Fun-ASR-Realtime

Will be retired on October 10, 2026View announcement

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Overview

This is the real-time version of Tongyi Lab's next-generation end-to-end speech recognition model, based on leading proprietary speech technology, and boasts exceptional contextual awareness and high-precision speech transcription capabilities. Based on an end-to-end architecture, Fun-ASR integrates innovative RAG technology, supporting multi-dimensional features such as large-scale hotword customization, automatic filtering of sensitive and modal particles, ITN normalization, and punctuation prediction, significantly improving overall recognition accuracy and contextual relevance. Furthermore, Fun-ASR supports flexible switching between Chinese and English, covers multiple regional dialects, and boasts enhanced noise robustness, adapting to diverse and complex environments.This is a snapshot released on November 7, 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
$0.000047Per second

Rate Limits

RPMRequests Per Minute
1K

API Reference

Call API

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from http import HTTPStatus
from dashscope.audio.asr import Recognition

# If you have not configured the API key in the environment variable, uncomment the following line and replace apiKey with your API key
# import dashscope
# dashscope.api_key = "apiKey"

recognition = Recognition(model='fun-asr-realtime-2025-11-07',
                          format='wav',
                          sample_rate=16000,
                          # “language_hints” only supports paraformer-realtime-v2
                          language_hints=['zh', 'en'],
                          callback=None)
result = recognition.call('asr_example.wav')
if result.status_code == HTTPStatus.OK:
    print('Results: ')
    print(result.get_sentence())
else:
    print('Error: ', result.message)
    
print(
    '[Metric] requestId: {}, first package delay ms: {}, last package delay ms: {}'
    .format(
        recognition.get_last_request_id(),
        recognition.get_first_package_delay(),
        recognition.get_last_package_delay(),
    ))