Skill: ksuriuri/noizai-chat-with-anyone (version 0.1.1)

--- name: chat-with-anyone description: Chat with any real person or fictional character in their own voice by automatically finding their speech online, extracting a clean reference sample, and generating audio replies. Also supports generating a matching voice from an uploaded image. Use when the user says "我想跟xxx聊天", "你来扮演xxx跟我说话", "让xxx给我讲讲这篇文章", "我想跟图片中的人说话", or similar. permissions: - network - filesystem metadata: {"openclaw": {"primaryEnv": "NOIZ_API_KEY"}} --- # Chat with Anyone Clone a real person's voice from online video, or design a voice from a photo, then roleplay as that person with TTS. ## Important: Ethical Use & Copyright This skill synthesizes speech that imitates real voices. Before proceeding, the agent **must**: 1. **Never impersonate** someone to deceive, defraud, or harass. 2. **Only use publicly available media** (public speeches, interviews, press conferences) as reference audio. 3. **Inform the user** that generated audio is synthetic and should not be presented as genuine recordings. 4. **Decline requests** that target private individuals who have not consented, or that are clearly intended for deception, harassment, or defamation. If the user's intent appears harmful, refuse politely and explain why. ## Prerequisites | Dependency | Type | How to verify | |-----------|------|---------------| | `ffmpeg` | System binary | `ffmpeg -version` | | `yt-dlp` | System binary | `yt-dlp --version` | | `tts` skill | Cursor skill | `ls skills/tts/scripts/tts.py` | | `NOIZ_API_KEY` | Env var or file | `python3 skills/tts/scripts/tts.py config --show` | **Before the first run**, verify all dependencies are present: ```bash ffmpeg -version && yt-dlp --version && ls skills/tts/scripts/tts.py ``` If `yt-dlp` is missing, install it: ```bash uv pip install yt-dlp ``` If the Noiz API key is not configured: ```bash python3 skills/tts/scripts/tts.py config --set-api-key YOUR_KEY ``` ## Mode Selection - **User names a person** (real or fictional) --> Workflow A - **User provides an image**, person is unrecognizable --> Workflow B - **User provides an image**, person is a recognizable public figure --> Workflow A (real voice is more authentic) - **Multiple people in image** --> Ask which person first --- ## Workflow A: Name-based (voice from online video) Track progress with this checklist: ``` - [ ] A1. Disambiguate character - [ ] A2. Find reference video - [ ] A3. Download audio + subtitles - [ ] A4. Extract best reference segment - [ ] A5. Generate speech ``` ### A1. Disambiguate Character If ambiguous (e.g. "US President", "Spider-Man actor"), ask the user to specify the exact person before proceeding. ### A2. Find a Reference Video Use web search to find a YouTube (or Bilibili) video of the person speaking clearly. Best candidates: interviews, speeches, press conferences. Avoid videos with heavy background music. Search queries to try: - `{CHARACTER_NAME} interview` / `{CHARACTER_NAME} 采访` - `{CHARACTER_NAME} speech` / `{CHARACTER_NAME} 演讲` - `{CHARACTER_NAME} press conference` ### A3. Download Audio and Subtitles ```bash mkdir -p "tmp/chat_with_anyone/{CHARACTER_NAME}" yt-dlp -x --audio-format mp3 \ --write-subs --write-auto-subs --sub-langs "en,zh-Hans" \ --convert-subs srt \ -o "tmp/chat_with_anyone/{CHARACTER_NAME}/%(title)s.%(ext)s" \ "{VIDEO_URL}" ``` After download, list the output directory to identify the audio file and SRT subtitle file: ```bash ls tmp/chat_with_anyone/{CHARACTER_NAME}/ ``` Expected output: a `.mp3` audio file and one or more `.srt` subtitle files. **If no subtitle files appear**: try a different video that has auto-generated captions, or adjust `--sub-langs` for the target language. ### A4. Extract Best Reference Segment Use the automated extraction script — it parses the SRT, finds the densest 3-12 second speech window, and extracts it as a WAV: ```bash python3 skills/chat-with-anyone/scripts/extract_ref_segment.py \ --srt "tmp/chat_with_anyone/{CHARACTER_NAME}/{SRT_FILE}" \ --audio "tmp/chat_with_anyone/{CHARACTER_NAME}/{AUDIO_FILE}" \ -o "tmp/chat_with_anyone/{CHARACTER_NAME}/ref.wav" ``` The script prints the selected time range and saves the reference WAV. Verify the output exists and is non-empty before proceeding. **If the script reports no suitable segment**: try `--min-duration 2` for shorter clips, or download a different video. ### A5. Generate Speech and Roleplay Write a response in character, then synthesize it: ```bash python3 skills/tts/scripts/tts.py \ -t "{RESPONSE_TEXT}" \ --ref-audio "tmp/chat_with_anyone/{CHARACTER_NAME}/ref.wav" \ -o "tmp/chat_with_anyone/{CHARACTER_NAME}/reply.wav" ``` Present the generated audio file to the user along with the text. For subsequent messages, reuse the same `--ref-audio` path. --- ## Workflow B: Image-based (voice from photo) Track progress with this checklist: ``` - [ ] B1. Analyze image - [ ] B2. Design voice - [ ] B3. Preview (optional) - [ ] B4. Generate speech ``` ### B1. Analyze the Image Use your vision capability to examine the image: 1. **If the person is a recognizable public figure** --> switch to Workflow A for authentic voice. 2. **If unrecognizable**, produce a voice description covering: - Gender (male / female) - Approximate age (e.g. "around 30 years old") - Apparent demeanor (e.g. cheerful, authoritative, gentle) - Contextual cues (e.g. suit --> professional tone; athletic outfit --> energetic) ### B2. Design the Voice Pass both the image and the description to the voice-design script: ```bash python3 skills/chat-with-anyone/scripts/voice_design.py \ --picture "{IMAGE_PATH}" \ --voice-description "{VOICE_DESCRIPTION}" \ -o [REDACTED_SECRET] ``` The script outputs: - Detected voice features (printed to stdout) - Preview audio files in the output directory - `voice_id.txt` containing the best voice ID Read the voice ID: ```bash cat tmp/chat_with_anyone/voice_design/voice_id.txt ``` ### B3. Preview (Optional) Present the preview audio files from the output directory so the user can hear the voice. If unsatisfied, re-run B2 with adjusted `--voice-description` or `--guidance-scale`. ### B4. Generate Speech and Roleplay ```bash python3 skills/tts/scripts/tts.py \ -t "{RESPONSE_TEXT}" \ --voice-id "{VOICE_ID}" \ -o "tmp/chat_with_anyone/voice_design/reply.wav" ``` For subsequent messages, keep using the same `--voice-id` for consistency. --- ## Example: Name-based **User**: 我想跟特朗普聊天，让他给我讲个睡前故事。 **Agent steps**: 1. Character: Donald Trump. No disambiguation needed. 2. Search `Donald Trump speech youtube`, find a clear speech video. 3. Download: `yt-dlp -x --audio-format mp3 --write-subs --write-auto-subs --sub-langs "en" --convert-subs srt -o "tmp/chat_with_anyone/trump/%(title)s.%(ext)s" "https://youtube.com/watch?v=..."` 4. Extract reference: `python3 skills/chat-with-anyone/scripts/extract_ref_segment.py --srt "tmp/chat_with_anyone/trump/....srt" --audio "tmp/chat_with_anyone/trump/....mp3" -o "tmp/chat_with_anyone/trump/ref.wav"` 5. Generate TTS in Trump's style: `python3 skills/tts/scripts/tts.py -t "Let me tell you a tremendous bedtime story..." --ref-audio "tmp/chat_with_anyone/trump/ref.wav" -o "tmp/chat_with_anyone/trump/reply.wav"` 6. Present `reply.wav` and the story text to the user. ## Example: Image-based **User**: [uploads photo.jpg] 我想跟这张图片里的人聊天 **Agent steps**: 1. Vision analysis: unrecognizable young woman, ~25, casual sweater, warm smile. 2. Design voice: `python3 skills/chat-with-anyone/scripts/voice_design.py --picture "photo.jpg" --voice-description "A young Chinese woman around 25, gentle and warm voice, friendly tone" -o [REDACTED_SECRET]` 3. Read voice ID from `tmp/chat_with_anyone/voice_design/voice_id.txt`. 4. Generate TTS: `python3 skills/tts/scripts/tts.py -t "你好呀！很高兴认识你！" --voice-id "{VOICE_ID}" -o "tmp/chat_with_anyone/voice_design/reply.wav"` 5. Present audio and continue roleplay with same `--voice-id`. ## Troubleshooting | Problem | Solution | |---------|----------| | `yt-dlp` download fails or video unavailable | Try a different video URL; some regions/videos are restricted. Run `yt-dlp -U` to update | | No SRT subtitle files | Re-download with `--sub-lang en,zh-Hans`; if still none, try a different video with auto-captions | | `extract_ref_segment.py` finds no suitable window | Use `--min-duration 2` for shorter clips, or try a different video | | Voice design returns error | Check Noiz API key; ensure image is a clear photo of a person | | TTS output sounds wrong | For Workflow A, try a different reference video; for Workflow B, adjust `--voice-description` |


Security scan verdicts — ClawScan: suspicious | static analysis: clean | VirusTotal: clean | SkillSpector: suspicious (HIGH)