Pii - Detecting Personally Identifiable Information using Azure Cognitive Services

This article will look at detecting Person Identifiable Information (Pii) using Azure Cognitive Services. I have created a demo using .NET Maui Blazor has been created and the Github repo is here:
https://github.com/toreaurstadboss/PiiDetectionDemo

Person Identifiable Information (Pii) is desired to detect and also redact, that is using censorship or obscuring Pii to prepare documents for publication. The Pii feature in Azure Cognitive Services is a part of the Language resource service. A quickstart for using Pii is available here:
https://learn.microsoft.com/en-us/azure/ai-services/language-service/personally-identifiable-information/quickstart?pivots=programming-language-csharp

After creating the Language resource, look up the keys and endpoints for you service. Using Azure CLI inside Cloud shell, you can enter this command to find the keys, in Azure many services has got two keys you can exchange with new keys through regeneration:

az cognitiveservices account keys list --resource-group SomeAzureResourceGroup --name SomeAccountAzureCognitiveServices
This is how you can query after endpoint of language resource using Azure CLI : az cognitiveservices account show --query "properties.endpoint" --resource-group SomeAzureResourceGroup --name SomeAccountAzureCognitiveServices
Next, the demo of this article. Connecting to the Pii Removal Text Analytics is possible using this Nuget package (REST calls can also be done manually): - Azure.AI.TextAnalytics version 5.3.0 Here is the other Nugets of my Demo included from the .csproj file :

PiiDetectionDemo.csproj

  <ItemGroup>
        <PackageReference Include="Azure.AI.TextAnalytics" Version="5.3.0" />
        <PackageReference Include="Microsoft.Maui.Controls" Version="$(MauiVersion)" />
        <PackageReference Include="Microsoft.Maui.Controls.Compatibility" Version="$(MauiVersion)" />
        <PackageReference Include="Microsoft.AspNetCore.Components.WebView.Maui" Version="$(MauiVersion)" />
        <PackageReference Include="Microsoft.Extensions.Logging.Debug" Version="8.0.0" />
    </ItemGroup>

A service using this Pii removal feature is simply making use of a TextAnalyticsClient and method RecognizePiiEntitiesAsync.

PiiRemovalTextClientService.cs IPiiRemovalTextClientService.cs

using Azure;
using Azure.AI.TextAnalytics;

namespace PiiDetectionDemo.Util
{
    public interface IPiiRemovalTextAnalyticsClientService
    {
        Task<Response<PiiEntityCollection>> RecognizePiiEntitiesAsync(string? document, string? language);
    }
}


namespace PiiDetectionDemo.Util
{
    public class PiiRemovalTextAnalyticsClientService : IPiiRemovalTextAnalyticsClientService
    {

        private TextAnalyticsClient _client;

        public PiiRemovalTextAnalyticsClientService()
        {
            var azureEndpoint = Environment.GetEnvironmentVariable("AZURE_COGNITIVE_SERVICE_ENDPOINT");
            var azureKey = Environment.GetEnvironmentVariable("AZURE_COGNITIVE_SERVICE_KEY");

            if (string.IsNullOrWhiteSpace(azureEndpoint))
            {
                throw new ArgumentNullException(nameof(azureEndpoint), "Missing system environment variable: AZURE_COGNITIVE_SERVICE_ENDPOINT");
            }
            if (string.IsNullOrWhiteSpace(azureKey))
            {
                throw new ArgumentNullException(nameof(azureKey), "Missing system environment variable: AZURE_COGNITIVE_SERVICE_KEY");
            }

            _client = new TextAnalyticsClient(new Uri(azureEndpoint), new AzureKeyCredential(azureKey));
        }

        public async Task<Response<PiiEntityCollection>> RecognizePiiEntitiesAsync(string? document, string? language)
        {
            var piiEntities = await _client.RecognizePiiEntitiesAsync(document, language);
            return piiEntities;
        }

    }
}

The UI codebehind of the razor component page showing the UI looks like this:

Home.razor.cs

using Azure;
using Microsoft.AspNetCore.Components;
using PiiDetectionDemo.Models;
using PiiDetectionDemo.Util;
using System;
using System.Collections.Generic;
using System.Linq;
using System.Text;
using System.Threading.Tasks;

namespace PiiDetectionDemo.Components.Pages
{
    public partial class Home
    {

        private IndexModel Model = new();
        private bool isProcessing = false;
        private bool isSearchPerformed = false;

        private async Task Submit()
        {
            isSearchPerformed = false;
            isProcessing = true;
            try
            {
                var response = await _piiRemovalTextAnalyticsClientService.RecognizePiiEntitiesAsync(Model.InputText, null);
                Model.RedactedText = response?.Value?.RedactedText;
                Model.UpdateHtmlRedactedText();
                Model.AnalysisResult = response?.Value;
                StateHasChanged();
            }
            catch (Exception ex)
            {
                await Console.Out.WriteLineAsync(ex.ToString());
            }
            isProcessing = false;
            isSearchPerformed = true;
        }

        private void removeWhitespace(ChangeEventArgs args)
        {
            Model.InputText = args.Value?.ToString()?.CleanupAllWhiteSpace();
            StateHasChanged();
        }



    }
}

To get the redacted or censored text void of any Pii that the Pii detection feature was able to detect, access the Value of type Azure.AI.TextAnalytics.PiiEntityCollection. Inside this object, the string RedactedText contains the censored / redacted text. The IndexModel looks like this :

using Azure.AI.TextAnalytics;
using Microsoft.AspNetCore.Components;
using PiiDetectionDemo.Util;
using System.ComponentModel.DataAnnotations;
using System.Text;

namespace PiiDetectionDemo.Models
{

    public class IndexModel
    {

        [Required]
        public string? InputText { get; set; }

        public string? RedactedText { get; set; }

        public string? HtmlRedactedText { get; set; }

        public MarkupString HtmlRedactedTextMarkupString { get; set; }

        public void UpdateHtmlRedactedText()
        {
            var sb = new StringBuilder(RedactedText);
            if (AnalysisResult != null && RedactedText != null)
            {
                foreach (var piiEntity in AnalysisResult.OrderByDescending(a => a.Offset))
                {
                    sb.Insert(piiEntity.Offset + piiEntity.Length, "</b></span>");
                    sb.Insert(piiEntity.Offset, $"<span style='background-color:lightgray;border:1px solid black;corner-radius:2px; color:{GetBackgroundColor(piiEntity)}' title='{piiEntity.Category}: {piiEntity.SubCategory} Confidence: {piiEntity.ConfidenceScore} Redacted Text: {piiEntity.Text}'><b>");
                }
            }
            HtmlRedactedText = sb.ToString()?.CleanupAllWhiteSpace();    
            HtmlRedactedTextMarkupString = new MarkupString(HtmlRedactedText ?? string.Empty);
        }

        private string GetBackgroundColor(PiiEntity piiEntity)
        {
            if (piiEntity.Category == PiiEntityCategory.PhoneNumber)
            {
                return "yellow";
            }
            if (piiEntity.Category == PiiEntityCategory.Organization)
            {
                return "orange";
            }
            if (piiEntity.Category == PiiEntityCategory.Address)
            {
                return "green";
            }
            return "gray";                   
        }

        public long ExecutionTime { get; set; }
        public PiiEntityCollection? AnalysisResult { get; set; }

    }
}

Frontend UI looks like this: Home.razor

@page "/"
@using PiiDetectionDemo.Util

@inject IPiiRemovalTextAnalyticsClientService _piiRemovalTextAnalyticsClientService;

<h3>Azure HealthCare Text Analysis - Pii detection feature - Azure Cognitive Services</h3>

<em>Pii = Person identifiable information</em>

<EditForm Model="@Model" OnValidSubmit="@Submit">
    <DataAnnotationsValidator />
    <ValidationSummary />

    <div class="form-group row">
        <label><strong>Text input</strong></label>
        <InputTextArea @oninput="removeWhitespace" class="overflow-scroll" style="max-height:500px;max-width:900px;font-size: 10pt;font-family:Verdana, Geneva, Tahoma, sans-serif" @bind-Value="@Model.InputText" rows="5" />
    </div>

    <div class="form-group row">
        <div class="col">
            <br />
            <button class="btn btn-outline-primary" type="submit">Run</button>
        </div>
        <div class="col">
        </div>
        <div class="col">
        </div>
    </div>

    <br />

    @if (isProcessing)
    {

        <div class="progress" style="max-width: 90%">
            <div class="progress-bar progress-bar-striped progress-bar-animated"
                 style="width: 100%; background-color: green">
                Retrieving result from Azure Text Analysis Pii detection feature. Processing..
            </div>
        </div>
        <br />

    }

    <div class="form-group row">
        <label><strong>Analysis result</strong></label>

        @if (isSearchPerformed)
        {
            <br />
            <b>Execution time took: @Model.ExecutionTime ms (milliseconds)</b>

            <br />
            <br />

            <b>Redacted text (Pii removed)</b>
            <br />

            <div class="form-group row">
               <label><strong>Categorized Pii redacted text</strong></label>
               <div>
               @Model.HtmlRedactedTextMarkupString
               </div>
            </div>

            <br />
            <br />

            <table class="table table-striped table-dark table-hover">
                <thead>
                <th>Pii text</th>
                <th>Category</th>
                <th>SubCategory</th>
                <th>Offset</th>
                <th>Length</th>
                <th>ConfidenceScore</th>
                </thead>
                <tbody>
                    @if (Model.AnalysisResult != null) {
                        @foreach (var entity in Model.AnalysisResult)
                        {
                            <tr>
                                <td>@entity.Text</td>
                                <td>@entity.Category.ToString()</td>
                                <td>@entity.SubCategory</td>
                                <td>@entity.Offset</td>
                                <td>@entity.Length</td>
                                <td>@entity.ConfidenceScore</td>                                        
                            </tr>
                        }
                    }
                </tbody>
            </table>

        }
    </div>

</EditForm>

The Demo uses Bootstrap 5 to build up a HTML table styled and showing the Azure.AI.TextAnalytics.PiiEntity properties.

Using synthesized speech in Azure Cognitive Services - Text to Speech

I have extended my demo repo with Multi-Lingual translator to include AI realistic speech. The Github repo for the demo is available here :

https://github.com/toreaurstadboss/MultiLingual.Translator

The speech synthesis service of Azure AI is accessed via a REST service. You can actually test it out first in Postman, retrieving an access token via an endpoint for this and then calling the text to speech endpoint using the access token as a bearer token. To get the demo working, you have to inside the Azure Portal create the necessary resources / services. This article is focused on speech service. Important, if you want to test out the DEMO yourself, remember to put the keys into environment variables so they are not exposed via source control. To get started with speech synthesis in Azure Cognitive Services, add a Speech Service resource via the Azure Portal. https://learn.microsoft.com/en-us/azure/ai-services/speech-service/overview We also need to add audio capability to our demo, which is a .NET MAUI Blazor app. The Nuget package used is the following : MultiLingual.Translator.csproj

<ItemGroup>
	<PackageReference Include="Plugin.Maui.Audio" Version="2.0.0" />
</ItemGroup>

This Nuget package's website is here: https://github.com/jfversluis/Plugin.Maui.Audio The MauiProgram.cs looks like the following, make note of AudioManager.Current, which is registered as a singleton. MauiProgram.cs

using Microsoft.Extensions.Configuration;
using MultiLingual.Translator.Lib;
using Plugin.Maui.Audio;

namespace MultiLingual.Translator;

public static class MauiProgram
{
	public static MauiApp CreateMauiApp()
	{
		var builder = MauiApp.CreateBuilder();
		builder
			.UseMauiApp<App>()
			.ConfigureFonts(fonts =>
			{
				fonts.AddFont("OpenSans-Regular.ttf", "OpenSansRegular");
			});

		builder.Services.AddMauiBlazorWebView();
		#if DEBUG
		builder.Services.AddBlazorWebViewDeveloperTools();
#endif

		builder.Services.AddSingleton(AudioManager.Current);
		builder.Services.AddTransient<MainPage>();

		builder.Services.AddScoped<IDetectLanguageUtil, DetectLanguageUtil>();
        builder.Services.AddScoped<ITranslateUtil, TranslateUtil>();
		builder.Services.AddScoped<ITextToSpeechUtil, TextToSpeechUtil>();

		var config = new ConfigurationBuilder().AddJsonFile("appsettings.json").Build();
		builder.Configuration.AddConfiguration(config);

        return builder.Build();
	}
}

Next up, let's look at the TextToSpeechUtil. This class, which is a service that does two things against the REST API of the text-to-speech Azure Cognitive AI service :

1. Fetch an access token
2. Synthesize text to speech

TextToSpeechUtil.cs

using Microsoft.Extensions.Configuration;
using MultiLingual.Translator.Lib.Models;
using System.Security;
using System.Text;

namespace MultiLingual.Translator.Lib
{
    public class TextToSpeechUtil : ITextToSpeechUtil
    {

        public TextToSpeechUtil(IConfiguration configuration)
        {
            _configuration = configuration;
        }

        public async Task<TextToSpeechResult> GetSpeechFromText(string text, string language, TextToSpeechLanguage[] actorVoices, string? preferredVoiceActorId)
        {
            var result = new TextToSpeechResult();

            result.Transcript = GetSpeechTextXml(text, language, actorVoices, preferredVoiceActorId, result);
            result.ContentType = _configuration[TextToSpeechSpeechContentType];
            result.OutputFormat = _configuration[TextToSpeechSpeechXMicrosoftOutputFormat];
            result.UserAgent = _configuration[TextToSpeechSpeechUserAgent];
            result.AvailableVoiceActorIds = ResolveAvailableActorVoiceIds(language, actorVoices);
            result.LanguageCode = language;

            string? token = await GetUpdatedToken();

            HttpClient httpClient = GetTextToSpeechWebClient(token);

            string ttsEndpointUrl = _configuration[TextToSpeechSpeechEndpoint];
            var response = await httpClient.PostAsync(ttsEndpointUrl, new StringContent(result.Transcript, Encoding.UTF8, result.ContentType));

            using (var memStream = new MemoryStream()) {
                var responseStream = await response.Content.ReadAsStreamAsync();
                responseStream.CopyTo(memStream);
                result.VoiceData = memStream.ToArray();
            }

            return result;
        }

        private async Task<string?> GetUpdatedToken()
        {
            string? token = _token?.ToNormalString();
            if (_lastTimeTokenFetched == null || DateTime.Now.Subtract(_lastTimeTokenFetched.Value).Minutes > 8)
            {
                token = await GetIssuedToken();
            }

            return token;
        }

        private HttpClient GetTextToSpeechWebClient(string? token)
        {
            var httpClient = new HttpClient();
            httpClient.DefaultRequestHeaders.Authorization = new System.Net.Http.Headers.AuthenticationHeaderValue("Bearer", token);
            httpClient.DefaultRequestHeaders.Add("X-Microsoft-OutputFormat", _configuration[TextToSpeechSpeechXMicrosoftOutputFormat]);
            httpClient.DefaultRequestHeaders.Add("User-Agent", _configuration[TextToSpeechSpeechUserAgent]);
            return httpClient;
        }
       
        private string GetSpeechTextXml(string text, string language, TextToSpeechLanguage[] actorVoices, string? preferredVoiceActorId, TextToSpeechResult result)
        {
            result.VoiceActorId = ResolveVoiceActorId(language, preferredVoiceActorId, actorVoices);
            string speechXml = $@"
            <speak version='1.0' xml:lang='en-US'>
                <voice xml:lang='en-US' xml:gender='Male' name='Microsoft Server Speech Text to Speech Voice {result.VoiceActorId}'>
                    <prosody rate='1'>{text}</prosody>
                </voice>
            </speak>";
            return speechXml;               
        }

        private List<string> ResolveAvailableActorVoiceIds(string language, TextToSpeechLanguage[] actorVoices)
        {
            if (actorVoices?.Any() == true)
            {
                var voiceActorIds = actorVoices.Where(v => v.LanguageKey == language || v.LanguageKey.Split("-")[0] == language).SelectMany(v => v.VoiceActors).Select(v => v.VoiceId).ToList();
                return voiceActorIds;
            }
            return new List<string>();
        }

        private string ResolveVoiceActorId(string language, string? preferredVoiceActorId, TextToSpeechLanguage[] actorVoices)
        {
            string actorVoiceId = "(en-AU, NatashaNeural)"; //default to a select voice actor id 
            if (actorVoices?.Any() == true)
            {
                var voiceActorsForLanguage = actorVoices.Where(v => v.LanguageKey == language || v.LanguageKey.Split("-")[0] == language).SelectMany(v => v.VoiceActors).Select(v => v.VoiceId).ToList();
                if (voiceActorsForLanguage != null)
                {
                    if (voiceActorsForLanguage.Any() == true)
                    {
                        var resolvedPreferredVoiceActorId = voiceActorsForLanguage.FirstOrDefault(v => v == preferredVoiceActorId);
                        if (!string.IsNullOrWhiteSpace(resolvedPreferredVoiceActorId))
                        {
                            return resolvedPreferredVoiceActorId!;
                        }
                        actorVoiceId = voiceActorsForLanguage.First();
                    }
                }
            }
            return actorVoiceId;
        }

        private async Task<string> GetIssuedToken()
        {
            var httpClient = new HttpClient();
            string? textToSpeechSubscriptionKey = Environment.GetEnvironmentVariable("AZURE_TEXT_SPEECH_SUBSCRIPTION_KEY", EnvironmentVariableTarget.Machine);
            httpClient.DefaultRequestHeaders.Add(OcpApiSubscriptionKeyHeaderName, textToSpeechSubscriptionKey);
            string tokenEndpointUrl = _configuration[TextToSpeechIssueTokenEndpoint];
            var response = await httpClient.PostAsync(tokenEndpointUrl, new StringContent("{}"));
            _token = (await response.Content.ReadAsStringAsync()).ToSecureString();
            _lastTimeTokenFetched = DateTime.Now;
            return _token.ToNormalString();
        }

        private const string OcpApiSubscriptionKeyHeaderName = "Ocp-Apim-Subscription-Key";
        private const string TextToSpeechIssueTokenEndpoint = "TextToSpeechIssueTokenEndpoint";
        private const string TextToSpeechSpeechEndpoint = "TextToSpeechSpeechEndpoint";        
        private const string TextToSpeechSpeechContentType = "TextToSpeechSpeechContentType";
        private const string TextToSpeechSpeechUserAgent = "TextToSpeechSpeechUserAgent";
        private const string TextToSpeechSpeechXMicrosoftOutputFormat = "TextToSpeechSpeechXMicrosoftOutputFormat";

        private readonly IConfiguration _configuration;

        private DateTime? _lastTimeTokenFetched = null;
        private SecureString _token = null;

    }
}

Let's look at the appsettings.json file. The Ocp-Apim-Subscription-Key is put into environment variable, this is a secret key you do not want to expose to avoid leaking a key an running costs for usage of service. Appsettings.json

{
  "TextToSpeechIssueTokenEndpoint": "https://norwayeast.api.cognitive.microsoft.com/sts/v1.0/issuetoken",
  "TextToSpeechSpeechEndpoint": "https://norwayeast.tts.speech.microsoft.com/cognitiveservices/v1",
  "TextToSpeechSpeechContentType": "application/ssml+xml",
  "TextToSpeechSpeechUserAgent": "MultiLingualTranslatorBlazorDemo",
  "TextToSpeechSpeechXMicrosoftOutputFormat": "audio-24khz-48kbitrate-mono-mp3"
}

Next up, I have gathered all the voice actor ids for languages in Azure Cognitive Services which have voice actor ids. Thesee are all the most known languages in the list of Azure about 150 supported languages, see the following json for an overview of voice actor ids. For example, Norwegian language got three voice actors that are synthesized neural net trained AI voice actors for realistic speech synthesis.

       [
  {
    "LanguageKey": "af-ZA",
    "VoiceActors": [
      {
        "IsFemale": true,
        "VoiceActor": "af-ZA-AdriNeural2",
        "VoiceId": "(af-ZA, AdriNeural2)"
      },
      {
        "IsFemale": false,
        "VoiceActor": "af-ZA-WillemNeural2",
        "VoiceId": "(af-ZA, WillemNeural2)"
      }
    ]
  },
  {
    "LanguageKey": "am-ET",
    "VoiceActors": [
      {
        "IsFemale": true,
        "VoiceActor": "am-ET-MekdesNeural2",
        "VoiceId": "(am-ET, MekdesNeural2)"
      },
      {
        "IsFemale": false,
        "VoiceActor": "am-ET-AmehaNeural2",
        "VoiceId": "(am-ET, AmehaNeural2)"
      }
    ]
  },
  {
    "LanguageKey": "ar-AE",
    "VoiceActors": [
      {
        "IsFemale": true,
        "VoiceActor": "ar-AE-FatimaNeural",
        "VoiceId": "(ar-AE, FatimaNeural)"
      },
      {
        "IsFemale": false,
        "VoiceActor": "ar-AE-HamdanNeural",
        "VoiceId": "(ar-AE, HamdanNeural)"
      }
    ]
  },
  {
    "LanguageKey": "ar-BH",
    "VoiceActors": [
      {
        "IsFemale": true,
        "VoiceActor": "ar-BH-LailaNeural",
        "VoiceId": "(ar-BH, LailaNeural)"
      },
      {
        "IsFemale": false,
        "VoiceActor": "ar-BH-AliNeural",
        "VoiceId": "(ar-BH, AliNeural)"
      }
    ]
  },
  {
    "LanguageKey": "ar-DZ",
    "VoiceActors": [
      {
        "IsFemale": true,
        "VoiceActor": "ar-DZ-AminaNeural",
        "VoiceId": "(ar-DZ, AminaNeural)"
      },
      {
        "IsFemale": false,
        "VoiceActor": "ar-DZ-IsmaelNeural",
        "VoiceId": "(ar-DZ, IsmaelNeural)"
      }
    ]
  },
  {
    "LanguageKey": "ar-EG",
    "VoiceActors": [
      {
        "IsFemale": true,
        "VoiceActor": "ar-EG-SalmaNeural",
        "VoiceId": "(ar-EG, SalmaNeural)"
      },
      {
        "IsFemale": false,
        "VoiceActor": "ar-EG-ShakirNeural",
        "VoiceId": "(ar-EG, ShakirNeural)"
      }
    ]
  },
  {
    "LanguageKey": "ar-IQ",
    "VoiceActors": [
      {
        "IsFemale": true,
        "VoiceActor": "ar-IQ-RanaNeural",
        "VoiceId": "(ar-IQ, RanaNeural)"
      },
      {
        "IsFemale": false,
        "VoiceActor": "ar-IQ-BasselNeural",
        "VoiceId": "(ar-IQ, BasselNeural)"
      }
    ]
  },
  {
    "LanguageKey": "ar-JO",
    "VoiceActors": [
      {
        "IsFemale": true,
        "VoiceActor": "ar-JO-SanaNeural",
        "VoiceId": "(ar-JO, SanaNeural)"
      },
      {
        "IsFemale": false,
        "VoiceActor": "ar-JO-TaimNeural",
        "VoiceId": "(ar-JO, TaimNeural)"
      }
    ]
  },
  {
    "LanguageKey": "ar-KW",
    "VoiceActors": [
      {
        "IsFemale": true,
        "VoiceActor": "ar-KW-NouraNeural",
        "VoiceId": "(ar-KW, NouraNeural)"
      },
      {
        "IsFemale": false,
        "VoiceActor": "ar-KW-FahedNeural",
        "VoiceId": "(ar-KW, FahedNeural)"
      }
    ]
  },
  {
    "LanguageKey": "ar-LB",
    "VoiceActors": [
      {
        "IsFemale": true,
        "VoiceActor": "ar-LB-LaylaNeural",
        "VoiceId": "(ar-LB, LaylaNeural)"
      },
      {
        "IsFemale": false,
        "VoiceActor": "ar-LB-RamiNeural",
        "VoiceId": "(ar-LB, RamiNeural)"
      }
    ]
  },
  {
    "LanguageKey": "ar-LY",
    "VoiceActors": [
      {
        "IsFemale": true,
        "VoiceActor": "ar-LY-ImanNeural",
        "VoiceId": "(ar-LY, ImanNeural)"
      },
      {
        "IsFemale": false,
        "VoiceActor": "ar-LY-OmarNeural",
        "VoiceId": "(ar-LY, OmarNeural)"
      }
    ]
  },
  {
    "LanguageKey": "ar-MA",
    "VoiceActors": [
      {
        "IsFemale": true,
        "VoiceActor": "ar-MA-MounaNeural",
        "VoiceId": "(ar-MA, MounaNeural)"
      },
      {
        "IsFemale": false,
        "VoiceActor": "ar-MA-JamalNeural",
        "VoiceId": "(ar-MA, JamalNeural)"
      }
    ]
  },
  {
    "LanguageKey": "ar-OM",
    "VoiceActors": [
      {
        "IsFemale": true,
        "VoiceActor": "ar-OM-AyshaNeural",
        "VoiceId": "(ar-OM, AyshaNeural)"
      },
      {
        "IsFemale": false,
        "VoiceActor": "ar-OM-AbdullahNeural",
        "VoiceId": "(ar-OM, AbdullahNeural)"
      }
    ]
  },
  {
    "LanguageKey": "ar-QA",
    "VoiceActors": [
      {
        "IsFemale": true,
        "VoiceActor": "ar-QA-AmalNeural",
        "VoiceId": "(ar-QA, AmalNeural)"
      },
      {
        "IsFemale": false,
        "VoiceActor": "ar-QA-MoazNeural",
        "VoiceId": "(ar-QA, MoazNeural)"
      }
    ]
  },
  {
    "LanguageKey": "ar-SA",
    "VoiceActors": [
      {
        "IsFemale": true,
        "VoiceActor": "ar-SA-ZariyahNeural",
        "VoiceId": "(ar-SA, ZariyahNeural)"
      },
      {
        "IsFemale": false,
        "VoiceActor": "ar-SA-HamedNeural",
        "VoiceId": "(ar-SA, HamedNeural)"
      }
    ]
  },
  {
    "LanguageKey": "ar-SY",
    "VoiceActors": [
      {
        "IsFemale": true,
        "VoiceActor": "ar-SY-AmanyNeural",
        "VoiceId": "(ar-SY, AmanyNeural)"
      },
      {
        "IsFemale": false,
        "VoiceActor": "ar-SY-LaithNeural",
        "VoiceId": "(ar-SY, LaithNeural)"
      }
    ]
  },
  {
    "LanguageKey": "ar-TN",
    "VoiceActors": [
      {
        "IsFemale": true,
        "VoiceActor": "ar-TN-ReemNeural",
        "VoiceId": "(ar-TN, ReemNeural)"
      },
      {
        "IsFemale": false,
        "VoiceActor": "ar-TN-HediNeural",
        "VoiceId": "(ar-TN, HediNeural)"
      }
    ]
  },
  {
    "LanguageKey": "ar-YE",
    "VoiceActors": [
      {
        "IsFemale": true,
        "VoiceActor": "ar-YE-MaryamNeural",
        "VoiceId": "(ar-YE, MaryamNeural)"
      },
      {
        "IsFemale": false,
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      {
        "IsFemale": true,
        "VoiceActor": "vi-VN-HoaiMyNeural",
        "VoiceId": "(vi-VN, HoaiMyNeural)"
      },
      {
        "IsFemale": false,
        "VoiceActor": "vi-VN-NamMinhNeural",
        "VoiceId": "(vi-VN, NamMinhNeural)"
      }
    ]
  },
  {
    "LanguageKey": "wuu-CN",
    "VoiceActors": [
      {
        "IsFemale": true,
        "VoiceActor": "wuu-CN-XiaotongNeural2",
        "VoiceId": "(wuu-CN, XiaotongNeural2)"
      },
      {
        "IsFemale": false,
        "VoiceActor": "wuu-CN-YunzheNeural2",
        "VoiceId": "(wuu-CN, YunzheNeural2)"
      }
    ]
  },
  {
    "LanguageKey": "yue-CN",
    "VoiceActors": [
      {
        "IsFemale": true,
        "VoiceActor": "yue-CN-XiaoMinNeural1,2",
        "VoiceId": "(yue-CN, XiaoMinNeural1,2)"
      },
      {
        "IsFemale": false,
        "VoiceActor": "yue-CN-YunSongNeural1,2",
        "VoiceId": "(yue-CN, YunSongNeural1,2)"
      }
    ]
  },
  {
    "LanguageKey": "zh-CN",
    "VoiceActors": [
      {
        "IsFemale": true,
        "VoiceActor": "zh-CN-XiaoxiaoNeural",
        "VoiceId": "(zh-CN, XiaoxiaoNeural)"
      },
      {
        "IsFemale": false,
        "VoiceActor": "zh-CN-YunxiNeural",
        "VoiceId": "(zh-CN, YunxiNeural)"
      },
      {
        "IsFemale": false,
        "VoiceActor": "zh-CN-YunjianNeural",
        "VoiceId": "(zh-CN, YunjianNeural)"
      },
      {
        "IsFemale": true,
        "VoiceActor": "zh-CN-XiaoyiNeural",
        "VoiceId": "(zh-CN, XiaoyiNeural)"
      },
      {
        "IsFemale": false,
        "VoiceActor": "zh-CN-YunyangNeural",
        "VoiceId": "(zh-CN, YunyangNeural)"
      },
      {
        "IsFemale": true,
        "VoiceActor": "zh-CN-XiaochenNeural",
        "VoiceId": "(zh-CN, XiaochenNeural)"
      },
      {
        "IsFemale": true,
        "VoiceActor": "zh-CN-XiaohanNeural",
        "VoiceId": "(zh-CN, XiaohanNeural)"
      },
      {
        "IsFemale": true,
        "VoiceActor": "zh-CN-XiaomengNeural",
        "VoiceId": "(zh-CN, XiaomengNeural)"
      },
      {
        "IsFemale": true,
        "VoiceActor": "zh-CN-XiaomoNeural",
        "VoiceId": "(zh-CN, XiaomoNeural)"
      },
      {
        "IsFemale": true,
        "VoiceActor": "zh-CN-XiaoqiuNeural",
        "VoiceId": "(zh-CN, XiaoqiuNeural)"
      },
      {
        "IsFemale": true,
        "VoiceActor": "zh-CN-XiaoruiNeural",
        "VoiceId": "(zh-CN, XiaoruiNeural)"
      },
      {
        "IsFemale": true,
        "VoiceActor": "zh-CN-XiaoshuangNeural",
        "VoiceId": "(zh-CN, XiaoshuangNeural)"
      },
      {
        "IsFemale": true,
        "VoiceActor": "zh-CN-XiaoxuanNeural",
        "VoiceId": "(zh-CN, XiaoxuanNeural)"
      },
      {
        "IsFemale": true,
        "VoiceActor": "zh-CN-XiaoyanNeural",
        "VoiceId": "(zh-CN, XiaoyanNeural)"
      },
      {
        "IsFemale": true,
        "VoiceActor": "zh-CN-XiaoyouNeural",
        "VoiceId": "(zh-CN, XiaoyouNeural)"
      },
      {
        "IsFemale": true,
        "VoiceActor": "zh-CN-XiaozhenNeural",
        "VoiceId": "(zh-CN, XiaozhenNeural)"
      },
      {
        "IsFemale": false,
        "VoiceActor": "zh-CN-YunfengNeural",
        "VoiceId": "(zh-CN, YunfengNeural)"
      },
      {
        "IsFemale": false,
        "VoiceActor": "zh-CN-YunhaoNeural",
        "VoiceId": "(zh-CN, YunhaoNeural)"
      },
      {
        "IsFemale": false,
        "VoiceActor": "zh-CN-YunxiaNeural",
        "VoiceId": "(zh-CN, YunxiaNeural)"
      },
      {
        "IsFemale": false,
        "VoiceActor": "zh-CN-YunyeNeural",
        "VoiceId": "(zh-CN, YunyeNeural)"
      },
      {
        "IsFemale": false,
        "VoiceActor": "zh-CN-YunzeNeural",
        "VoiceId": "(zh-CN, YunzeNeural)"
      },
      {
        "IsFemale": true,
        "VoiceActor": "zh-CN-XiaorouNeural1",
        "VoiceId": "(zh-CN, XiaorouNeural1)"
      },
      {
        "IsFemale": false,
        "VoiceActor": "zh-CN-YunjieNeural1",
        "VoiceId": "(zh-CN, YunjieNeural1)"
      }
    ]
  },
  {
    "LanguageKey": "zh-CN-GUANGXI",
    "VoiceActors": [
      {
        "IsFemale": false,
        "VoiceActor": "zh-CN-guangxi-YunqiNeural1,2",
        "VoiceId": "(zh-CN, guangxi)"
      }
    ]
  },
  {
    "LanguageKey": "zh-CN-henan",
    "VoiceActors": [
      {
        "IsFemale": false,
        "VoiceActor": "zh-CN-henan-YundengNeural2",
        "VoiceId": "(zh-CN, henan)"
      }
    ]
  },
  {
    "LanguageKey": "zh-CN-liaoning",
    "VoiceActors": [
      {
        "IsFemale": true,
        "VoiceActor": "zh-CN-liaoning-XiaobeiNeural1,2",
        "VoiceId": "(zh-CN, liaoning)"
      },
      {
        "IsFemale": false,
        "VoiceActor": "zh-CN-liaoning-YunbiaoNeural1,2",
        "VoiceId": "(zh-CN, liaoning)"
      }
    ]
  },
  {
    "LanguageKey": "zh-CN-shaanxi",
    "VoiceActors": [
      {
        "IsFemale": true,
        "VoiceActor": "zh-CN-shaanxi-XiaoniNeural1,2",
        "VoiceId": "(zh-CN, shaanxi)"
      }
    ]
  },
  {
    "LanguageKey": "zh-CN-shandong",
    "VoiceActors": [
      {
        "IsFemale": false,
        "VoiceActor": "zh-CN-shandong-YunxiangNeural2",
        "VoiceId": "(zh-CN, shandong)"
      }
    ]
  },
  {
    "LanguageKey": "zh-CN-sichuan",
    "VoiceActors": [
      {
        "IsFemale": false,
        "VoiceActor": "zh-CN-sichuan-YunxiNeural1,2",
        "VoiceId": "(zh-CN, sichuan)"
      }
    ]
  },
  {
    "LanguageKey": "zh-HK",
    "VoiceActors": [
      {
        "IsFemale": true,
        "VoiceActor": "zh-HK-HiuMaanNeural",
        "VoiceId": "(zh-HK, HiuMaanNeural)"
      },
      {
        "IsFemale": false,
        "VoiceActor": "zh-HK-WanLungNeural",
        "VoiceId": "(zh-HK, WanLungNeural)"
      },
      {
        "IsFemale": true,
        "VoiceActor": "zh-HK-HiuGaaiNeural",
        "VoiceId": "(zh-HK, HiuGaaiNeural)"
      }
    ]
  },
  {
    "LanguageKey": "zh-TW",
    "VoiceActors": [
      {
        "IsFemale": true,
        "VoiceActor": "zh-TW-HsiaoChenNeural",
        "VoiceId": "(zh-TW, HsiaoChenNeural)"
      },
      {
        "IsFemale": false,
        "VoiceActor": "zh-TW-YunJheNeural",
        "VoiceId": "(zh-TW, YunJheNeural)"
      },
      {
        "IsFemale": true,
        "VoiceActor": "zh-TW-HsiaoYuNeural",
        "VoiceId": "(zh-TW, HsiaoYuNeural)"
      }
    ]
  },
  {
    "LanguageKey": "zu-ZA",
    "VoiceActors": [
      {
        "IsFemale": true,
        "VoiceActor": "zu-ZA-ThandoNeural2",
        "VoiceId": "(zu-ZA, ThandoNeural2)"
      },
      {
        "IsFemale": false,
        "VoiceActor": "zu-ZA-ThembaNeural2",
        "VoiceId": "(zu-ZA, ThembaNeural2)"
      }
    ]
  }
]
               
                  

Let's look at the source code for calling the TextToSpeechUtil.cs shown above from a MAUI Blazor app view, Index.razor The code below shown is two private methods that does the work of retrieving the audio file from the Azure Speeech Service by first loading up all the voice actor ids from a bundled json file of voice actors displayed above and deserialize this into a list of voice actors. Retrieving the audio file passes in the translated text of which to generate synthesized speedch for and also the target language, all available actor voices and preferred voice actor id, if set. Retrieved is metadata and the audio file, in a MP3 file format. The file format is recognized by for example Windows withouth having to have any codec libraries installed in addition. Index.razor (Inside the @code block { .. } of that razor file)

 private async Task<TextToSpeechLanguage[]> GetActorVoices()
    {
        //https://learn.microsoft.com/en-us/azure/ai-services/speech-service/language-support?tabs=tts
        Stream actorVoicesStream = await FileSystem.OpenAppPackageFileAsync("voicebook.json");
        using StreamReader sr = new StreamReader(actorVoicesStream);
        string actorVoicesJson = string.Empty;
        string line;

        while ((line = sr.ReadLine()) != null)
        {
            //Console.WriteLine(line);
            actorVoicesJson += line;
        }

        var actorVoices = JsonSerializer.Deserialize<TextToSpeechLanguage[]>(actorVoicesJson);
        return actorVoices;
    }

    private async void SpeakText()
    {
        await Submit();
        var actorVoices = await GetActorVoices();
        TextToSpeechResult textToSpeechResult = await TextToSpeechUtil.GetSpeechFromText(Model.TranslatedText, Model.TargetLanguage, actorVoices, Model.PreferredVoiceActorId);

        Model.ActiveVoiceActorId = textToSpeechResult.VoiceActorId;
        Model.Transcript = textToSpeechResult.Transcript;
        Model.AvailableVoiceActorIds = textToSpeechResult.AvailableVoiceActorIds;
        Model.AdditionalVoiceDataMetaInformation = $"Byte size voice data: {textToSpeechResult?.VoiceData?.Length}, Audio output format: {textToSpeechResult.OutputFormat}";

        var voiceFolder = Path.Combine(FileSystem.Current.AppDataDirectory, "Resources", "Raw");
        if (!Directory.Exists(voiceFolder))
        {
            Directory.CreateDirectory(voiceFolder);
        }
        string voiceFile = "textToSpeechVoiceOutput_" + Model.TargetLanguage + Guid.NewGuid().ToString("N") + ".mpga";
        string voiceRelativeFile = Path.Combine(voiceFile);

        string voiceFileFullPath = Path.Combine(voiceFolder, voiceFile);
        await File.WriteAllBytesAsync(voiceFileFullPath, textToSpeechResult.VoiceData);
        Stream voiceStream = File.OpenRead(voiceFileFullPath);

        StateHasChanged();

        var player = AudioManager.CreatePlayer(voiceStream);
        player.Play();
    }

A screenshot shows how the DEMO app now looks like. You can translate text into other language and then have speech synthesis in Azure AI Cognitive Service generate a realistic audio speech of the translated text so you can also see how the text not only is translated, but also pronounced.

Using Azure Cognitive Services to summarize articles

I have added a repo on Github for a web scraping app written in .NET MAUI Blazor. It uses Azure Cognitive Services to summarize articles. https://github.com/toreaurstadboss/DagbladetWebscrapper The web scrapper uses the Nuget package for Html agility pack to handle the DOM after downloading articles from the Internet. As the name of the repo suggests, it can be used to read for example Dagbladet articles, without having to waddle through ads. 'Website Scraping' is a term that means extracting data from web sites, or content in general. The following libraries are used in the Razor lib containing the text handling methods to scrap web pages:

<PackageReference Include="Azure.AI.TextAnalytics" Version="5.3.0" />
<PackageReference Include="HtmlAgilityPack" Version="1.11.52" />
<PackageReference Include="Microsoft.AspNetCore.Components.Web" Version="6.0.19" />

Let's first look at the SummarizationUtil class. This uses TextAnalyticsClient in Azure.AI.TextAnalytics. We will summarize articles into five sentence summaries using the
Azure AI text analytics client.

using Azure.AI.TextAnalytics;
using System.Text;

namespace Webscrapper.Lib
{
	public class SummarizationUtil : ISummarizationUtil
	{

		public async Task<List<ExtractiveSummarizeResult>> GetExtractiveSummarizeResult(string document, TextAnalyticsClient client)
		{
			var batchedDocuments = new List<string>
			{
				document
			};
			var result = new List<ExtractiveSummarizeResult>();
			var options = new ExtractiveSummarizeOptions
			{
				 MaxSentenceCount = 5
			};
			var operation = await client.ExtractiveSummarizeAsync(Azure.WaitUntil.Completed, batchedDocuments, options: options);
			await foreach (ExtractiveSummarizeResultCollection documentsInPage in operation.Value)
			{
				foreach (ExtractiveSummarizeResult documentResult in documentsInPage)
				{
					result.Add(documentResult);
				}
			}
			return result;
		}

		public async Task<string> GetExtractiveSummarizeSentectesResult(string document, TextAnalyticsClient client)
		{
			List<ExtractiveSummarizeResult> summaries = await GetExtractiveSummarizeResult(document, client);
			return string.Join(Environment.NewLine, summaries.Select(s => s.Sentences).SelectMany(x => x).Select(x => x.Text));
		}

	}

}

We set up the extraction here to return a maximum of five sentences. Note the use of await foreach here. (async ienumerable) Here is a helper method to get a string from a ExtractiveSummarizeResult.

using Azure.AI.TextAnalytics;
using System.Text;

namespace Webscrapper.Lib
{

	public static class SummarizationExtensions
	{

		public static string GetExtractiveSummarizeResultInfo(this ExtractiveSummarizeResult documentResults)
		{
			var sb = new StringBuilder();

			if (documentResults.HasError)
			{
				sb.AppendLine($"Error!");
				sb.AppendLine($"Document error code: {documentResults.Error.ErrorCode}.");
				sb.AppendLine($"Message: {documentResults.Error.Message}");
			}
			else
			{
				sb.AppendLine($"SUCCESS. There are no errors encountered while summarizing the document");
			}

			sb.AppendLine($"Extracted the following {documentResults.Sentences.Count} sentence(s):");
			sb.AppendLine();

			foreach (ExtractiveSummarySentence sentence in documentResults.Sentences)
			{
				sb.AppendLine($"Sentence: {sentence.Text} Offset: {sentence.Offset} Rankscore: {sentence.RankScore} Length:{sentence.Length}");
				sb.AppendLine();
			}
			return sb.ToString();
		}
	}

}

Here is a factory method to create a TextAnalyticsClient.

using Azure;
using Azure.AI.TextAnalytics;

namespace Webscrapper.Lib
{
    public static class TextAnalyticsClientFactory
    {

        public static TextAnalyticsClient CreateClient()
        {
            string? uri = Environment.GetEnvironmentVariable("AZURE_COGNITIVE_SERVICE_ENDPOINT", EnvironmentVariableTarget.Machine);
            string? key = Environment.GetEnvironmentVariable("AZURE_COGNITIVE_SERVICE_KEY", EnvironmentVariableTarget.Machine);
            if (uri == null)
            {
                throw new ArgumentNullException(nameof(uri), "Could not get system environment variable named 'AZURE_COGNITIVE_SERVICE_ENDPOINT' Set this variable first.");
            }
            if (uri == null)
            {
                throw new ArgumentNullException(nameof(uri), "Could not get system environment variable named 'AZURE_COGNITIVE_SERVICE_KEY' Set this variable first.");
            }
            var client = new TextAnalyticsClient(new Uri(uri!), new AzureKeyCredential(key!));
            return client;
        }

    }
}

To use Azure Cognitive Services, you have to get the endpoint (an url) and a service key for your account in Azure portal after having activated Azure Cognitive Services. The page extraction util looks like this, note the use of Html Agility pack.

using HtmlAgilityPack;
using System.Text;

namespace Webscrapper.Lib
{
	public class PageExtractionUtil : IPageExtractionUtil
	{

		public async Task<string?> ExtractHtml(string url, bool includeTags)
		{
			if (string.IsNullOrEmpty(url)) 
				return null;
			var httpClient = new HttpClient();

			string pageHtml = await httpClient.GetStringAsync(url);
			if (string.IsNullOrEmpty(pageHtml))
			{
				return null;
			}

			var htmlDoc = new HtmlDocument(); 
			htmlDoc.LoadHtml(pageHtml);
			var textNodes = htmlDoc.DocumentNode.SelectNodes("//h1|//h2|//h3|//h4|//h5|//h6|//p")
				.Where(n => !string.IsNullOrWhiteSpace(n.InnerText)).ToList();
			var sb = new StringBuilder();
			foreach (var textNode in textNodes)
			{
				var text = textNode.InnerText;
				if (includeTags)
				{
					sb.AppendLine($"<{textNode.Name}>{textNode.InnerText}</{textNode.Name}>");
				}
				else
				{
					sb.AppendLine($"{textNode.InnerText}");
				}
			}
			return sb.ToString();
		}
	}
}

Let's look at an example usage :

@page "/"
@inject ISummarizationUtil SummarizationUtil
@inject IPageExtractionUtil PageExtractionUtil

@using DagbladetWebscrapper.Models;

<h1>Dagbladet Artikkel Oppsummering</h1>

<EditForm Model="@Model" OnValidSubmit="@Submit" class="form-group">
    <DataAnnotationsValidator />
    <ValidationSummary />
  
    <div class="form-group row">
    <label for="Model.ArticleUrl">Url til artikkel</label>
    <InputText @bind-Value="Model!.ArticleUrl" placeholder="Skriv inn url til artikkel i Dagbladet" />
    </div>

    <div class="form-group row">
    <span>Artikkelens oppsummering</span>
    <InputTextArea readonly="readonly" placeholder="Her dukker opp artikkelens oppsummering" @bind-Value="Model!.SummarySentences" rows="5"></InputTextArea>
    </div>

    <div class="form-group row">
    <span>Artikkelens tekst</span>
    <InputTextArea readonly="readonly" placeholder="Her dukker opp teksten til artikkelen" @bind-Value="Model!.ArticleText" rows="5"></InputTextArea>
    </div>
    
    <button type="submit">Submit</button>


</EditForm>

@code {
    private Azure.AI.TextAnalytics.TextAnalyticsClient _client;

    public IndexModel Model { get; set; } = new();

    private async void Submit()
    {
        string articleText = await PageExtractionUtil.ExtractHtml(Model!.ArticleUrl, false);
        Model.ArticleText = articleText;
        if (_client == null)
        {
            _client = TextAnalyticsClientFactory.CreateClient();
        }
        string summaryText = await SummarizationUtil.GetExtractiveSummarizeSentectesResult(articleText, _client);
        Model.SummarySentences = summaryText;

        StateHasChanged();
    }   

}

The view model class for the form looks like this.

using System.ComponentModel.DataAnnotations;

namespace DagbladetWebscrapper.Models
{
	public class IndexModel
	{
        [Required]
        public string? ArticleUrl { get; set; }

        public string SummarySentences { get; set; }

        public string ArticleText { get; set; }
    }
}

Let's look at a screen shot that shows the app in use. It targets an article on the tabloid newspaper Dagbladet in Norway. This tabloid is notorious for writing sensational titles of articles so you have to click into the article (e.g. 'clickbait') and then inside the article, you have to wade through lots of ads. Here, you now have an app, where you can open up www.dagbladet.no and find a link to an article and now extract the text and get a five sentence summary using Azure AI Cognitive services in a .NET MAUI app.