Live streaming ASR garbled text detection

Service activation and resource plan purchase

Before you use the service, confirm that it is activated. After you activate the service, you must purchase a resource plan.

• Activate service: Activation page

• Purchase resource plan: Purchase page

Service invocation and debugging

For more information about model invocation, see Model Invocation.

For more information about SDK examples, see SDK Examples.

Debug

Configure access credentials using environment variables

1. Notes:

   1. An AccessKey pair for an Alibaba Cloud account grants full access to all APIs. This poses a high security threat. We recommend that you create and use a Resource Access Management (RAM) user for API access or daily operations and maintenance (O&M). To create a RAM user, log on to the RAM console.

   2. Do not hard-code your AccessKey ID and AccessKey secret in your code to prevent security threats. Instead, configure environment variables to store and access your AccessKey pair.

2. Configure for Linux and macOS

   export NLP_AK_ENV=<access_key_id>
   export NLP_SK_ENV=<access_key_secret>

   Replace <access_key_id> with your AccessKey ID and <access_key_secret> with your AccessKey secret. For more information, see Step 2: Obtain an AccessKey pair for an account.

3. Configure for Windows

   1. Create a file for environment variables. Add the NLP_AK_ENV and NLP_SK_ENV variables and set them to your AccessKey ID and AccessKey secret.

   2. Restart Windows.

Java code example

/**
 * An AccessKey pair for an Alibaba Cloud account has all API access permissions, which poses a high security threat. We strongly recommend that you create and use a RAM user for API access or daily O&M. To create a RAM user, log on to the RAM console.
 * This example shows how to store the AccessKey ID and AccessKey secret in environment variables. You can also store them in a configuration file as needed.
 * We strongly recommend that you do not hard-code the AccessKey ID and AccessKey secret in your code to prevent security threats.
 */
String accessKeyId = System.getenv("NLP_AK_ENV");
String accessKeySecret = System.getenv("NLP_SK_ENV");
DefaultProfile defaultProfile = DefaultProfile.getProfile("cn-hangzhou",accessKeyId,accessKeySecret);
IAcsClient client = new DefaultAcsClient(defaultProfile);
Map<String, Object> map = new HashMap<>();
map.put("input", "Give yourself an acceleration acceleration acceleration acceleration");
RunPreTrainServiceRequest request = new RunPreTrainServiceRequest();
request.setServiceName("E-Game-Language-Model");
request.setPredictContent(JSON.toJSONString(map));
RunPreTrainServiceResponse response = client.getAcsResponse(request);
System.out.println(response.getPredictResult());

Python code example

# Install dependencies
pip install aliyun-python-sdk-core
pip install aliyun-python-sdk-nlp-automl

# -*- coding: utf8 -*-
import json
import os

from aliyunsdkcore.client import AcsClient
from aliyunsdkcore.acs_exception.exceptions import ClientException
from aliyunsdkcore.acs_exception.exceptions import ServerException
from aliyunsdknlp_automl.request.v20191111 import RunPreTrainServiceRequest

# An AccessKey pair for an Alibaba Cloud account has all API access permissions, which poses a high security threat. We strongly recommend that you create and use a RAM user for API access or daily O&M. To create a RAM user, log on to the RAM console.
# This example shows how to store the AccessKey ID and AccessKey secret in environment variables. You can also store them in a configuration file as needed.
# We strongly recommend that you do not hard-code the AccessKey ID and AccessKey secret in your code to prevent security threats.
access_key_id = os.environ['NLP_AK_ENV']
access_key_secret = os.environ['NLP_SK_ENV']

# Initialize AcsClient instance
client = AcsClient(
  access_key_id,
  access_key_secret,
  "cn-hangzhou"
);
content ={"input": "Give yourself an acceleration acceleration acceleration acceleration"}
# Initialize a request and set parameters
request = RunPreTrainServiceRequest.RunPreTrainServiceRequest()
request.set_ServiceName('E-Game-Language-Model')
request.set_PredictContent(json.dumps(content))
# Print response
response = client.do_action_with_exception(request)
resp_obj = json.loads(response)
predict_result = json.loads(resp_obj['PredictResult'])
print(predict_result['result'])

PredictContent example

{
  "input": "Give yourself an acceleration acceleration acceleration acceleration"
}

PredictResult example

{
  "label": [
    {
      "preplexity ": 48.247,
      "is_readable": True
    }
  ]
}

Input parameters

Response parameters