AudioCPP Command Usage

Use audiocpp_cli for direct model inference.

audiocpp_cli --task <task> --family <family> --model <model-dir> --backend <backend> [inputs] [outputs]

Common Options

Option	Values	Default	Meaning
--task	gen, tts, clon, vc, svc, s2s, asr, align, vad, diar, sep, vdes	required	User task.
--family	model family name	required	Selects the model implementation. Must match a registered loader (audiocpp_cli --list-loaders).
--model	local model directory	required	Path to local model assets.
--backend	cpu, cuda, vulkan, metal, best	cpu	Inference backend.
--mode	offline, streaming	offline	Run mode. Most models are offline.
--device	integer	0	Backend device index.
--list-devices	flag	off	List available backend devices and exit; combine with --backend/--device to select one.
--threads	integer	4	Backend/OpenMP worker threads.
--log	flag	off	Print progress and timing logs to stdout.
--log-file	path	not set	Stream progress and timing logs to a file.
--metrics	flag	off	Print compact offline wall time, audio duration, RTF, realtime speed, sample rate, and channel metrics.

Common Inputs And Outputs

Option	Used by	Meaning
--text	generation, TTS, ASR context, alignment transcript	Input text.
--audio	generation/editing, ASR, VAD, diarization, separation, conversion, alignment	Input WAV, or - to stream raw PCM from stdin (requires --mode streaming).
--input-format	streaming ASR with --audio -	Raw PCM sample format, s16le or f32le. Default s16le.
--input-rate	streaming ASR with --audio -	Raw PCM sample rate in Hz. Default 16000.
--input-channels	streaming ASR with --audio -	Raw PCM channel count. Default 1.
--voice-ref	voice clone / voice design / some VC paths	Reference voice WAV.
--language	language-aware models	Language code.
--out	audio-producing models	Output WAV path.
--out-dir	multi-output or batch models	Output directory.
--segments-out	VAD	Speech segments JSON.
--vad-chunks-out	offline VAD	VAD-based audio chunk windows JSON.
--turns-out	diarization	Speaker turns JSON.
--words-out	ASR/alignment	Word timestamps JSON.
--audio-chunk-seconds	ASR	Split long audio before model inference, where supported.
--audio-chunk-mode	ASR/alignment	auto, fixed, vad, or none, where supported.

Common Generation Options

Omit these unless you need explicit control. If --seed is omitted, models that sample use a random seed.

Option	Values	Meaning
--seed	integer	Reproducible random seed.
--max-tokens	integer	Maximum generated tokens for AR/LLM-style models.
--max-steps	integer	Maximum diffusion or generation steps for models that expose it.
--temperature	float	Sampling temperature.
--top-k	integer	Top-k sampling limit.
--top-p	float in (0, 1]	Nucleus sampling limit.
--repetition-penalty	float	Penalize repeated tokens.
--do-sample	true, false	Enable sampling instead of greedy decode.
--guidance-scale	float	Classifier-free guidance scale.
--num-inference-steps	integer	Diffusion/flow denoising steps.
--text-chunk-size	integer chars	Split long text where supported, including TTS text.
--text-chunk-mode	default, tag_aware, japanese, endline	Select text chunking mode where supported.

Batch Inputs

Option	Meaning
--request-sequence <json>	Run multiple JSON requests through one offline model session.
--batch-text-file <txt>	One request per non-empty text line.
--batch-text-dir <dir>	One request per .txt, .md, or .json file; each file is normalized into a single paragraph.
--batch-audio-dir <dir>	One request per .wav file.
`--batch-audio-role audio	voice_ref
`--batch-merge-audio none	concat`
--batch-manifest-out <json>	Write a batch output manifest.

--batch-text-dir reads .txt and .md files as plain text. For .json, use either a JSON string root or an object with a string input or text field.

Use --request-sequence when you want to send multiple requests in one long-lived offline session:

audiocpp_cli --task tts --family pocket_tts \
  --model models/PocketTTS-GGUF/english/pocket-tts-english-q8_0.gguf \
  --backend cuda \
  --request-sequence requests.json \
  --out-dir outputs \
  --metrics

For each request id, --metrics prints metrics[<id>].wall_ms, audio_duration_ms, rtf, x_realtime, sample_rate, and channels.

Model Docs

Need	Doc
Speech, voice clone, long-form TTS	tts.md
Music and sound generation	music_generation.md
OmniVoice TTS, voice cloning, voice design, and streaming	models/omnivoice.md
ASR models	asr.md
VAD and diarization	speech_analysis.md
Voice conversion codec and source separation	audio_tools.md