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QwenQwen3-ASR-0.6B

Qwen3ASR

Provides Qwen3-ASR with a domain prompt and deterministic decoding controls.

Automatic speech recognitionVoiceHub-nativeqwen3-asrParameters: 938MLanguages: ar, yue +28Training: nativeLicense: Checkpoint-specific

Parameter metadata: Exact serialized tensor-element total from VoiceHub's audited native primary checkpoint; a distinct learned-parameter total is not available.

Use this model Checkpoint
Resources
Upstream GitHub VoiceHub source Open in Colab

Usage

Complete the VoiceHub installation once, then run this repository-authored example. Model pages intentionally contain no package-install command.

This example is maintained against VoiceHub's public API; it is not copied from an upstream demo or package README.

Model-specific path: Provides Qwen3-ASR with a domain prompt and deterministic decoding controls.

Inputs and controls: Prompts should contain context, not a fabricated transcript of the input audio.

from pathlib import Path

from voicehub import AutoModelForSpeechRecognition

AUDIO_FILE = Path("speech.wav")
if not AUDIO_FILE.is_file():
    raise FileNotFoundError(AUDIO_FILE)

model = AutoModelForSpeechRecognition.from_pretrained(
    'Qwen/Qwen3-ASR-0.6B',
    model_type='asr_qwen3',
    device="cuda",
    lazy_load=True,
)
output = model.transcribe(
    AUDIO_FILE,
    language="en",
    prompt="Technical meeting with VoiceHub terminology",
    do_sample=False,
)
print(output.text)
for segment in output.segments:
    print(segment.start, segment.end, segment.text, segment.confidence)

Use authorized recordings. Verify hardware needs and pin a revision in production.

Overview

asr_qwen3 is a VoiceHub automatic speech recognition integration. This page is generated from its registry contract. Open the asr_qwen3 Colab notebook.

Property Value
Task Automatic speech recognition
Architecture qwen3-asr
Runtime VoiceHub-native
Languages ar, yue, zh, cs, … complete audited list below
Capabilities automatic-speech-recognition, multilingual, language-identification, hotwords, long-form, safetensors, fine-tuning, lora, voicehub-native, native-runtime
Reusable components —
Normalized output ASROutput

Language support

Supported language abbreviations

ar, yue, zh, cs, da, nl, en, fil, fi, fr, de, el, hi, hu, id, it, ja, ko, mk, ms, fa, pl, pt, ro, ru, es, sv, th, tr, vi

The same checkpoint also names Anhui, Dongbei, Fujian, Gansu, Guizhou, Hebei, Henan, Hubei, Hunan, Jiangxi, Ningxia, Shandong, Shaanxi, Shanxi, Sichuan, Tianjin, Yunnan, Zhejiang, Cantonese (Hong Kong accent), Cantonese (Guangdong accent), Wu, and Minnan dialects.

Paper and GitHub

Configuration

Load configuration without constructing the model:

from voicehub import AutoConfig

config = AutoConfig.for_model('asr_qwen3')
print(config.model_type)
Property Value
Canonical model type asr_qwen3
Configuration class Qwen3ASRConfig
Architecture class Qwen3ASRForSpeechRecognition

Processing

Create the registered processor without allocating model weights:

from voicehub import AutoProcessor

processor = AutoProcessor.from_pretrained(
    'Qwen/Qwen3-ASR-0.6B',
    model_type='asr_qwen3',
)
print(type(processor).__name__)

Inference

The Usage example returns ASROutput through AutoModelForSpeechRecognition.

Input and output contract

Property Value
Readiness integrated-raw
Data architecture prompted-multimodal
Sample rate 16,000 Hz
Contract getter get_asr_dataset_spec('asr_qwen3')
Variant Required fields One of Boundary Other rules
raw-audio audio text / transcription / transcript Source at most one: text / transcription / transcript
qwen3-model-ready input_ids, attention_mask, input_features, feature_attention_mask, labels — Prepared —

Qwen3-ASR completion-only multimodal fine-tuning records. See the data workflow.

Training and optimization

Use available_optimization_passes() to discover reversible public passes. Unsupported runtime or hardware fails closed before mutation.

Training contract

Property Value
Support native
Family speech-sequence-to-sequence
Recipe single-phase
Default phase speech_recognition
Training checkpoint Qwen/Qwen3-ASR-0.6B
Native training graph yes
Phase Kind Components Required inputs Loss keys
speech_recognition objective model — loss

The integration accepts its declared source or prepared contract directly. Call model.validate_training_support() first, then follow the training workflow.

Checkpoints, provenance, license, and limitations

Property Value
Default checkpoint Qwen/Qwen3-ASR-0.6B
Hugging Face ID Qwen/Qwen3-ASR-0.6B
Repository availability verified through the Hugging Face model API on 2026-08-11; pin a revision before production use.
Checkpoint status Registry default; pin an immutable revision for production and reproducible evidence
Optional dependency extra Core package
Hardware and runtime Usage selects cuda; verify checkpoint-specific requirements
Real-checkpoint evidence Release evidence; a registry default alone is not execution evidence
Implementation voicehub.models.asr_qwen3.modeling_asr_qwen3.Qwen3ASRForSpeechRecognition
Configuration voicehub.models.asr_qwen3.configuration_asr_qwen3.Qwen3ASRConfig
Source provenance voicehub/architectures/qwen3_asr/SOURCE.json
License Checkpoint-specific

No VoiceHub-specific license override is registered. Verify the checkpoint and upstream source terms before use.

Confirm the checkpoint revision, access terms, provenance, and license.

Limitations

  • No integration-specific checkpoint limitation is registered. Verify the selected checkpoint revision and its documented runtime requirements.
  • Validate memory, precision, and optional dependencies on the target system.
  • Public optimizations fail closed when the runtime or hardware cannot satisfy their validation contract; an unavailable pass is not reported as applied.
  • Contract tests do not replace the linked released-checkpoint evidence.

Public API

Use the stable configuration, processor, and task-model facades below.

Configuration

Qwen3ASRConfig

View source

Qwen3ASRConfig(**config_kwargs)

Parameters

  • **config_kwargs — Configuration fields validated by Qwen3ASRConfig.

Model

Qwen3ASRForSpeechRecognition

View source

AutoModelForSpeechRecognition.from_pretrained(
    pretrained_model_name_or_path,
    *,
    model_type='asr_qwen3',
    config=None,
    **model_kwargs,
)

Parameters

  • pretrained_model_name_or_path — Hub ID or compatible local directory.
  • model_type — Canonical model type; use 'asr_qwen3'.
  • config — Optional preloaded Qwen3ASRConfig instance.
  • **model_kwargs — Model-specific loading arguments.
from voicehub import get_model_spec

spec = get_model_spec('asr_qwen3')
print(spec.display_name, spec.task.value)
Purpose Public object
Discover get_model_spec('asr_qwen3')
Load and run AutoModelForSpeechRecognition
Configure Qwen3ASRConfig
Process AutoProcessor
Model implementation Qwen3ASRForSpeechRecognition
Normalized output ASROutput
Training contract get_training_spec('asr_qwen3')
Optimization lifecycle available_optimization_passes, apply_optimization_plan, optimization_manifest, restore_optimization_plan

See all model guides, inference, and the training matrix.