asr-max(the sibling model), use thestepfun-asrskill — they share an API key but live on different endpoints with different body shapes.
Why this skill exists — two non-obvious pitfalls that cost hours if you don't know them:
stepaudio-3-ttsrejectsvoice_label(the step-tts-2 way) — verified on v3 2026-09-16: HTTP 400voice_label is not supported for this model. Emotion/prosody goes throughinstruction(natural-language description, ≤500 chars on v3 — 200 was the 2.5 limit) and inline()parentheses inside the text itself.- Censorship behavior is model-version-specific — the 2.5-era trigger list (死 / 消失 / sensitive political terms →
censorship_block) did not fire on v3 in a 2026-09-16 single-sample probe; treat censorship as present but re-verify per trigger before building rewrite maps. The 2.5-era options are inreferences/migration_from_v2.md.
Config and auth
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>"}
EOFIf 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).
Common tasks — decision tree
| 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 / stepaudio-2.5-tts | see references/migration_from_v2.md | voice_label.emotion → instruction rewrite + 2.5-era censorship list |
Starting points
- Synthesize a single line: Run
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. - From code: this script is the endpoint's wrapper in
llm-registry—llmreg.wrapper_for("stepfun-tts").tts_generate.synthesize(api_key=…, text=…, model=…, extra={…}).extrais merged into the request body as-is; with{"timestamp": True, "return_url": True}the server answers a JSON envelope ({"data": {"url", "subtitles"}}) that comes back underjsoninstead ofaudio_bytes(verified 2026-09-19). Parameters are not billed — send what you need. Direct/v1/audio/speechcalls elsewhere are blocked by thellm-entry-guardhook. - A full migration from
step-tts-2→ Contextual TTS: readreferences/migration_from_v2.mdend-to-end before touching code. It has theINSTRUCTION_MAP, the SKIP_CENSORED list pattern, and the output-directory-strategy for non-destructive A/B (written for 2.5; the migration mechanics are identical on v3).
Contextual TTS — beyond emotion labels
The headline feature of stepaudio-3-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. ≤500 chars on v3 (2.5 was 200; a 300-char instruction verified accepted on v3 2026-09-16). 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 (verified 2026-04-23 on 2.5; all five re-verified on v3 2026-09-16, including these instruction and inline-prosody cases):
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 respected
What `stepaudio-3-tts` will NOT accept — voice_label parameter. Error on v3: voice_label is not supported for this model (2.5 said ...for v2 models). This is the #1 migration gotcha from step-tts-2.
Common error patterns (real errors, real fixes)
| Error response | Actual cause | Fix |
|---|---|---|
"voice_label is not supported for this model" (v3) / "...for v2 models" (2.5) | Sent voice_label to a Contextual TTS model | 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 (2.5-era: 死 / 消失 / etc.; v3 triggers unverified) | 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.
When to read references
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 Contextual TTS. Has the emotion→instruction rewrite table, the A/B directory strategy, decision checkpoints, and the 2026-04 speed/quality trade-off data (written against 2.5). Read before any migration work.references/known_issues.md— censorship patterns, TTS duration inflation, v2-family parameter naming gotcha, 1000-char hard cap. 2.5-era verification; re-verify on v3 before relying on a specific entry. Read when debugging anomalous output or evaluating whether to adopt.
Design invariants (don't break these)
- Non-destructive A/B output — when regenerating a corpus with a new model, write to a parallel directory (
voice/zh_v3/), never overwrite the production corpus. The migration playbook shows why. - Per-line censorship handling — if 2/29 lines get
censorship_block, don't fail the batch. Log the skipped IDs, continue. Mixed-model fallback (step-tts-2 for the skipped 2) is normal. - Don't duplicate voice_label logic in new code — any new TTS code targeting stepaudio-3-tts should only use
instruction+ inline(). Do not write a branch that conditionally emitsvoice_label.
v3-specific facts (verified 2026-09-16)
More from daymade
Use this skill in a project
Open any RiverX project, search the Skills panel for daymade/claude-code-skills/stepfun-tts, and install it in one click.
