快速入门:使用文本翻译 API 通过 C# 来检测文本语言Quickstart: Use the Translator Text API to detect text language using C#

本快速入门介绍如何使用 .NET Core、C# 7.1 或更高版本和文本翻译 REST API 来检测所提供文本的语言。In this quickstart, you'll learn how to detect the language of provided text using .NET Core, C# 7.1 or later, and the Translator Text REST API.

此快速入门需要包含文本翻译资源的 Azure 认知服务帐户This quickstart requires an Azure Cognitive Services account with a Translator Text resource. 如果没有帐户,可以使用试用帐户获取订阅密钥。If you don't have an account, you can use the trial to get a subscription key.

提示

如果你想一次看到所有代码,这个示例的源代码可以在 GitHub 上找到。If you'd like to see all the code at once, the source code for this sample is available on GitHub.

先决条件Prerequisites

创建 .NET Core 项目Create a .NET Core project

打开新的命令提示符(或终端会话)并运行以下命令:Open a new command prompt (or terminal session) and run these commands:

dotnet new console -o detect-sample
cd detect-sample

第一个命令执行两项操作。The first command does two things. 它创建新的 .NET 控制台应用程序,并创建名为 detect-sample 的目录。It creates a new .NET console application, and creates a directory named detect-sample. 第二个目录转到项目的目录。The second command changes to the directory for your project.

接下来需安装 Json.Net。Next, you'll need to install Json.Net. 在项目的目录中,运行以下命令:From your project's directory, run:

dotnet add package Newtonsoft.Json --version 11.0.2

选择 C# 语言版本Select the C# language version

本快速入门需要 C# 7.1 或更高版本。This quickstart requires C# 7.1 or later. 可以通过多种方式来更改项目的 C# 版本。There are a few ways to change the C# version for your project. 本指南将介绍如何调整 detect-sample.csproj 文件。In this guide, we'll show you how to adjust the detect-sample.csproj file. 如需所有可用选项,例如在 Visual Studio 中更改语言的选项,请参阅选择 C# 语言版本For all available options, such as changing the language in Visual Studio, see Select the C# language version.

打开项目,然后打开 detect-sample.csprojOpen your project, then open detect-sample.csproj. 确保将 LangVersion 设置为 7.1 或更高版本。Make sure that LangVersion is set to 7.1 or later. 如果没有用于语言版本的属性组,请添加以下行:If there isn't a property group for the language version, add these lines:

<PropertyGroup>
   <LangVersion>7.1</LangVersion>
</PropertyGroup>

将所需命名空间添加到项目Add required namespaces to your project

此前运行的 dotnet new console 命令创建了一个项目(包括 Program.cs)。The dotnet new console command that you ran earlier created a project, including Program.cs. 此文件是需放置应用程序代码的位置。This file is where you'll put your application code. 打开 Program.cs,替换现有的 using 语句。Open Program.cs, and replace the existing using statements. 这些语句可确保你有权访问生成并运行示例应用所需的所有类型。These statements ensure that you have access to all the types required to build and run the sample app.

using System;
using System.Net.Http;
using System.Text;
using System.Threading.Tasks;
// Install Newtonsoft.Json with NuGet
using Newtonsoft.Json;

为 JSON 响应创建类Create classes for the JSON response

接下来,我们将创建一个在反序列化由文本翻译 API 返回的 JSON 响应时使用的类。Next, we're going to create a class that's used when deserializing the JSON response returned by the Translator Text API.

/// <summary>
/// The C# classes that represents the JSON returned by the Translator Text API.
/// </summary>
public class DetectResult
{
    public string Language { get; set; }
    public float Score { get; set; }
    public bool IsTranslationSupported { get; set; }
    public bool IsTransliterationSupported { get; set; }
    public AltTranslations[] Alternatives { get; set; }
}
public class AltTranslations
{
    public string Language { get; set; }
    public float Score { get; set; }
    public bool IsTranslationSupported { get; set; }
    public bool IsTransliterationSupported { get; set; }
}

创建源文本语言检测函数Create a function to detect the source text's language

Program 类中创建名为 DetectTextRequest() 的函数。Within the Program class, create a function called DetectTextRequest(). 该类封装用于调用 Detect 资源的代码,并将结果输出到控制台。This class encapsulates the code used to call the Detect resource and prints the result to console.

static public async Task DetectTextRequest(string subscriptionKey, string host, string route, string inputText)
{
  /*
   * The code for your call to the translation service will be added to this
   * function in the next few sections.
   */
}

序列化检测请求Serialize the detect request

接下来需创建 JSON 对象并将其序列化,其中包含要进行语言检测的文本。Next, we need to create and serialize the JSON object that includes the text that will undergo language detection.

System.Object[] body = new System.Object[] { new { Text = inputText } };
var requestBody = JsonConvert.SerializeObject(body);

实例化客户端并发出请求Instantiate the client and make a request

以下行实例化 HttpClientHttpRequestMessageThese lines instantiate the HttpClient and the HttpRequestMessage:

using (var client = new HttpClient())
using (var request = new HttpRequestMessage())
{
  // In the next few sections you'll add code to construct the request.
}

构造请求并输出响应Construct the request and print the response

HttpRequestMessage 中,需执行以下操作:Inside the HttpRequestMessage you'll:

  • 声明 HTTP 方法Declare the HTTP method
  • 构造请求 URIConstruct the request URI
  • 插入请求正文(序列化的 JSON 对象)Insert the request body (serialized JSON object)
  • 添加必需的标头Add required headers
  • 发出异步请求Make an asynchronous request
  • 输出响应Print the response

HttpRequestMessage 添加以下代码:Add this code to the HttpRequestMessage:

// Build the request.
request.Method = HttpMethod.Post;
// Construct the URI and add headers.
request.RequestUri = new Uri(host + route);
request.Content = new StringContent(requestBody, Encoding.UTF8, "application/json");
request.Headers.Add("Ocp-Apim-Subscription-Key", subscriptionKey);
request.Headers.Add("Ocp-Apim-Subscription-Region", "your region");

// Send the request and get response.
HttpResponseMessage response = await client.SendAsync(request).ConfigureAwait(false);
// Read response as a string.
string result = await response.Content.ReadAsStringAsync();
// Deserialize the response using the classes created earlier.
DetectResult[] deserializedOutput = JsonConvert.DeserializeObject<DetectResult[]>(result);
// Iterate over the deserialized response.
foreach (DetectResult o in deserializedOutput)
{
    Console.WriteLine("The detected language is '{0}'. Confidence is: {1}.\nTranslation supported: {2}.\nTransliteration supported: {3}.\n",
        o.Language, o.Score, o.IsTranslationSupported, o.IsTransliterationSupported);
    // Create a counter
    int counter = 0;
    // Iterate over alternate translations.
    foreach (AltTranslations a in o.Alternatives)
    {
        counter++;
        Console.WriteLine("Alternative {0}", counter);
        Console.WriteLine("The detected language is '{0}'. Confidence is: {1}.\nTranslation supported: {2}.\nTransliteration supported: {3}.\n",
            a.Language, a.Score, a.IsTranslationSupported, a.IsTransliterationSupported);
    }
}

如果使用的是认知服务多服务订阅,则还必须在请求参数中包括 Ocp-Apim-Subscription-RegionIf you are using a Cognitive Services multi-service subscription, you must also include the Ocp-Apim-Subscription-Region in your request parameters. 详细了解如何使用多服务订阅进行身份验证Learn more about authenticating with the multi-service subscription.

将其放在一起Put it all together

最后一步是在 Main 函数中调用 DetectTextRequest()The last step is to call DetectTextRequest() in the Main function. 找到 static void Main(string[] args) 并将其替换为以下代码:Locate static void Main(string[] args) and replace it with this code:

static async Task Main(string[] args)
{
    // This is our main function.
    // Output languages are defined in the route.
    // For a complete list of options, see API reference.
    string subscriptionKey = "YOUR_TRANSLATOR_TEXT_KEY_GOES_HERE";
    string host = "https://api.translator.azure.cn";
    string route = "/detect?api-version=3.0";
    string breakSentenceText = @"How are you doing today? The weather is pretty pleasant. Have you been to the movies lately?";
    await DetectTextRequest(subscriptionKey, host, route, breakSentenceText);
}

运行示例应用Run the sample app

上述操作完成后,就可以运行示例应用了。That's it, you're ready to run your sample app. 从命令行(或终端会话)导航到项目目录,然后运行以下命令:From the command line (or terminal session), navigate to your project directory and run:

dotnet run

示例响应Sample response

运行示例后,应当会看到输出到终端的以下内容:After you run the sample, you should see the following printed to terminal:

备注

请在此语言列表中查找国家/地区缩写。Find the country/region abbreviation in this list of languages.

The detected language is 'en'. Confidence is: 1.
Translation supported: True.
Transliteration supported: False.

Alternative 1
The detected language is 'fil'. Confidence is: 0.82.
Translation supported: True.
Transliteration supported: False.

Alternative 2
The detected language is 'ro'. Confidence is: 1.
Translation supported: True.
Transliteration supported: False.

此消息是从原始 JSON 构建的,如下所示:This message is built from the raw JSON, which will look like this:

[  
    {  
        "language":"en",
        "score":1.0,
        "isTranslationSupported":true,
        "isTransliterationSupported":false,
        "alternatives":[  
            {  
                "language":"fil",
                "score":0.82,
                "isTranslationSupported":true,
                "isTransliterationSupported":false
            },
            {  
                "language":"ro",
                "score":1.0,
                "isTranslationSupported":true,
                "isTransliterationSupported":false
            }
        ]
    }
]

清理资源Clean up resources

请务必删除示例应用的源代码中的机密信息,例如订阅密钥。Make sure to remove any confidential information from your sample app's source code, like subscription keys.

后续步骤Next steps

查看 API 参考,了解使用文本翻译 API 可以执行的所有操作。Take a look at the API reference to understand everything you can do with the Translator Text API.

另请参阅See also