Fun-ASR

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Overview

This is a new-generation large speech recognition model that focuses on Mandarin Chinese, English, and Japanese. It supports a wide range of regional dialects, offers enhanced noise robustness, and adapts to diverse and complex environments, making it the top recommendation for users in China.This is a snapshot released on August 25, 2025.

Input

Audio

Output

Text

Features

Prefix Completion

Enable Partial Mode when calling the Qwen API to make the model continue strictly from your provided prefix text.View docs

Function Calling

Use function calling to connect large language models with external tools and systems.View docs

Cache

Context Cache stores shared prefixes for long-context requests to reduce repeated computation, improve latency, and lower cost.View docs

Structured Outputs

Structured Outputs help ensure the model returns a JSON string in the expected format.View docs

Batches

Asynchronously process requests in batches to reduce costs.View docs

Web Search

Enable web search so the model can answer with real-time retrieved data.View docs

Fine-tuning

Train models on sample data to better adapt them to specific tasks.View docs

Pricing

Audio Duration
$0.000035Per second

Rate Limits

RPMRequests Per Minute
600

API Reference

Call API

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from http import HTTPStatus
from dashscope.audio.asr import Transcription
import dashscope
import os
import json

dashscope.api_key = os.getenv("DASHSCOPE_API_KEY")

task_response = Transcription.async_call(
    model='fun-asr-2025-08-25',
    file_urls=['https://dashscope.oss-cn-beijing.aliyuncs.com/samples/audio/paraformer/hello_world_female2.wav',
               'https://dashscope.oss-cn-beijing.aliyuncs.com/samples/audio/paraformer/hello_world_male2.wav']
)

transcribe_response = Transcription.wait(task=task_response.output.task_id)
if transcribe_response.status_code == HTTPStatus.OK:
    print(json.dumps(transcribe_response.output, indent=4, ensure_ascii=False))
    print('transcription done!')