Alibaba Cloud AI Audio ASR Realtime

Use when low-latency realtime speech recognition is needed with Alibaba Cloud Model Studio Qwen ASR Realtime models, including streaming microphone input, li...

Category: provider

Model Studio Qwen ASR Realtime

Validation

bash

mkdir -p output/aliyun-qwen-asr-realtime
python -m py_compile skills/ai/audio/aliyun-qwen-asr-realtime/scripts/prepare_realtime_asr_request.py && echo "py_compile_ok" > output/aliyun-qwen-asr-realtime/validate.txt

Pass criteria: command exits 0 and output/aliyun-qwen-asr-realtime/validate.txt is generated.

Output And Evidence

• Save session payloads and response samples under output/aliyun-qwen-asr-realtime/.

Critical model names

Use one of these exact model strings:

• qwen3-asr-flash-realtime
• qwen3-asr-flash-realtime-2026-02-10

Use cases

• Realtime subtitles and captions
• Voice-agent duplex input
• Streaming speech-to-text in browser or terminal clients

Prerequisites

• Set DASHSCOPE_API_KEY in your environment, or add dashscope_api_key to ~/.alibabacloud/credentials.
• Realtime sessions generally require WebSocket or streaming session handling in the client.

Normalized interface (asr.realtime)

Request

• model (string, optional): default qwen3-asr-flash-realtime
• language_hints (array, optional)
• format (string, optional): e.g. pcm, wav
• sample_rate (int, optional): e.g. 16000
• chunk_ms (int, optional): frame size in milliseconds

Response

• text (string): recognized transcript fragment
• is_final (bool): finalization marker
• usage (object, optional)

Quick start

Generate a request template:

bash

python skills/ai/audio/aliyun-qwen-asr-realtime/scripts/prepare_realtime_asr_request.py \
  --output output/aliyun-qwen-asr-realtime/request.json

Operational guidance

• Prefer 16kHz mono PCM unless your client stack requires another format.
• Keep chunks small enough for responsive partial results.
• If you only have recorded files, use skills/ai/audio/aliyun-qwen-asr/ instead.

References

• references/sources.md