Papercut voice

Every later stage needs two things in the narration folder: voice/final_narrator/<id>.wav (one WAV per script line) and timing_narrator.js (a start and end for every word). This skill produces them by one of three paths, then builds the captions and the scene plan. The full reference for the scripts is library/voice/README.md.

Preflight

• Library: $PAPERCUT_LIB, else the PAPERCUT_LIB= line in ~/.config/papercut-explainer/config.env, else ask once. Export it, and . "$PAPERCUT_LIB/env.sh" loads ASR_PY, QWEN_TTS_PY and the other config values into the shell.
• A scaffolded project (papercut-build, step 1) with narration/script.json and papercut/episode.json holding scenes. new_episode.sh copies build_timing.py into narration/.
• If the user already has a TTS installed, use it as it is and don't rebuild it (path B, or A if it is Qwen3-TTS). Ask once which one and where it runs. Otherwise ask which path, and say what it needs:

Path	Needs	Install mode
A. Local Qwen3-TTS	the voice venv from library/voice/setup_tts.sh (model download 2.3-4.2 GB)	Full
B. Your own recording or another TTS	an ASR backend (mlx-whisper or faster-whisper) and librosa + numpy for the pitch pass, in the Python that ASR_PY and QWEN_TTS_PY name	Full, or those packages by hand
C. Placeholder	ffmpeg; macOS for --say	Standard

If the path needs more than the install has, run ./install.sh --doctor and hand over to papercut-setup. Without ASR, build_timing.py only estimates 2.75 words a second, so captions drift against real audio.

Path A: local Qwen3-TTS

From the series folder:

cp $PAPERCUT_LIB/voice/voice.example.json voice/voice.json     # once per series; edit it
$PAPERCUT_LIB/voice/narrate.sh voice/voice.json episodes/NN-slug/narration
$PAPERCUT_LIB/voice/finalize.sh voice/voice.json episodes/NN-slug/narration episodes/NN-slug/narration/voice/takes/narrator [num.json]

• voice.json: speaker (CustomVoice: Aiden, Dylan, Eric, Ryan, Serena, Vivian, Sohee, Ono_anna, Uncle_fu) and instruct. Recommended: CustomVoice 1.7B, Ryan or Aiden, instruct "friendly, natural, conversational, like telling a friend; clear pauses between sentences; stress the key word of each line". takes_per_line defaults to 3. tempo stays 1.0 (other values need rubberband). qa_targets set the pitch range and the ASR match (0.9).
• A script line can carry tts (respelled text for pronunciation; captions keep text) and its own instruct. num.json maps numerals to spoken words ({"13,000": "thirteen thousand"}) so ASR matching doesn't fail on digits.
• Run one TTS process at a time; the 1.7B model is memory-hungry.
• finalize.sh runs ASR and pitch on every take, picks one per line, trims, loudness-normalises to -16 LUFS, re-runs ASR on the finals and writes timing_narrator.js. After listening, put corrections in voice/picks_override.json ({"l3_name": 2}) and rerun with SKIP_PICK=1.
• Voice Design (describing a voice in words) is a Qwen3-TTS mode that narrate.py doesn't drive. Generate with it elsewhere and use path B.

Path B: your own recording or another TTS

• Put one WAV per line in voice/final_narrator/<id>.wav, or raw takes as voice/takes/narrator/<id>_<k>.wav and run finalize.sh as above.
• For finished lines, transcribe them, write voice/chosen_narrator.json as {id: "voice/final_narrator/<id>.wav"}, then from narration/:

$ASR_PY $PAPERCUT_LIB/voice/asr.py voice/final_narrator/*.wav > voice/asr_narrator_final.json
CHOSEN=voice/chosen_narrator.json TIMING_OUT=timing_narrator.js python3 build_timing.py voice/asr_narrator_final.json

Path C: placeholder

From the narration/ folder:

python3 $PAPERCUT_LIB/tools/placeholder_vo.py [--wps 3.0] [--say [VOICE]]

It writes silent WAVs (or the macOS say voice with --say) and timing_narrator.js from script.json alone, spreading word times by word length. --wps 3.5 to 4 approximates the target pace (default 3.0). The reel can be built and timed first and re-voiced later: swap the WAVs, rerun finalize.sh, rerun build_vo.py, and the word cues follow.

Delivery rules

Delivery is human, unhurried and emphasised. The viewer must follow every line on the first listen.

• Breathing room. A real pause at every sentence end and between list beats ("Fine. Fine. Fine."). Start with 0.3-0.4 s between lines (gap in episode.json, default 0.22; gaps adds an extra beat after one named line) and judge by ear. Pauses go at sentence or clause boundaries only: a 0.2 s gap inside a phrase, such as "copied it, | by taking...", reads as lag. Use the 30 s ceiling for air instead of cutting pauses, and never slow the tempo to get it.
• Emphasis. The one or two words each line leans on (the number, the twist word, the verdict) come from the script's staging table. Pass them as a per-line instruct.
• Tone. Conversational and a little amused, not announcer energy. Questions sound like real questions, the catch line sounds curious, the CTA is warm. The narrator still doesn't joke; the picture does.
• Clone model (no instructions). With a clone voice (ref_audio + ref_text, Base model) the levers are the text and the take. Write the pauses into the punctuation (full stops between list beats, a short question as its own sentence). Generate several seeds of one continuous take (SEED_BASE, takes_per_line), pick the one with the most pitch movement on the target words and ASR 0.9 or better, and re-take a flat line alone (ONLY=l4_peak) and splice it at a sentence boundary. Only clone a voice you have the right to use.
• Whole script at once gives consistent prosody: generate one take, split_take.py cuts it per line, then set "gap": 0 in episode.json. Per scene is fine if the user prefers.
• Play the first three lines to the user before the full run: ONLY=l1_hook,l2_...,l3_... narrate.sh ....

Captions and timing

From papercut/, once episode.json has scenes:

python3 $PAPERCUT_LIB/tools/build_vo.py     # public/vo/voiceover.wav, public/vo/captions.json, src/plan.json
python3 $PAPERCUT_LIB/tools/timing_md.py    # Timing section of STORYBOARD.md

captions.json is a Remotion Caption[]; scene boundaries come from the word timestamps; the composition length is plan.json's durationInFrames. build_vo.py flags any scene under 1.2 s. With no library, transcribe the WAV with the Remotion captions skill (whisper.cpp) or any speech-to-text tool that returns word timestamps.

Captions are one torn tag per word, pages of 1-3 words, at 3.5-4 words a second (../papercut-explainer/references/style-guide.md, sections 11 and 13).

Hand-off

Next is papercut-build (stubs, scenes, sound, render). It reads src/plan.json and the Timing section of papercut/STORYBOARD.md. Any later voice change reruns build_vo.py and timing_md.py; the scene cache then re-renders everything.