Turning it into audio¶

Everything up to this point produces a script that is meant to be spoken. This turns it into a file you can play.

uv run mimem build paper.pdf --out out/paper --speak sapi

That is the whole thing: a PDF goes in, out/paper/audio.wav comes out, with the pauses in it.

If you already have a programme, synthesise it on its own:

uv run mimem speak out/paper --engine sapi --voice "Microsoft Zira Desktop"

Choosing an engine¶

`--engine`	Needs	Good for
`silent`	nothing	Seeing a programme's true length and shape before paying to voice it. The default.
`sapi`	Windows	Hearing whether a programme works, free and offline. Not a nice voice.
`piper`	a Piper install and a voice file	Listening properly, offline and free.
`openai`	a URL, usually a key	Listening properly, at the best quality, for money.

List what a voice engine offers:

uv run mimem voices --engine sapi

--engine openai speaks the POST /audio/speech shape, which is not only OpenAI's: point --base-url at a local VoiceStudio or any other compatible server and it is the same code path.

uv run mimem speak out/paper --engine openai --base-url http://localhost:8000/v1 --voice nova

Start with silent

It produces correctly-shaped silence at a plausible speaking rate, so you can check the length, the structure and the timing map without a voice, a key or a network. If something is wrong with the programme, this is where you find out, in a second and for nothing.

What you get¶

audio.wav: The programme. One WAV, uncompressed, because that is what concatenates exactly and needs no dependency to write. Convert it afterwards if you want something smaller.
timings.json: Where every beat landed: its start, how long it actually ran, how long the pause after it actually was, and what the profile had predicted. This is what a player needs to jump to a beat, and what tells you whether the duration arithmetic is any good.

The pauses are real silence¶

A retrieval prompt is only useful if the gap after it is long enough to actually try to remember. mimem does not ask the engine for a break — engines vary in whether they honour one, and TTS-02 forbids relying on prosody markup — it inserts the silence itself, in frames, during assembly.

Two consequences worth knowing. The pauses are exact, and they are identical whichever engine you choose; that is what rule TTS-05's engine choice must not change the content means in practice. And a 20-minute programme typically contains around two minutes of deliberate silence, which is not a bug in the file.

The second run is cheap¶

Audio is cached by content. Fix one sentence, run again, and one beat is re-synthesised:

synthesising 89 beats with sapi
  19.9 min of audio, 1 beats synthesised, 88 reused from cache

The key is the text plus the engine and voice, so changing voice re-synthesises rather than replaying the old one under a new name. Beats whose text is identical — the retrieval cue is said many times in a programme — are synthesised once and heard as often as the script says.

--no-cache disables it. Deleting out/paper/.speech is the whole of cache invalidation.

Predicted length versus real length¶

Every duration in mimem up to this point was a word count divided by the profile's words-per-minute. Now there is a measurement to compare it against, and it prints on every run:

  19.9 min of audio, 73 beats synthesised, 16 reused from cache
  predicted 19.2 min, so 0.7 min over (4%)

Four percent, on that paper, through that engine — close, but consistently short, at a median of about three-quarters of a second per beat. If you are tuning segment lengths, the real numbers are in timings.json.

Known limits¶

Output is WAV only. A 20-minute programme is around 50 MB. Adding MP3 would mean shelling out to ffmpeg, which is a dependency and a platform matrix this project does not want.
sapi starts a PowerShell process per beat, which costs about a second each: a 90-beat programme takes under two minutes to synthesise, and almost all of it is startup.
piper will not download a voice for you. A tool that quietly pulls hundreds of megabytes from a third party on first run is not one to trust with your reading; fetch the .onnx yourself and pass it with --voice.
Nothing plays it for you yet. Scheduling, playback and review across sessions are part two.