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Alibaba Cloud Model Studio:Non-real-time speech recognition (Fun-ASR-Flash) HTTP API

Last Updated:Oct 30, 2026

This topic describes the parameters and interface details of the Fun-ASR-Flash non-real-time speech recognition HTTP API.

For input requirements such as supported audio formats, file size limits, and duration limits, see Audio specifications.

Service endpoints

Singapore

POST https://{WorkspaceId}.ap-southeast-1.maas.aliyuncs.com/api/v1/services/aigc/multimodal-generation/generation

Replace {WorkspaceId} with your actual Workspace ID.

China (Beijing)

POST https://{WorkspaceId}.cn-beijing.maas.aliyuncs.com/api/v1/services/aigc/multimodal-generation/generation

Replace {WorkspaceId} with your actual Workspace ID.

ImportantAlibaba Cloud Model Studio has released workspace-specific domains for the China (Beijing) and Singapore regions. The new dedicated domains deliver superior performance and higher stability for inference requests. We recommend migrating to the new domains:

  • China (Beijing): from dashscope.aliyuncs.com to {WorkspaceId}.cn-beijing.maas.aliyuncs.com
  • Singapore: from dashscope-intl.aliyuncs.com to {WorkspaceId}.ap-southeast-1.maas.aliyuncs.com

Request headers

ParameterTypeRequiredDescription

Authorization

string

Yes

The authentication token, in the format Bearer <your_api_key>. Replace "<your_api_key>" with your actual API key.

Content-Type

string

Yes

The media type of the request body. Fixed to application/json.

X-DashScope-SSE

string

No

Controls whether results are returned as an SSE stream. Set to enable to turn on SSE streaming. The server returns intermediate and final recognition results in multiple messages only for audio that is at least 1 minute long. Set to disable or omit the parameter to return only the final result.

Request body

modelstring(Required)

The model name.

inputobject(Required)

The input information.

Properties

messagesarray(object)(Required)

The message list. It contains the audio to recognize and, optionally, conversation context that improves recognition accuracy.

ImportantThe context feature improves the recognition accuracy of domain-specific terms. For usage, see Context enhancement.

A request can include at most 5 context messages of each type (input_text and text). If you exceed this limit, only the 5 most recent messages are kept. The total context text per turn (the combined length of the text fields in the user and assistant messages) cannot exceed 400 characters, where each character counts as 1. Any excess is truncated from the end.

ImportantWhen you include context, the message order in messages matters: context messages must be arranged by conversation turn. Within each turn, the user message (of type input_text) must come before the corresponding assistant message (of type text). The user message that contains input_audio must be the last item in the messages array.

Properties

rolestring(Required)

The message role. Valid values:

  • user (Required): A user message. When type is input_audio, it holds the audio to recognize. When type is input_text, it holds recognition results from previous turns or a domain-specific word list (optional, used as context).
  • assistant (Optional, context): Replies from the large language model in previous turns.

contentarray(object)(Required)

The message content list.

Properties

typestring(Required)

The content type. Each request needs at least one message of type input_audio. Valid values:

  • input_audio (Required): The audio input to recognize (role is user). You must also pass the input_audio object.
  • input_text (Optional, context): Recognition results of the user's speech from previous turns, or a domain-specific word list (role is user). You must also pass the text field.
  • text (Optional, context): Replies from the large language model in previous turns (role is assistant). You must also pass the text field.

input_audioobject(Conditionally required)

Required when type is input_audio.

Properties

datastring(Required)

The audio data to recognize. For input requirements such as supported audio formats, file size limits, and duration limits, see Audio specifications. Two methods are supported:

  • Audio file URL: Pass a publicly accessible URL to the audio file.
  • Base64 Data URI: Pass the Base64-encoded audio data as a Data URI. The value is the data:{MIME_TYPE};base64, prefix concatenated with the Base64-encoded audio data. Supported MIME types include audio/wav and audio/mp3.

Example (URL): https://example.com/audio/sample.wav

Example (Base64): data:audio/wav;base64,{BASE64_ENCODED_DATA}

textstring(Conditionally required)

When type is input_text, enter the recognition results of the user's speech from previous turns or a domain-specific word list. When type is text, enter the large language model's replies from previous turns. Text length is measured in characters, where each character counts as 1. The combined length of the text fields across all messages in a single context turn cannot exceed 400 characters. Any excess is truncated from the end.

parametersobject(Required)

The model parameters.

NoteText polishing is disabled by default and is not yet available.

Text polishing: While transcribing speech, the model removes meaningless filler words and stuttered repetitions, handles self-corrections, smooths out colloquial expressions, and standardizes punctuation and text formatting. The output is more concise, fluent, and readable while preserving the speaker’s final intent and key information as much as possible.

Properties

formatstring(Required)

The audio format. Set this to match your actual audio format. Supported values include wav, mp3, and opus. For details, see Audio specifications.

sample_ratestring(Optional)

The audio sample rate, in Hz. For example, 16000 means a 16 kHz sample rate. For details, see Audio specifications.

vocabulary_idstring(Optional)

The ID of a precompiled hot word list.

Generate this ID in advance by calling the create hot word list API. Pass the ID during recognition to use the hot words in the list.

Suitable for scenarios where the vocabulary is known and relatively stable, and where you need to reuse the same word list across requests.

For usage details, see Precompiled hotwords.

language_hints array[string](Optional)

The language codes to recognize. If the language is unknown in advance, omit this parameter to let the model detect it automatically. You can set up to 1 value. If you set more, only the first 1 take effect.

Supported language codes

  • zh: Chinese
  • en: English
  • ja: Japanese
  • ko: Korean
  • vi: Vietnamese
  • th: Thai
  • id: Indonesian
  • ms: Malay
  • tl: Filipino
  • hi: Hindi
  • ar: Arabic
  • fr: French
  • de: German
  • es: Spanish
  • pt: Portuguese
  • ru: Russian
  • it: Italian
  • nl: Dutch
  • sv: Swedish
  • da: Danish
  • fi: Finnish
  • no: Norwegian
  • el: Greek
  • pl: Polish
  • cs: Czech
  • hu: Hungarian
  • ro: Romanian
  • bg: Bulgarian
  • hr: Croatian
  • sk: Slovak

The following examples use the configuration for the Singapore region. Replace "{WorkspaceId}" with your actual workspace ID. The configuration differs across regions, and the API key for the Singapore region differs from the one for the Beijing region.

Non-streaming

curl --location --request POST 'https://{WorkspaceId}.ap-southeast-1.maas.aliyuncs.com/api/v1/services/aigc/multimodal-generation/generation' \
     --header "Authorization: Bearer $DASHSCOPE_API_KEY" \
     --header "Content-Type: application/json" \
     --header "X-DashScope-SSE: disable" \
     --data '{
    "model": "fun-asr-flash-2026-06-15",
    "input": {
        "messages": [
            {
                "role": "user",
                "content": [
                    {
                        "type": "input_audio",
                        "input_audio": {
                            "data": "{YOUR_AUDIO_URL}"
                        }
                    }
                ]
            }
        ]
    },
    "parameters": {
        "format": "wav",
        "sample_rate": "16000"
    }
}'

Streaming

curl --location --request POST 'https://{WorkspaceId}.ap-southeast-1.maas.aliyuncs.com/api/v1/services/aigc/multimodal-generation/generation' \
     --header "Authorization: Bearer $DASHSCOPE_API_KEY" \
     --header "Content-Type: application/json" \
     --header "X-DashScope-SSE: enable" \
     --data '{
    "model": "fun-asr-flash-2026-06-15",
    "input": {
        "messages": [
            {
                "role": "user",
                "content": [
                    {
                        "type": "input_audio",
                        "input_audio": {
                            "data": "{YOUR_AUDIO_URL}"
                        }
                    }
                ]
            }
        ]
    },
    "parameters": {
        "format": "wav",
        "sample_rate": "16000"
    }
}'

With context - non-streaming

curl --location --request POST 'https://{WorkspaceId}.ap-southeast-1.maas.aliyuncs.com/api/v1/services/aigc/multimodal-generation/generation' \
     --header "Authorization: Bearer $DASHSCOPE_API_KEY" \
     --header "Content-Type: application/json" \
     --header "X-DashScope-SSE: disable" \
     --data @- <<'JSON'
{
    "model": "fun-asr-flash-2026-06-15",
    "input": {
        "messages": [
            {
                "role": "user",
                "content": [
                    {
                        "type": "input_text",
                        "text": "Hello"
                    }
                ]
            },
            {
                "role": "assistant",
                "content": [
                    {
                        "type": "text",
                        "text": "Hello, I'm Qwen. How can I help you?"
                    }
                ]
            },
            {
                "role": "user",
                "content": [
                    {
                        "type": "input_audio",
                        "input_audio": {
                            "data": "{YOUR_AUDIO_URL}"
                        }
                    }
                ]
            }
        ]
    },
    "parameters": {
        "format": "wav",
        "sample_rate": "16000"
    }
}
JSON

With context - streaming

curl --location --request POST 'https://{WorkspaceId}.ap-southeast-1.maas.aliyuncs.com/api/v1/services/aigc/multimodal-generation/generation' \
     --header "Authorization: Bearer $DASHSCOPE_API_KEY" \
     --header "Content-Type: application/json" \
     --header "X-DashScope-SSE: enable" \
     --data @- <<'JSON'
{
    "model": "fun-asr-flash-2026-06-15",
    "input": {
        "messages": [
            {
                "role": "user",
                "content": [
                    {
                        "type": "input_text",
                        "text": "Hello"
                    }
                ]
            },
            {
                "role": "assistant",
                "content": [
                    {
                        "type": "text",
                        "text": "Hello, I'm Qwen. How can I help you?"
                    }
                ]
            },
            {
                "role": "user",
                "content": [
                    {
                        "type": "input_audio",
                        "input_audio": {
                            "data": "{YOUR_AUDIO_URL}"
                        }
                    }
                ]
            }
        ]
    },
    "parameters": {
        "format": "wav",
        "sample_rate": "16000"
    }
}
JSON

Base64

You can pass Base64-encoded data (Data URL) in the format data:<mediatype>;base64,<data>.

  • <mediatype>: The MIME type.

    The value depends on the audio format. For example:

    • WAV: audio/wav
    • MP3: audio/mpeg
  • <data>: The Base64-encoded string of the audio.

    Base64 encoding increases the data size. For audio file size and duration limits, see Audio specifications.

  • Example: data:audio/wav;base64,SUQzBAAAAAAAI1RTU0UAAAAPAAADTGF2ZjU4LjI5LjEwMAAAAAAAAAAAAAAA//PAxABQ/BXRbMPe4IQAhl9

    import base64, pathlib
    
    # Replace with the path to your own audio file and make sure it meets the audio requirements
    file_path = pathlib.Path("{YOUR_AUDIO_FILE}")
    base64_str = base64.b64encode(file_path.read_bytes()).decode()
    data_uri = f"data:audio/mpeg;base64,{base64_str}"
    
    import java.nio.file.*;
          import java.util.Base64;
    
          public class Main {
              /**
               * Replace with the path to your own audio file and make sure it meets the audio requirements
               */
              public static String toDataUrl(String filePath) throws Exception {
                  byte[] bytes = Files.readAllBytes(Paths.get(filePath));
                  String encoded = Base64.getEncoder().encodeToString(bytes);
                  return "data:audio/mpeg;base64," + encoded;
              }
    
              public static void main(String[] args) throws Exception {
                  System.out.println(toDataUrl("{YOUR_AUDIO_FILE}"));
              }
          }
    
import base64, pathlib
import os
import requests

# Replace with the path to your own audio file and make sure it meets the audio requirements
file_path = pathlib.Path("{YOUR_AUDIO_FILE}")
base64_str = base64.b64encode(file_path.read_bytes()).decode()
data_uri = f"data:audio/wav;base64,{base64_str}"

# Replace "{WorkspaceId}" with your actual workspace ID
url = "https://{WorkspaceId}.ap-southeast-1.maas.aliyuncs.com/api/v1/services/aigc/multimodal-generation/generation"

headers = {
    "Authorization": f"Bearer {os.environ['DASHSCOPE_API_KEY']}",
    "Content-Type": "application/json",
    "X-DashScope-SSE": "disable",
}

payload = {
    "model": "fun-asr-flash-2026-06-15",
    "input": {
        "messages": [
            {
                "role": "user",
                "content": [
                    {
                        "type": "input_audio",
                        "input_audio": {
                            "data": data_uri,
                        },
                    }
                ],
            }
        ]
    },
    "parameters": {
        "format": "wav",
        "sample_rate": "16000",
    },
}

response = requests.post(url, headers=headers, json=payload)
print(response.status_code)
print(response.json())

Response body

request_idstring

The unique identifier of this request.

outputobject

The output result.

Properties

textstring

The full recognized text accumulated so far.

sentenceobject

The details of the current sentence.

Properties

sentence_idinteger

The sentence number, starting from 1.

sentence_endboolean

Whether this is the final result for the sentence. true indicates that recognition of the sentence is complete.

begin_timeinteger

The start time of the sentence, in milliseconds.

end_timeinteger

The end time of the sentence, in milliseconds. Returned only when sentence_end is true.

textstring

The recognized text of the current sentence.

channel_idinteger

The channel number, starting from 0.

wordsarray

The list of word-level timestamps.

Properties

textstring

The word text.

begin_timeinteger

The start time of the word, in milliseconds.

end_timeinteger

The end time of the word, in milliseconds.

punctuationstring

The punctuation mark after the word. An empty string when there is no punctuation.

fixedboolean

Whether the word is stabilized. false indicates that the word's timestamp may be adjusted in subsequent events.

usageobject

The usage information. Returned only when sentence_end is true.

Properties

durationinteger

The processed audio duration, in seconds.

Non-streaming

{
    "output": {
        "sentence": {
            "begin_time": 760,
            "channel_id": 0,
            "end_time": 3800,
            "sentence_end": true,
            "sentence_id": 1,
            "text": "Hello World, this is Alibaba Speech Lab.",
            "words": [
                {"begin_time": 760, "end_time": 1040, "fixed": true, "punctuation": "", "text": "Hello"},
                {"begin_time": 1040, "end_time": 1240, "fixed": true, "punctuation": ",", "text": " World"},
                {"begin_time": 1360, "end_time": 1880, "fixed": true, "punctuation": "", "text": "this is"},
                {"begin_time": 1880, "end_time": 2520, "fixed": true, "punctuation": "", "text": "Alibaba"},
                {"begin_time": 2520, "end_time": 2840, "fixed": true, "punctuation": "", "text": "Speech"},
                {"begin_time": 2840, "end_time": 3800, "fixed": true, "punctuation": ".", "text": "Lab"}
            ]
        },
        "text": "Hello World, this is Alibaba Speech Lab."
    },
    "usage": {
        "duration": 4
    },
    "request_id": "40e0734d-096f-9ae3-86c1-a8c013287561"
}

Streaming

The SSE streaming response uses the following event format:

id:{sequence_number}
      event:result
      :HTTP_STATUS/200
      data:{JSON_data}

Example response:

id:1
event:result
:HTTP_STATUS/200
data:{"output":{"sentence":{"sentence_id":1,"sentence_end":true,"end_time":3800,"words":[{"end_time":1040,"punctuation":"","begin_time":760,"fixed":true,"text":"Hello"},{"end_time":1240,"punctuation":",","begin_time":1040,"fixed":true,"text":" World"},{"end_time":1880,"punctuation":"","begin_time":1360,"fixed":true,"text":"this is"},{"end_time":2520,"punctuation":"","begin_time":1880,"fixed":true,"text":"Alibaba"},{"end_time":2840,"punctuation":"","begin_time":2520,"fixed":true,"text":"Speech"},{"end_time":3800,"punctuation":".","begin_time":2840,"fixed":true,"text":"Lab"}],"begin_time":760,"text":"Hello World, this is Alibaba Speech Lab.","channel_id":0},"text":"Hello World, this is Alibaba Speech Lab."},"usage":{"duration":4},"request_id":"fc1582e4-935c-9fc2-a482-a98bf43daa69"}

SSE streaming result processing logic

In streaming mode, the client needs to handle the following:

  1. For each SSE event received, parse the JSON in the data field.
  2. Use output.sentence.sentence_end to determine whether the current sentence has ended. When it is true, recognition is complete, the word-level timestamps are stabilized, and the result can be used as final. When it is false, recognition is still in progress, and text and timestamps may be updated in subsequent events.
  3. The usage information is returned only in sentence-end events and includes the processed audio duration.