| name | mkt-elevenlabs-tts-to-mp3 |
| description | Convert Vietnamese/English script text to MP3 voiceover using ElevenLabs TTS API. Calls POST /v1/text-to-speech/{voice_id}, streams audio bytes, writes MP3 directly. Locked to Hoang's brand voice ID by default. USE WHEN user says 'tạo mp3 elevenlabs', 'elevenlabs tts', 'eleven labs voice', 'text to speech elevenlabs', 'tạo voiceover elevenlabs', 'đọc text bằng elevenlabs', 'tts elevenlabs to mp3', 'eleven labs script to mp3', 'voiceover bằng elevenlabs', 'giọng elevenlabs'. |
ElevenLabs TTS to MP3
Convert script text to MP3 voiceover via ElevenLabs Text-to-Speech API.
Defaults
- Voice ID:
K7ewtjKRNtwwt3lKQ6M0 (Hoang's brand voice — locked) — overridable via ELEVENLABS_VOICE_ID env or --voice_id
- Model:
eleven_v3 (most expressive, supports audio tags like [excited], [whisper], [laugh]; best for storytelling content) — overridable via --model_id. Alternatives: eleven_multilingual_v2 (high quality, slower), eleven_turbo_v2_5 (fast, slightly flat), eleven_flash_v2_5 (fastest)
- Output format:
mp3_44100_128 (44.1 kHz / 128 kbps) — overridable via --output_format
- Voice settings:
stability=0.5, similarity_boost=0.75, style=0, use_speaker_boost=true (ElevenLabs defaults)
- Pronunciation map: auto-loaded from
assets/vn-pronunciation-map.json — disable with --no-pronounce-map, or point at a different file with --pronounce-map path.json
- Char limit: 5000 per request (ElevenLabs hard limit). Text > 5000 chars → script exits with error and asks user to split manually.
Quick Usage
From file
uv run .claude/skills/mkt-elevenlabs-tts-to-mp3/scripts/text_to_mp3.py \
--file path/to/script.txt \
-o workspace/content/YYYY-MM-DD/voiceover.mp3
From inline text
uv run .claude/skills/mkt-elevenlabs-tts-to-mp3/scripts/text_to_mp3.py \
"Xin chào các bạn, hôm nay mình chia sẻ về AI Agent" \
-o workspace/assets/elevenlabs/sample.mp3
Custom voice / model
uv run .claude/skills/mkt-elevenlabs-tts-to-mp3/scripts/text_to_mp3.py \
--file script.txt \
--voice_id K7ewtjKRNtwwt3lKQ6M0 \
--model_id eleven_turbo_v2_5 \
-o output.mp3
Tweak voice expressiveness
uv run .claude/skills/mkt-elevenlabs-tts-to-mp3/scripts/text_to_mp3.py \
--file script.txt \
--stability 0.4 \
--similarity_boost 0.8 \
--style 0.2 \
-o output.mp3
Voice settings — when to tweak
| Setting | Range | Effect |
|---|
stability | 0.0–1.0 | Higher = more monotone/predictable; lower = more emotional/variable. 0.5 is the sweet spot for narration. Drop to 0.3–0.4 for casual hooks; raise to 0.7+ for formal explainers. |
similarity_boost | 0.0–1.0 | How closely to clone the reference voice. 0.75 default. Raise toward 0.9 if voice sounds "off" from the original. |
style | 0.0–1.0 | Style exaggeration. 0 default. Adds latency when > 0. Useful (0.1–0.3) for expressive content. |
use_speaker_boost | bool | Sharpens speaker similarity. Keep true for brand voice consistency. |
Pronunciation Map (pre-TTS substitution)
The skill auto-loads a whole-word case-insensitive substitution map from assets/vn-pronunciation-map.json and applies it before sending text to the API. Two valid use cases:
Use case 1 — English-word fix. ElevenLabs multilingual models try to read the whole text in the dominant language. In a Vietnamese script, English words like doc, chat, git get pronounced as VN syllables. Map them to VN-phonetic spelling: "doc" -> "đóc" makes the model say close to /dɒk/.
Use case 2 — Vietnamese proper noun with missing diacritics. Source scripts often type place names without diacritics (Hanoi, Saigon, Da Nang). The TTS reads them flat and wrong. Map them to the proper VN spelling so the model reads them as the correct Vietnamese word: "Hanoi" -> "Hà Nội". Default map ships with the common VN cities (Hà Nội, Sài Gòn, Việt Nam, Đà Nẵng, Hải Phòng, Phú Quốc, Hạ Long, Cần Thơ, Vũng Tàu).
Default mapping:
{
"doc": "đóc", "chat": "chát", "git": "gít",
"Hanoi": "Hà Nội", "Saigon": "Sài Gòn", "Vietnam": "Việt Nam",
"Da Nang": "Đà Nẵng", "Hai Phong": "Hải Phòng", "Phu Quoc": "Phú Quốc",
"Ha Long": "Hạ Long", "Can Tho": "Cần Thơ", "Vung Tau": "Vũng Tàu"
}
How it works: each key is matched case-insensitively with \b...\b boundaries, then replaced. The substitution happens in-memory before the API call — your source script stays clean. Multi-word keys like "Da Nang" work because \b boundaries surround the whole phrase.
Curating the dictionary — listen first, add second:
- Run the skill on a short test script containing the candidate word
- If the model already reads it correctly, don't add it (overfitting will break things)
- Watch out for collisions: adding
"code" would also rewrite the Code in Claude Code (brand name) → never do that
- For brand names that need protecting, leave them out entirely
- For VN place names, only add ones where the unaccented form is unambiguous (skip
Hue — collides with English "hue")
Override / disable:
uv run scripts/text_to_mp3.py --file s.txt --pronounce-map workspace/.../map.json -o out.mp3
uv run scripts/text_to_mp3.py --file s.txt --no-pronounce-map -o out.mp3
The script prints every applied substitution to stderr (e.g. 'doc' -> 'đóc' (4x)) so you can verify what changed.
Number formatting (VN narration)
The multilingual TTS mis-reads digit groups that use Vietnamese conventions, because it falls back to English rules (dot = decimal, comma = thousands). Examples:
| Source digits | Misread as | Should say |
|---|
82.820 | "eighty-two point eight two zero" | "tám mươi hai nghìn tám trăm hai mươi" |
28,8 | "twenty-eight comma eight" | "hai mươi tám phẩy tám" |
4.000 | "four point zero zero zero" | "bốn nghìn" |
Rule: in VN scripts, spell out multi-digit numbers with separators as Vietnamese words before TTS. The script does not auto-convert (VN number-to-words is non-trivial — proper "lăm" vs "năm", "mốt" vs "một", placement of "nghìn/triệu/tỷ"), but it warns to stderr on every run when a thousand-separator dot or comma-decimal is detected:
Warning: VN TTS may mis-read these digit groups — consider spelling them as VN words in the script:
'82.820' (thousand-separator dot (e.g. 82.820))
'28,8' (comma decimal (e.g. 28,8))
When you see the warning, edit the script and re-run. Small standalone digits (10 tòa, 25 tiện ích, 71 phần trăm, ranges like 70-80) usually read fine — leave them as digits.
Workflow
- Load
ELEVENLABS_API_KEY from project .env
- Read text from
--file or positional arg, strip whitespace
- Apply pronunciation map (unless
--no-pronounce-map) — whole-word case-insensitive replacement
- Validate
len(text) <= 5000
POST https://api.elevenlabs.io/v1/text-to-speech/{voice_id}?output_format=mp3_44100_128
- Header:
xi-api-key: <key>, Content-Type: application/json, Accept: audio/mpeg
- Body:
{
"text": "...",
"model_id": "eleven_v3",
"voice_settings": {
"stability": 0.5,
"similarity_boost": 0.75,
"style": 0,
"use_speaker_boost": true
}
}
- Stream audio bytes directly to output MP3 (no transcoding needed — server returns MP3)
- Print
output_path, size_mb, char_count, voice_id, model_id
Output Convention
- Short/test:
workspace/assets/elevenlabs/<name>.mp3
- Video production:
workspace/content/YYYY-MM-DD/video-short/<project>/voiceover.mp3
Requirements
ELEVENLABS_API_KEY in project .env (header auth: xi-api-key)- Optional
ELEVENLABS_VOICE_ID in .env to lock a different default voice
- Python deps managed via PEP 723 inline metadata (auto-installed by
uv run): requests, python-dotenv
- No
ffmpeg needed — ElevenLabs returns MP3 directly
Why no chunking
ElevenLabs limits requests to 5000 characters. The skill fails fast above that limit instead of auto-splitting because:
- A single voiceover should be a coherent chunk — splitting mid-script causes prosody jumps at concat boundaries
- The user's content (hooks, short scripts, video segments) typically fits well under 5000 chars
- If the user genuinely needs longer audio, they should split the script semantically (paragraph breaks) and call this skill per chunk, then concat with ffmpeg in their own pipeline
API Reference
