voice_audio_multi/docs/models/gigaam_asr.md

GigaAM ASR

GigaAM v3 and GigaAM Multilingual use the gigaam_asr family. Both are released under the MIT license.

Field	Value
Task	asr
Mode	offline
Output	Transcript text, longform segments, optional word timestamps
Long-form audio	Automatic quiet-energy chunking
Languages	v3: Russian; Multilingual: Russian, Kazakh, Kyrgyz, Uzbek, English

Variants

Upstream repository	Revision	GGUF filename
ai-sage/GigaAM-v3	ctc	gigaam-v3-ctc-f16.gguf
ai-sage/GigaAM-v3	rnnt	gigaam-v3-rnnt-f16.gguf
ai-sage/GigaAM-v3	e2e_ctc	gigaam-v3-e2e-ctc-f16.gguf
ai-sage/GigaAM-v3	e2e_rnnt	gigaam-v3-e2e-rnnt-f16.gguf
ai-sage/GigaAM-Multilingual	ctc	gigaam-multilingual-ctc-f32.gguf
ai-sage/GigaAM-Multilingual	ctc	gigaam-multilingual-ctc-f16.gguf
ai-sage/GigaAM-Multilingual	large_ctc	gigaam-multilingual-large-ctc-f32.gguf
ai-sage/GigaAM-Multilingual	large_ctc	gigaam-multilingual-large-ctc-f16.gguf

E2E variants restore punctuation and capitalization. Select the checkpoint by passing its GGUF file directly. Language is inferred from the audio, not selected by a request option.

Convert

Download a fine-tuned ASR checkpoint, not the SSL-only encoder:

hf download ai-sage/GigaAM-v3 --revision ctc --local-dir models/GigaAM-v3-ctc
python tests/gigaam_asr/convert_gguf.py models/GigaAM-v3-ctc \
  models/GigaAM-ASR-GGUF/gigaam-v3-ctc-f16.gguf \
  --staging-dir models/GigaAM-v3-ctc/converted

The converter requires PyTorch, safetensors, and build/debug/bin/audiocpp_gguf. It preserves checkpoint tensor dtypes and embeds configuration, model spec, and the SentencePiece tokenizer where needed. In v3 packages, the encoder is F16 while frontend and decoder tensors retain their original precision. Use the repository, revision, and filename from the table for other variants. For an F16 multilingual package, add --type f16 and use -f16.gguf as the filename suffix. The frontend, normalization weights, and biases remain F32.

CLI

audiocpp_cli --task asr --family gigaam_asr \
  --model models/GigaAM-ASR-GGUF/gigaam-v3-ctc-f16.gguf \
  --backend cuda --audio speech.wav --text-out transcript.txt --log

For CPU inference, use --backend cpu --threads 8. Long recordings are split automatically and the chunk transcripts are joined in order. Add --words-out words.json to enable and save word timestamps. Add --segments-out segments.json to save the longform chunk boundaries and text. Word timestamps come from decoder token emission frames, not forced alignment.

For VAD-based segmentation, set --request-option audio_chunk_mode=vad and --session-option gigaam_asr.vad_model_path=/path/to/vad-model. The selected VAD must support the input sample rate. For example, the bundled Silero weights are in assets/framework/models/silero_vad and require 16 kHz input. The VAD is loaded only when requested. This uses the framework VAD chunker; it does not reproduce the official Python pipeline's external Pyannote segment boundaries.

Use --session-option weight_type=<type> only to override the packaged tensor storage type at load time.

Server Timestamps

Send JSON to /v1/audio/transcriptions/details with the configured model ID:

{
  "model": "gigaam",
  "audio_path": "/path/to/speech.wav",
  "options": {"return_timestamps": true}
}

The response contains words, and segments for chunked longform audio. Their start_sample and end_sample values use the response's sample_rate. The multipart transcription route does not forward custom options; use the JSON request above to select timestamp or chunking options.

Request Options (use with --request-option)

Option	Default	Meaning
return_timestamps	false	Include word start/end times; enabled automatically by CLI --words-out.
audio_chunk_mode	auto	auto and quiet_energy split near quiet points; fixed uses equal-duration chunks; vad uses the selected VAD; none processes the whole recording at once.
audio_chunk_duration_sec	25	Maximum chunk duration, from 0.02 to 25 seconds. Ignored by none; disabling chunking increases memory use on long recordings.

Session Options (use with --session-option)

Option	Default	Meaning
weight_type	native	Weight storage override.
gigaam_asr.vad_model_path	Empty	Offline VAD model path, required only for audio_chunk_mode=vad. Legacy unprefixed vad_model_path remains accepted.

Translation, speaker labels, and live audio streaming are not exposed by this port.