aliyun-qwen-asr

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Use when transcribing non-realtime speech with Alibaba Cloud Model Studio Qwen ASR models (`qwen3-asr-flash`, `qwen-audio-asr`, `qwen3-asr-flash-filetrans`). Use when converting recorded audio files to text, generating transcripts with timestamps, or documenting DashScope/OpenAI-compatible ASR request and response fields.

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Sourcecinience/alicloud-skills
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NPX Install

npx skill4agent add cinience/alicloud-skills aliyun-qwen-asr

Tags

Translated version includes tags in frontmatter
qwen-asrspeech-to-textdashscopeaudio-transcriptionnon-realtime-asr

SKILL.md Content

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Category: provider

Model Studio Qwen ASR (Non-Realtime)

Validation

bash
mkdir -p output/aliyun-qwen-asr
python -m py_compile skills/ai/audio/aliyun-qwen-asr/scripts/transcribe_audio.py && echo "py_compile_ok" > output/aliyun-qwen-asr/validate.txt
Pass criteria: command exits 0 and 
output/aliyun-qwen-asr/validate.txt
is generated.

Output And Evidence

  • Store transcripts and API responses under 
    output/aliyun-qwen-asr/
    .
  • Keep one command log or sample response per run.
Use Qwen ASR for recorded audio transcription (non-realtime), including short audio sync calls and long audio async jobs.

Critical model names

Use one of these exact model strings:
  • qwen3-asr-flash
  • qwen3-asr-flash-2026-02-10
  • qwen-audio-asr
  • qwen3-asr-flash-filetrans
  • qwen3-asr-flash-filetrans-2025-11-17
Selection guidance:
  • Use 
    qwen3-asr-flash
    , 
    qwen3-asr-flash-2026-02-10
    , or 
    qwen-audio-asr
    for short/normal recordings (sync).
  • Use 
    qwen3-asr-flash-filetrans
    or 
    qwen3-asr-flash-filetrans-2025-11-17
    for long-file transcription (async task workflow).

Prerequisites

  • Install SDK dependencies (script uses Python stdlib only):
bash
python3 -m venv .venv
. .venv/bin/activate
  • Set 
    DASHSCOPE_API_KEY
    in environment, or add 
    dashscope_api_key
    to 
    ~/.alibabacloud/credentials
    .

Normalized interface (asr.transcribe)

Request

  • audio
    (string, required): public URL or local file path.
  • model
    (string, optional): default 
    qwen3-asr-flash
    .
  • language_hints
    (array<string>, optional): e.g. 
    zh
    , 
    en
    .
  • sample_rate
    (number, optional)
  • vocabulary_id
    (string, optional)
  • disfluency_removal_enabled
    (bool, optional)
  • timestamp_granularities
    (array<string>, optional): e.g. 
    sentence
    .
  • async
    (bool, optional): default false for sync models, true for 
    qwen3-asr-flash-filetrans
    .

Response

  • text
    (string): normalized transcript text.
  • task_id
    (string, optional): present for async submission.
  • status
    (string): 
    SUCCEEDED
    or submission status.
  • raw
    (object): original API response.

Quick start (official HTTP API)

Sync transcription (OpenAI-compatible protocol):
bash
curl -sS --location 'https://dashscope.aliyuncs.com/compatible-mode/v1/chat/completions' \
  --header "Authorization: Bearer $DASHSCOPE_API_KEY" \
  --header 'Content-Type: application/json' \
  --data '{
    "model": "qwen3-asr-flash",
    "messages": [
      {
        "role": "user",
        "content": [
          {
            "type": "input_audio",
            "input_audio": {
              "data": "https://dashscope.oss-cn-beijing.aliyuncs.com/audios/welcome.mp3"
            }
          }
        ]
      }
    ],
    "stream": false,
    "asr_options": {
      "enable_itn": false
    }
  }'
Async long-file transcription (DashScope protocol):
bash
curl -sS --location 'https://dashscope.aliyuncs.com/api/v1/services/audio/asr/transcription' \
  --header "Authorization: Bearer $DASHSCOPE_API_KEY" \
  --header 'X-DashScope-Async: enable' \
  --header 'Content-Type: application/json' \
  --data '{
    "model": "qwen3-asr-flash-filetrans",
    "input": {
      "file_url": "https://dashscope.oss-cn-beijing.aliyuncs.com/audios/welcome.mp3"
    }
  }'
Poll task result:
bash
curl -sS --location "https://dashscope.aliyuncs.com/api/v1/tasks/<task_id>" \
  --header "Authorization: Bearer $DASHSCOPE_API_KEY"

Local helper script

Use the bundled script for URL/local-file input and optional async polling:
bash
python skills/ai/audio/aliyun-qwen-asr/scripts/transcribe_audio.py \
  --audio "https://dashscope.oss-cn-beijing.aliyuncs.com/audios/welcome.mp3" \
  --model qwen3-asr-flash \
  --language-hints zh,en \
  --print-response
Long-file mode:
bash
python skills/ai/audio/aliyun-qwen-asr/scripts/transcribe_audio.py \
  --audio "https://dashscope.oss-cn-beijing.aliyuncs.com/audios/welcome.mp3" \
  --model qwen3-asr-flash-filetrans \
  --async \
  --wait

Operational guidance

  • For local files, use 
    input_audio.data
    (data URI) when direct URL is unavailable.
  • Keep 
    language_hints
    minimal to reduce recognition ambiguity.
  • For async tasks, use 5-20s polling interval with max retry guard.
  • Save normalized outputs under 
    output/aliyun-qwen-asr/transcripts/
    .

Output location

  • Default output: 
    output/aliyun-qwen-asr/transcripts/
  • Override base dir with 
    OUTPUT_DIR
    .

Workflow

  1. Confirm user intent, region, identifiers, and whether the operation is read-only or mutating.
  2. Run one minimal read-only query first to verify connectivity and permissions.
  3. Execute the target operation with explicit parameters and bounded scope.
  4. Verify results and save output/evidence files.

References

  • references/api_reference.md
  • references/sources.md
  • Realtime synthesis is provided by 
    skills/ai/audio/aliyun-qwen-tts-realtime/
    .