从文字或图像生成3D模型,并与目录素材搭配使用。在Blender中检查形状、材质、大小和接地情况,记录生成条件、来源及费用,再将素材加入场景。
- 根据文字生成独特的3D道具
- 将概念图中的物体转为3D模型
- 用目录中的植被和岩石填充背景
在OpenMontage中使用Azure AI Speech,将多语言脚本生成为旁白。可选择声音、调整语速和音调,并保存为MP3或供后续混音编辑的WAV文件。
Generate neural narration audio using Azure AI Speech (REST text-to-speech). Use when synthesizing voiceovers or narration in OpenMontage. Optional cloud TTS provider — preferred when AZURE_SPEECH_KEY is configured; the local piper_tts remains the default offline path. Shares one Speech resource with azure_stt.
此技能在OpenMontage中使用Azure AI Speech,将脚本文字生成为旁白音频。通过azure_tts选择声音,调整语速、音调,以及该声音支持的朗读风格。音频可以保存为MP3;如果之后需要混音和编辑,也可以选择WAV。
适合为讲解视频添加旁白,或朗读多语言脚本。音频按场景分段生成,因此修改脚本的一部分后,可以只重新生成对应片段。需要调整朗读速度或整体表达风格时,也可使用这一流程。
需要互联网连接和Azure AI Speech资源。须设置AZURE_SPEECH_KEY,以及区域或专用端点。云服务使用会产生费用。不同声音支持的朗读风格有所不同,因此应先试听,再生成完整脚本。离线时的默认路径为piper_tts。
本介绍由 AI(OpenAI Codex)根据公开的 SKILL.md 撰写。准确的规格请查看下方原文。
AI 仅根据 SKILL.md 的内容,从 4 个方面进行了评估。星标数和热度不计入评估。
总分按每项 A=25 分、B=15 分、C=5 分相加。 由 AI(OpenAI Codex)于 2026年10月23日 评估。仅供参考,安装前请同时查看原文。
安装前可以查看交给 AI 代理的指令内容。
Generate narration with Azure neural TTS — high-quality multilingual voices,
SSML prosody control, and express-as styles, served synchronously by the REST
/cognitiveservices/v1 endpoint (no token exchange, Blob storage, or job
polling). In OpenMontage this is exposed through the azure_tts tool
(capability=tts, provider=azure). It is an optional cloud TTS provider —
when AZURE_SPEECH_KEY is configured, prefer it for high-quality cloud
narration. The local piper_tts remains the default offline path and the
fallback when Azure is unavailable; elevenlabs_tts remains the choice for
voice cloning.
Docs: REST text to speech · Voice gallery
Same Speech resource as azure_stt — one key/region unlocks both directions
(STT and TTS). Create a Speech resource in the
Azure portal; copy the key and region from its
Keys and Endpoint page.
export AZURE_SPEECH_KEY=your_speech_resource_key
export AZURE_SPEECH_REGION=eastus # your resource's region
# export AZURE_TTS_ENDPOINT=https://... # optional: full custom TTS host
# (the TTS host is https://<region>.tts.speech.microsoft.com — a different
# subdomain than the STT endpoint, hence the separate override var)
azure_tts reports AVAILABLE once AZURE_SPEECH_KEY plus either
AZURE_SPEECH_REGION or AZURE_TTS_ENDPOINT are set.
Route through tts_selector as usual (it auto-discovers azure_tts), or call
the provider tool directly when the user has approved Azure:
from tools.tool_registry import registry
registry.discover()
tts = registry._tools["azure_tts"]
result = tts.execute({
"text": "Every design decision in this dashboard has a reason.",
"voice": "andrew", # alias or full Azure short name
"rate": "-4%", # slightly slower for narration
# "style": "narration-professional", # for voices that support styles
"output_path": "projects/my-video/assets/audio/seg_001.mp3",
"output_format": "mp3", # or "wav" (48kHz PCM) for mixing
})
If azure_tts is unavailable (no key) or errors, fall back per its declared
chain: elevenlabs_tts → openai_tts → piper_tts.
Curated shortlist (aliases accepted by the voice param):
| Alias | Voice | Character |
|---|---|---|
andrew | en-US-AndrewMultilingualNeural | warm, confident, conversational — the default; founder/explainer register |
brandon | en-US-BrandonMultilingualNeural | deeper, measured |
ava | en-US-AvaMultilingualNeural | confident, bright female |
guy | en-US-GuyNeural | authoritative |
jenny | en-US-JennyNeural | friendly, clear |
Any valid Azure voice short name may be passed verbatim (e.g.
de-DE-KatjaNeural); the Multilingual voices handle non-English text well —
set locale to match the text's language for correct SSML.
rate / pitch — SSML prosody. Narration usually reads best slightly
slowed ("-4%" to "-8%"); leave pitch at "0%" unless correcting a voice.style — express-as style for voices that support it
(narration-professional, calm, newscast). Unsupported styles are
silently ignored by Azure, so listen to a sample before batch runs.output_format — mp3 (48kHz/192kbit) for delivery, wav (48kHz PCM)
when the segment feeds audio_mixer for further processing.Azure neural TTS Standard tier bills roughly $16 per 1M characters (~$0.016
per 1k chars; a 150-word narration segment ≈ $0.015). The tool reports
per-call cost_usd for the cost tracker. See
Azure AI Speech pricing for current rates.
execute call = one narration segment. Generate per script section (the
asset stage convention) rather than one giant paragraph — smaller segments
align cleanly to scene timings and are cheap to regenerate.rate/pitch/style params.还没有评价。欢迎分享你的使用感受。
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从文字或图像生成3D模型,并与目录素材搭配使用。在Blender中检查形状、材质、大小和接地情况,记录生成条件、来源及费用,再将素材加入场景。
使用ACE-Step 1.5生成视频背景音乐和带歌词的歌曲,可指定曲风、时长、速度与调性,也支持改编参考音频,以及从混合音频中分离人声或乐器。
使用ElevenLabs创建语音对话助手或角色,配置声音、应答规则、语言模型及外部工具,支持嵌入网站,并通过Twilio集成设置电话外呼。
根据文字或参考图像生成AI视频,并按用途、可用服务和预算选择模型。可制作社交平台竖屏短片、让商品照片动起来,也可通过对话编辑已有片段。
根据文字描述或参考图片生成AI视频,并按用途和费用选择生成服务。支持设置画面比例、查看生成进度,以及通过Gemini Omni对话修改现有视频。
通过Atlas Cloud使用多种模型生成和编辑图像与视频,只需一个API密钥,即可保存生成素材,以及所用模型、提交设置和预估费用等记录。