Showing posts with label .NET 6. Show all posts
Showing posts with label .NET 6. Show all posts

Monday 20 November 2023

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,
        "VoiceActor": "ar-YE-SalehNeural",
        "VoiceId": "(ar-YE, SalehNeural)"
      }
    ]
  },
  {
    "LanguageKey": "az-AZ",
    "VoiceActors": [
      {
        "IsFemale": true,
        "VoiceActor": "az-AZ-BanuNeural2",
        "VoiceId": "(az-AZ, BanuNeural2)"
      },
      {
        "IsFemale": false,
        "VoiceActor": "az-AZ-BabekNeural2",
        "VoiceId": "(az-AZ, BabekNeural2)"
      }
    ]
  },
  {
    "LanguageKey": "bg-BG",
    "VoiceActors": [
      {
        "IsFemale": true,
        "VoiceActor": "bg-BG-KalinaNeural",
        "VoiceId": "(bg-BG, KalinaNeural)"
      },
      {
        "IsFemale": false,
        "VoiceActor": "bg-BG-BorislavNeural",
        "VoiceId": "(bg-BG, BorislavNeural)"
      }
    ]
  },
  {
    "LanguageKey": "bn-BD",
    "VoiceActors": [
      {
        "IsFemale": true,
        "VoiceActor": "bn-BD-NabanitaNeural2",
        "VoiceId": "(bn-BD, NabanitaNeural2)"
      },
      {
        "IsFemale": false,
        "VoiceActor": "bn-BD-PradeepNeural2",
        "VoiceId": "(bn-BD, PradeepNeural2)"
      }
    ]
  },
  {
    "LanguageKey": "bn-IN",
    "VoiceActors": [
      {
        "IsFemale": true,
        "VoiceActor": "bn-IN-TanishaaNeural2",
        "VoiceId": "(bn-IN, TanishaaNeural2)"
      },
      {
        "IsFemale": false,
        "VoiceActor": "bn-IN-BashkarNeural2",
        "VoiceId": "(bn-IN, BashkarNeural2)"
      }
    ]
  },
  {
    "LanguageKey": "bs-BA",
    "VoiceActors": [
      {
        "IsFemale": true,
        "VoiceActor": "bs-BA-VesnaNeural2",
        "VoiceId": "(bs-BA, VesnaNeural2)"
      },
      {
        "IsFemale": false,
        "VoiceActor": "bs-BA-GoranNeural2",
        "VoiceId": "(bs-BA, GoranNeural2)"
      }
    ]
  },
  {
    "LanguageKey": "ca-ES",
    "VoiceActors": [
      {
        "IsFemale": true,
        "VoiceActor": "ca-ES-JoanaNeural",
        "VoiceId": "(ca-ES, JoanaNeural)"
      },
      {
        "IsFemale": false,
        "VoiceActor": "ca-ES-EnricNeural",
        "VoiceId": "(ca-ES, EnricNeural)"
      },
      {
        "IsFemale": true,
        "VoiceActor": "ca-ES-AlbaNeural",
        "VoiceId": "(ca-ES, AlbaNeural)"
      }
    ]
  },
  {
    "LanguageKey": "cs-CZ",
    "VoiceActors": [
      {
        "IsFemale": true,
        "VoiceActor": "cs-CZ-VlastaNeural",
        "VoiceId": "(cs-CZ, VlastaNeural)"
      },
      {
        "IsFemale": false,
        "VoiceActor": "cs-CZ-AntoninNeural",
        "VoiceId": "(cs-CZ, AntoninNeural)"
      }
    ]
  },
  {
    "LanguageKey": "cy-GB",
    "VoiceActors": [
      {
        "IsFemale": true,
        "VoiceActor": "cy-GB-NiaNeural2",
        "VoiceId": "(cy-GB, NiaNeural2)"
      },
      {
        "IsFemale": false,
        "VoiceActor": "cy-GB-AledNeural2",
        "VoiceId": "(cy-GB, AledNeural2)"
      }
    ]
  },
  {
    "LanguageKey": "da-DK",
    "VoiceActors": [
      {
        "IsFemale": true,
        "VoiceActor": "da-DK-ChristelNeural",
        "VoiceId": "(da-DK, ChristelNeural)"
      },
      {
        "IsFemale": false,
        "VoiceActor": "da-DK-JeppeNeural",
        "VoiceId": "(da-DK, JeppeNeural)"
      }
    ]
  },
  {
    "LanguageKey": "de-AT",
    "VoiceActors": [
      {
        "IsFemale": true,
        "VoiceActor": "de-AT-IngridNeural",
        "VoiceId": "(de-AT, IngridNeural)"
      },
      {
        "IsFemale": false,
        "VoiceActor": "de-AT-JonasNeural",
        "VoiceId": "(de-AT, JonasNeural)"
      }
    ]
  },
  {
    "LanguageKey": "de-CH",
    "VoiceActors": [
      {
        "IsFemale": true,
        "VoiceActor": "de-CH-LeniNeural",
        "VoiceId": "(de-CH, LeniNeural)"
      },
      {
        "IsFemale": false,
        "VoiceActor": "de-CH-JanNeural",
        "VoiceId": "(de-CH, JanNeural)"
      }
    ]
  },
  {
    "LanguageKey": "de-DE",
    "VoiceActors": [
      {
        "IsFemale": true,
        "VoiceActor": "de-DE-KatjaNeural",
        "VoiceId": "(de-DE, KatjaNeural)"
      },
      {
        "IsFemale": false,
        "VoiceActor": "de-DE-ConradNeural1",
        "VoiceId": "(de-DE, ConradNeural1)"
      },
      {
        "IsFemale": true,
        "VoiceActor": "de-DE-AmalaNeural",
        "VoiceId": "(de-DE, AmalaNeural)"
      },
      {
        "IsFemale": false,
        "VoiceActor": "de-DE-BerndNeural",
        "VoiceId": "(de-DE, BerndNeural)"
      },
      {
        "IsFemale": false,
        "VoiceActor": "de-DE-ChristophNeural",
        "VoiceId": "(de-DE, ChristophNeural)"
      },
      {
        "IsFemale": true,
        "VoiceActor": "de-DE-ElkeNeural",
        "VoiceId": "(de-DE, ElkeNeural)"
      },
      {
        "IsFemale": true,
        "VoiceActor": "de-DE-GiselaNeural",
        "VoiceId": "(de-DE, GiselaNeural)"
      },
      {
        "IsFemale": false,
        "VoiceActor": "de-DE-KasperNeural",
        "VoiceId": "(de-DE, KasperNeural)"
      },
      {
        "IsFemale": false,
        "VoiceActor": "de-DE-KillianNeural",
        "VoiceId": "(de-DE, KillianNeural)"
      },
      {
        "IsFemale": true,
        "VoiceActor": "de-DE-KlarissaNeural",
        "VoiceId": "(de-DE, KlarissaNeural)"
      },
      {
        "IsFemale": false,
        "VoiceActor": "de-DE-KlausNeural",
        "VoiceId": "(de-DE, KlausNeural)"
      },
      {
        "IsFemale": true,
        "VoiceActor": "de-DE-LouisaNeural",
        "VoiceId": "(de-DE, LouisaNeural)"
      },
      {
        "IsFemale": true,
        "VoiceActor": "de-DE-MajaNeural",
        "VoiceId": "(de-DE, MajaNeural)"
      },
      {
        "IsFemale": false,
        "VoiceActor": "de-DE-RalfNeural",
        "VoiceId": "(de-DE, RalfNeural)"
      },
      {
        "IsFemale": true,
        "VoiceActor": "de-DE-SeraphinaNeural",
        "VoiceId": "(de-DE, SeraphinaNeural)"
      },
      {
        "IsFemale": true,
        "VoiceActor": "de-DE-TanjaNeural",
        "VoiceId": "(de-DE, TanjaNeural)"
      }
    ]
  },
  {
    "LanguageKey": "el-GR",
    "VoiceActors": [
      {
        "IsFemale": true,
        "VoiceActor": "el-GR-AthinaNeural",
        "VoiceId": "(el-GR, AthinaNeural)"
      },
      {
        "IsFemale": false,
        "VoiceActor": "el-GR-NestorasNeural",
        "VoiceId": "(el-GR, NestorasNeural)"
      }
    ]
  },
  {
    "LanguageKey": "en-AU",
    "VoiceActors": [
      {
        "IsFemale": true,
        "VoiceActor": "en-AU-NatashaNeural",
        "VoiceId": "(en-AU, NatashaNeural)"
      },
      {
        "IsFemale": false,
        "VoiceActor": "en-AU-WilliamNeural",
        "VoiceId": "(en-AU, WilliamNeural)"
      },
      {
        "IsFemale": true,
        "VoiceActor": "en-AU-AnnetteNeural",
        "VoiceId": "(en-AU, AnnetteNeural)"
      },
      {
        "IsFemale": true,
        "VoiceActor": "en-AU-CarlyNeural",
        "VoiceId": "(en-AU, CarlyNeural)"
      },
      {
        "IsFemale": false,
        "VoiceActor": "en-AU-DarrenNeural",
        "VoiceId": "(en-AU, DarrenNeural)"
      },
      {
        "IsFemale": false,
        "VoiceActor": "en-AU-DuncanNeural",
        "VoiceId": "(en-AU, DuncanNeural)"
      },
      {
        "IsFemale": true,
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  }
]
               
                  

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.



Saturday 14 October 2023

Using Image Analysis in Azure AI Cognitive Services

I have added a demo .NET MAUI Blazor app that uses Image Analysis in Computer Vision in Azure Cognitive Services. Note that Image Analysis is not available in all Azure data centers. For example, Norway East does not have this feature. However, North Europe Azure data center do have the feature, the data center i Ireland. A Github repo exists for this demo here:

https://github.com/toreaurstadboss/Image.Analyze.Azure.Ai

A screen shot for this demo is shown below: Demo screenshot The demo allows you to upload a picture (supported formats are .jpeg, .jpg and .png, but Azure AI Image Analyzer supports a lot of other image formats too). The demo shows a preview of the selected image and to the right an image of bounding boxes of objects in the image. A list of tags extracted from the image are also shown. Raw data from the Azure Image Analyzer service is shown in the text box area below the pictures, with a list of tags to the right. The demo is written with .NET Maui Blazor and .NET 6. Let us look at some code for making this demo. ImageSaveService.cs


using Image.Analyze.Azure.Ai.Models;
using Microsoft.AspNetCore.Components.Forms;

namespace Ocr.Handwriting.Azure.AI.Services
{

    public class ImageSaveService : IImageSaveService
    {

        public async Task<ImageSaveModel> SaveImage(IBrowserFile browserFile)
        {
            var buffers = new byte[browserFile.Size];
            var bytes = await browserFile.OpenReadStream(maxAllowedSize: 30 * 1024 * 1024).ReadAsync(buffers);
            string imageType = browserFile.ContentType;

            var basePath = FileSystem.Current.AppDataDirectory;
            var imageSaveModel = new ImageSaveModel
            {
                SavedFilePath = Path.Combine(basePath, $"{Guid.NewGuid().ToString("N")}-{browserFile.Name}"),
                PreviewImageUrl = $"data:{imageType};base64,{Convert.ToBase64String(buffers)}",
                FilePath = browserFile.Name,
                FileSize = bytes / 1024,
            };

            await File.WriteAllBytesAsync(imageSaveModel.SavedFilePath, buffers);

            return imageSaveModel;
        }

    }
}

//Interface defined inside IImageService.cs shown below
using Image.Analyze.Azure.Ai.Models;
using Microsoft.AspNetCore.Components.Forms;

namespace Ocr.Handwriting.Azure.AI.Services
{
  
    public interface IImageSaveService
    {

        Task<ImageSaveModel> SaveImage(IBrowserFile browserFile);

    }

}


The ImageSaveService saves the uploaded image from the IBrowserFile into a base-64 string from the image bytes of the uploaded IBrowserFile via OpenReadStream of the IBrowserFile. This allows us to preview the uploaded image. The code also saves the image to the AppDataDirectory that MAUI supports - FileSystem.Current.AppDataDirectory. Let's look at how to call the analysis service itself, it is actually quite straight forward. ImageAnalyzerService.cs


using Azure;
using Azure.AI.Vision.Common;
using Azure.AI.Vision.ImageAnalysis;

namespace Image.Analyze.Azure.Ai.Lib
{

    public class ImageAnalyzerService : IImageAnalyzerService
    {

        public ImageAnalyzer CreateImageAnalyzer(string imageFile)
        {
            string key = Environment.GetEnvironmentVariable("AZURE_COGNITIVE_SERVICES_VISION_SECONDARY_KEY");
            string endpoint = Environment.GetEnvironmentVariable("AZURE_COGNITIVE_SERVICES_VISION_SECONDARY_ENDPOINT");
            var visionServiceOptions = new VisionServiceOptions(new Uri(endpoint), new AzureKeyCredential(key));

            using VisionSource visionSource = CreateVisionSource(imageFile);

            var analysisOptions = CreateImageAnalysisOptions();

            var analyzer = new ImageAnalyzer(visionServiceOptions, visionSource, analysisOptions);
            return analyzer;

        }

        private static VisionSource CreateVisionSource(string imageFile)
        {
            using var stream = File.OpenRead(imageFile);
            using var reader = new StreamReader(stream);
            byte[] imageBuffer;
            using (var streamReader = new MemoryStream())
            {
                stream.CopyTo(streamReader);
                imageBuffer = streamReader.ToArray();
            }

            using var imageSourceBuffer = new ImageSourceBuffer();
            imageSourceBuffer.GetWriter().Write(imageBuffer);
            return VisionSource.FromImageSourceBuffer(imageSourceBuffer);
        }

        private static ImageAnalysisOptions CreateImageAnalysisOptions() => new ImageAnalysisOptions
        {
            Language = "en",
            GenderNeutralCaption = false,
            Features =
              ImageAnalysisFeature.CropSuggestions
            | ImageAnalysisFeature.Caption
            | ImageAnalysisFeature.DenseCaptions
            | ImageAnalysisFeature.Objects
            | ImageAnalysisFeature.People
            | ImageAnalysisFeature.Text
            | ImageAnalysisFeature.Tags
        };

    }

}

//interface shown below 

 public interface IImageAnalyzerService
 {
     ImageAnalyzer CreateImageAnalyzer(string imageFile);
 }



We retrieve environment variables here and we create an ImageAnalyzer. We create a Vision source from the saved picture we uploaded and open a stream to it using File.OpenRead method on System.IO. Since we saved the file in the AppData folder of the .NET MAUI app, we can read this file. We set up the image analysis options and the vision service options. We then call the return the image analyzer. Let's look at the code-behind of the index.razor file that initializes the Image analyzer, and runs the Analyze method of it. Index.razor.cs
 
 
 using Azure.AI.Vision.ImageAnalysis;
using Image.Analyze.Azure.Ai.Extensions;
using Image.Analyze.Azure.Ai.Models;
using Microsoft.AspNetCore.Components.Forms;
using Microsoft.JSInterop;
using System.Text;

namespace Image.Analyze.Azure.Ai.Pages
{
    partial class Index
    {

        private IndexModel Model = new();

        //https://learn.microsoft.com/en-us/azure/ai-services/computer-vision/how-to/call-analyze-image-40?WT.mc_id=twitter&pivots=programming-language-csharp

        private string ImageInfo = string.Empty;

        private async Task Submit()
        {
            if (Model.PreviewImageUrl == null || Model.SavedFilePath == null)
            {
                await Application.Current.MainPage.DisplayAlert($"MAUI Blazor Image Analyzer App", $"You must select an image first before running Image Analysis. Supported formats are .jpeg, .jpg and .png", "Ok", "Cancel");
                return;
            }

            using var imageAnalyzer = ImageAnalyzerService.CreateImageAnalyzer(Model.SavedFilePath);

            ImageAnalysisResult analysisResult = await imageAnalyzer.AnalyzeAsync();

            if (analysisResult.Reason == ImageAnalysisResultReason.Analyzed)
            {
                Model.ImageAnalysisOutputText = analysisResult.OutputImageAnalysisResult();
                Model.Caption = $"{analysisResult.Caption.Content} Confidence: {analysisResult.Caption.Confidence.ToString("F2")}";
                Model.Tags = analysisResult.Tags.Select(t => $"{t.Name} (Confidence: {t.Confidence.ToString("F2")})").ToList();
                var jsonBboxes = analysisResult.GetBoundingBoxesJson();
                await JsRunTime.InvokeVoidAsync("LoadBoundingBoxes", jsonBboxes);
            }
            else
            {
                ImageInfo = $"The image analysis did not perform its analysis. Reason: {analysisResult.Reason}";
            }

            StateHasChanged(); //visual refresh here
        }

        private async Task CopyTextToClipboard()
        {
            await Clipboard.SetTextAsync(Model.ImageAnalysisOutputText);
            await Application.Current.MainPage.DisplayAlert($"MAUI Blazor Image Analyzer App", $"The copied text was put into the clipboard. Character length: {Model.ImageAnalysisOutputText?.Length}", "Ok", "Cancel");
        }

        private async Task OnInputFile(InputFileChangeEventArgs args)
        {
            var imageSaveModel = await ImageSaveService.SaveImage(args.File);
            Model = new IndexModel(imageSaveModel);
            await Application.Current.MainPage.DisplayAlert($"MAUI Blazor ImageAnalyzer app App", $"Wrote file to location : {Model.SavedFilePath} Size is: {Model.FileSize} kB", "Ok", "Cancel");
        }


    }
}
 
 
In the code-behind above we have a submit handler called Submit. We there analyze the image and send the result both to the UI and also to a client side Javascript method using IJSRuntime in .NET MAUI Blazor. Let's look at the two helper methods of ImageAnalysisResult next. ImageAnalysisResultExtensions.cs
 
 
 using Azure.AI.Vision.ImageAnalysis;
using System.Text;

namespace Image.Analyze.Azure.Ai.Extensions
{
    public static class ImageAnalysisResultExtensions
    {

        public static string GetBoundingBoxesJson(this ImageAnalysisResult result)
        {
            var sb = new StringBuilder();
            sb.AppendLine(@"[");

            int objectIndex = 0;
            foreach (var detectedObject in result.Objects)
            {
                sb.Append($"{{ \"Name\": \"{detectedObject.Name}\", \"Y\": {detectedObject.BoundingBox.Y}, \"X\": {detectedObject.BoundingBox.X}, \"Height\": {detectedObject.BoundingBox.Height}, \"Width\": {detectedObject.BoundingBox.Width}, \"Confidence\": \"{detectedObject.Confidence:0.0000}\" }}");
                objectIndex++;
                if (objectIndex < result.Objects?.Count)
                {
                    sb.Append($",{Environment.NewLine}");
                }
                else
                {
                    sb.Append($"{Environment.NewLine}");
                }
            }
            sb.Remove(sb.Length - 2, 1); //remove trailing comma at the end
            sb.AppendLine(@"]");
            return sb.ToString();
        }

        public static string OutputImageAnalysisResult(this ImageAnalysisResult result)
        {
            var sb = new StringBuilder();

            if (result.Reason == ImageAnalysisResultReason.Analyzed)
            {

                sb.AppendLine($" Image height = {result.ImageHeight}");
                sb.AppendLine($" Image width = {result.ImageWidth}");
                sb.AppendLine($" Model version = {result.ModelVersion}");

                if (result.Caption != null)
                {
                    sb.AppendLine(" Caption:");
                    sb.AppendLine($"   \"{result.Caption.Content}\", Confidence {result.Caption.Confidence:0.0000}");
                }

                if (result.DenseCaptions != null)
                {
                    sb.AppendLine(" Dense Captions:");
                    foreach (var caption in result.DenseCaptions)
                    {
                        sb.AppendLine($"   \"{caption.Content}\", Bounding box {caption.BoundingBox}, Confidence {caption.Confidence:0.0000}");
                    }
                }

                if (result.Objects != null)
                {
                    sb.AppendLine(" Objects:");
                    foreach (var detectedObject in result.Objects)
                    {
                        sb.AppendLine($"   \"{detectedObject.Name}\", Bounding box {detectedObject.BoundingBox}, Confidence {detectedObject.Confidence:0.0000}");
                    }
                }

                if (result.Tags != null)
                {
                    sb.AppendLine($" Tags:");
                    foreach (var tag in result.Tags)
                    {
                        sb.AppendLine($"   \"{tag.Name}\", Confidence {tag.Confidence:0.0000}");
                    }
                }

                if (result.People != null)
                {
                    sb.AppendLine($" People:");
                    foreach (var person in result.People)
                    {
                        sb.AppendLine($"   Bounding box {person.BoundingBox}, Confidence {person.Confidence:0.0000}");
                    }
                }

                if (result.CropSuggestions != null)
                {
                    sb.AppendLine($" Crop Suggestions:");
                    foreach (var cropSuggestion in result.CropSuggestions)
                    {
                        sb.AppendLine($"   Aspect ratio {cropSuggestion.AspectRatio}: "
                            + $"Crop suggestion {cropSuggestion.BoundingBox}");
                    };
                }

                if (result.Text != null)
                {
                    sb.AppendLine($" Text:");
                    foreach (var line in result.Text.Lines)
                    {
                        string pointsToString = "{" + string.Join(',', line.BoundingPolygon.Select(pointsToString => pointsToString.ToString())) + "}";
                        sb.AppendLine($"   Line: '{line.Content}', Bounding polygon {pointsToString}");

                        foreach (var word in line.Words)
                        {
                            pointsToString = "{" + string.Join(',', word.BoundingPolygon.Select(pointsToString => pointsToString.ToString())) + "}";
                            sb.AppendLine($"     Word: '{word.Content}', Bounding polygon {pointsToString}, Confidence {word.Confidence:0.0000}");
                        }
                    }
                }

                var resultDetails = ImageAnalysisResultDetails.FromResult(result);
                sb.AppendLine($" Result details:");
                sb.AppendLine($"   Image ID = {resultDetails.ImageId}");
                sb.AppendLine($"   Result ID = {resultDetails.ResultId}");
                sb.AppendLine($"   Connection URL = {resultDetails.ConnectionUrl}");
                sb.AppendLine($"   JSON result = {resultDetails.JsonResult}");
            }
            else
            {
                var errorDetails = ImageAnalysisErrorDetails.FromResult(result);
                sb.AppendLine(" Analysis failed.");
                sb.AppendLine($"   Error reason : {errorDetails.Reason}");
                sb.AppendLine($"   Error code : {errorDetails.ErrorCode}");
                sb.AppendLine($"   Error message: {errorDetails.Message}");
            }

            return sb.ToString();
        }

    }
}


  
 
Finally, let's look at the client side Javascript function that we call and send the bounding boxes json to draw the boxes. We will use Canvas in HTML 5 to show the picture and the bounding boxes of objects found in the image. index.html
 
 
 	<script type="text/javascript">

		var colorPalette = ["red", "yellow", "blue", "green", "fuchsia", "moccasin", "purple", "magenta", "aliceblue", "lightyellow", "lightgreen"];

		function rescaleCanvas() {
			var img = document.getElementById('PreviewImage');
			var canvas = document.getElementById('PreviewImageBbox');
			canvas.width = img.width;
			canvas.height = img.height;
		}

		function getColor() {
			var colorIndex = parseInt(Math.random() * 10);
			var color = colorPalette[colorIndex];
			return color;
		}

		function LoadBoundingBoxes(objectDescriptions) {
			if (objectDescriptions == null || objectDescriptions == false) {
				alert('did not find any objects in image. returning from calling load bounding boxes : ' + objectDescriptions);
				return;
			}

			var objectDesc = JSON.parse(objectDescriptions);
			//alert('calling load bounding boxes, starting analysis on clientside js : ' + objectDescriptions);

			rescaleCanvas();
			var canvas = document.getElementById('PreviewImageBbox');
			var img = document.getElementById('PreviewImage');

			var ctx = canvas.getContext('2d');
			ctx.drawImage(img, img.width, img.height);

			ctx.font = "10px Verdana";

			for (var i = 0; i < objectDesc.length; i++) {
				ctx.beginPath();
				ctx.strokeStyle = "black";
				ctx.lineWidth = 1;
				ctx.fillText(objectDesc[i].Name, objectDesc[i].X + objectDesc[i].Width / 2, objectDesc[i].Y + objectDesc[i].Height / 2);
				ctx.fillText("Confidence: " + objectDesc[i].Confidence, objectDesc[i].X + objectDesc[i].Width / 2, 10 + objectDesc[i].Y + objectDesc[i].Height / 2);
			}

			for (var i = 0; i < objectDesc.length; i++) {
				ctx.fillStyle = getColor();
				ctx.globalAlpha = 0.2;
				ctx.fillRect(objectDesc[i].X, objectDesc[i].Y, objectDesc[i].Width, objectDesc[i].Height);
				ctx.lineWidth = 3;
				ctx.strokeStyle = "blue";
				ctx.rect(objectDesc[i].X, objectDesc[i].Y, objectDesc[i].Width, objectDesc[i].Height);
				ctx.fillStyle = "black";
				ctx.fillText("Color: " + getColor(), objectDesc[i].X + objectDesc[i].Width / 2, 20 + objectDesc[i].Y + objectDesc[i].Height / 2);

				ctx.stroke();
			}

			ctx.drawImage(img, 0, 0);


			console.log('got these object descriptions:');
			console.log(objectDescriptions);

		}
	</script>

 
  
The index.html file in wwwroot is the place we usually put extra css and js for MAUI Blazor apps and Blazor apps. I have chosen to put the script directly into the index.html file and not in a .js file, but that is an option to be chosen to tidy up a bit more. So there you have it, we can relatively easily find objects in images using Azure analyze image service in Azure Cognitive Services. We can get tags and captions of the image. In the demo the caption is shown above the picture loaded. Azure Computer vision service is really good since it has got a massive training set and can recognize a lot of different objects for different usages. As you see in the source code, I have the key and endpoint inside environment variables that the code expects exists. Never expose keys and endpoints in your source code.