speak

Convert any text into speech audio. Supports two backends (Kokoro local, Noiz cloud), two modes (simple or timeline-accurate), and per-segment voice control.

Triggers

text to speech / speak / say / tts
voice clone / dubbing
epub to audio / srt to audio / convert to audio

Simple Mode — text to audio

# Kokoro (auto-detected when installed)
bash skills/speak/scripts/tts.sh speak -t "Hello world" -v af_sarah -o hello.wav
bash skills/speak/scripts/tts.sh speak -f article.txt -v zf_xiaoni --lang cmn -o out.mp3 --format mp3

# Noiz (auto-detected when NOIZ_API_KEY is set, or force with --backend noiz)
# If --voice-id is omitted, the script prints 5 available built-in voices and exits.
# Pick one from the output and re-run with --voice-id <id>.
bash skills/speak/scripts/tts.sh speak -f input.txt --voice-id voice_abc --auto-emotion --emo '{"Joy":0.5}' -o out.wav

# Noiz: optional --duration (float, seconds, range (0, 36]) for target audio length
bash skills/speak/scripts/tts.sh speak -t "Short line" --voice-id voice_abc --duration 3.5 -o out.wav

# Voice cloning (Noiz only — no voice-id needed, uses ref audio)
# Use your own reference audio: local file path or URL (only when using Noiz).
bash skills/speak/scripts/tts.sh speak -t "Hello" --ref-audio ./ref.wav -o clone.wav
bash skills/speak/scripts/tts.sh speak -t "Hello" --ref-audio https://example.com/my_voice.wav -o clone.wav

Timeline Mode — SRT to time-aligned audio

For precise per-segment timing (dubbing, subtitles, video narration).

Step 1: Get or create an SRT

If the user doesn't have one, generate from text:

bash skills/speak/scripts/tts.sh to-srt -i article.txt -o article.srt
bash skills/speak/scripts/tts.sh to-srt -i article.txt -o article.srt --cps 15 --gap 500

--cps = characters per second (default 4, good for Chinese; ~15 for English). The agent can also write SRT manually.

Step 2: Create a voice map

JSON file controlling default + per-segment voice settings. segments keys support single index "3" or range "5-8".

Kokoro voice map:

{
  "default": { "voice": "zf_xiaoni", "lang": "cmn" },
  "segments": {
    "1": { "voice": "zm_yunxi" },
    "5-8": { "voice": "af_sarah", "lang": "en-us", "speed": 0.9 }
  }
}

Noiz voice map (adds emo, reference_audio support). reference_audio can be a local path or a URL (user’s own audio; Noiz only):

{
  "default": { "voice_id": "voice_123", "target_lang": "zh" },
  "segments": {
    "1": { "voice_id": "voice_host", "emo": { "Joy": 0.6 } },
    "2-4": { "reference_audio": "./refs/guest.wav" }
  }
}

Dynamic Reference Audio Slicing: If you are translating or dubbing a video and want each sentence to automatically use the audio from the original video at the exact same timestamp as its reference audio, use the --ref-audio-track argument instead of setting reference_audio in the map:

bash skills/speak/scripts/tts.sh render --srt input.srt --voice-map vm.json --ref-audio-track original_video.mp4 -o output.wav

See examples/ for full samples.

Step 3: Render

bash skills/speak/scripts/tts.sh render --srt input.srt --voice-map vm.json -o output.wav
bash skills/speak/scripts/tts.sh render --srt input.srt --voice-map vm.json --backend noiz --auto-emotion -o output.wav

When to Choose Which

Need	Recommended
Just read text aloud, no fuss	Kokoro (default)
EPUB/PDF audiobook with chapters	Kokoro (native support)
Voice blending (`"v1:60,v2:40"`)	Kokoro
Voice cloning from reference audio	Noiz
Emotion control (`emo` param)	Noiz
Exact server-side duration per segment	Noiz

When the user needs emotion control + voice cloning + precise duration together, Noiz is the only backend that supports all three.

Requirements

ffmpeg in PATH (timeline mode)
Noiz: get your API key at developers.noiz.ai, then run bash skills/speak/scripts/tts.sh config --set-api-key YOUR_KEY
Kokoro: if already installed, pass --backend kokoro to use the local backend

For backend details and full argument reference, see reference.md.