Book Image

Learning Microsoft Cognitive Services

By : Leif Larsen
Book Image

Learning Microsoft Cognitive Services

By: Leif Larsen

Overview of this book

Take your app development to the next level with Learning Microsoft Cognitive Services. Using Leif's knowledge of each of the powerful APIs, you'll learn how to create smarter apps with more human-like capabilities. ? Discover what each API has to offer and learn how to add it to your app ? Study each AI using theory and practical examples ? Learn current API best practices
Table of Contents (20 chapters)
Learning Microsoft Cognitive Services
About the Author
About the Reviewer
Customer Feedback
Additional Information on Linguistic Analysis

Getting feedback on detected faces

Now that we have seen what else Microsoft Cognitive Services can offer, we are going to add an API to our face detection application. Through this part we will add the Bing Speech API to make the application say the number of faces out loud.

This feature of the API is not provided in the NuGet package, and as such we are going to use the REST API.

To reach our end goal we are going to add two new classes, TextToSpeak and Authentication. The first class will be in charge of generating correct headers and making the calls to our service endpoint. The latter class will be in charge of generating an authentication token. This will be tied together in our ViewModel, where we will make the application speak back to us.

We need to get our hands on an API key first. Head over to and click the yellow button stating Get started for free. Make sure the correct API (Bing Speech Free/Preview) is selected and accept the terms and conditions.

To be able to call the Bing Speech API, we need to have an authorization token. Go back to Visual Studio and create a new file called Authentication.cs. Place this in the Model folder.

We need to add two new references to the project. Find System.Runtime.Serialization and System.Web packages in the Assembly tab in the Add References window and add them.

In our newly created Authentication file, add a public class beneath the automatically generated class:

    public class AccessTokenInfo 
        public string access_token { get; set; } 
        public string token_type { get; set; } 
        public string expires_in { get; set; } 
        public string scope { get; set; } 

The response for our access token request will be serialized into this class, which will be used by our text-to-speech conversion later.

In our Authentication class, define four private variables and one public property:

    private string _requestDetails; 
    private AccessTokenInfo _token; 
    private Timer _tokenRenewer; 
    private const int TokenRefreshInterval = 9; 
    public AccessTokenInfo Token { get { return _token; } } 

The constructor should accept two string parameters, clientId and clientSecret. The clientId parameter will typically be your application name, while the clientSecret parameter is the API key you signed up for.

In the constructor, assign _requestDetails, _token, and _accessTokenRenewer variables:

    _requestDetails = string.Format("grant_type=client_credentials & client_id={0} & client_secret={1} & scope={2}", 
    _token = GetToken(); 
    _tokenRenewer = new Timer(new TimerCallback(OnTokenExpiredCallback), this, 

The _requestDetails variable contains the credentials provided in the parameters. It also defines a scope, for which these are valid.

We then fetch the access token; in a method we will create shortly.

Finally, we create our timer class, which will call the callback function in 9 minutes. The callback function will need to fetch the access token again and assign it to the _token variable. It also needs to assure that we run the timer again in 9 minutes.

Next we need to create the GetToken method. This method should return an AccessTokenInfo object, and it should be declared as private:

    WebRequestwebRequest = WebRequest.Create(""); 
    webRequest.ContentType = "application/x-www-form-urlencoded"; 
webRequest.Method = "POST"; 

In the method, we start by creating a web request object, pointing to an endpoint that will generate our token. We specify the content type and HTTP method:

    byte[] bytes = Encoding.ASCII.GetBytes(_requestDetails); 
webRequest.ContentLength = bytes.Length; 

We then go on to get the byte array from the _requestDetails variable that we initialized in the constructor. This will be sent with the web request:

        using (Stream outputStream = webRequest.GetRequestStream()) 
            outputStream.Write(bytes, 0, bytes.Length); 

When the request has been sent, we expect there to be a response. We want to read this response and serialize it into the AccessTokenInfo object, which we created earlier:

        using (WebResponsewebResponse = webRequest.GetResponse()) 
            DataContractJsonSerializerserializer = new DataContractJsonSerializer(typeof(AccessTokenInfo)); 
            AccessTokenInfo token = (AccessTokenInfo) serializer.ReadObject(webResponse.GetResponseStream()); 
            return token; 

Add a catch clause to handle potential errors and the authentication class is ready to be used.

Add a new file, called TextToSpeak.cs, if you have not already done so. Put this file in the Model folder.

Beneath the newly created class (but inside the namespace), we want to add two event arguments classes. These will be used to handle audio events, which we will see later:

    public class AudioEventArgs : EventArgs 
        public AudioEventArgs(Stream eventData) 
            EventData = eventData; 
        public StreamEventData { get; private set; }  

The AudioEventArgs class simply takes a generic stream, and you can imagine it being used to send the audio stream to our application:

    public class AudioErrorEventArgs : EventArgs 
        public AudioErrorEventArgs(string message) 
            ErrorMessage = message; 
        public string ErrorMessage { get; private set; } 

This next class allows us to send an event with a specific error message.

We move on to start on the TextToSpeak class, where we start off by declaring some events and class members:

    public class TextToSpeak 
        public event EventHandler<AudioEventArgs>OnAudioAvailable; 
        public event EventHandler<AudioErrorEventArgs>OnError; 
        private string _gender; 
        private string _voiceName; 
        private string _outputFormat; 
        private string _authorizationToken; 
        private AccessTokenInfo _token;  
        private List<KeyValuePair<string, string>> _headers = new  List<KeyValuePair<string, string>>(); 

The first two lines in the class are events using the event argument classes we created earlier. These events will be triggered if a call to the API finishes, and returns some audio, or if anything fails. The next few lines are string variables, which we will use as input parameters. We have one line to contain our access token information. The last line creates a new list, which we will use to hold our request headers.

We add two constant strings to our class:

        private const string RequestUri =  ""; 
        private const string SsmlTemplate = "<speak version='1.0'xml:lang='en-US'><voice xml:lang='en-US'xml:gender='{0}' name='{1}'>{2}</voice></speak>";

The first string contains the request URI. That is the REST API endpoint we need to call to execute our request. Next we have a string defining our Speech Synthesis Markup Language (SSML) template. This is where we will specify what the Speech service should say, and a bit on how it should say it.

Next we create our constructor:

        public TextToSpeak() 
            _gender = "Female"; 
            _outputFormat = "riff-16khz-16bit-mono-pcm"; 
            _voiceName = "Microsoft Server Speech Text to Speech Voice (en-US, ZiraRUS)"; 

Here we are just initializing some of our variables, declared earlier. As you may see, we are defining the voice to be female and we define it to use a specific voice. In terms of gender, naturally it can be either female or male. In terms of voice name, it can be one of a long list of options. We will look more into the details of that list when we go through this API in a later chapter.

The last line specifies the output format of the audio. This will define the format and codec in use by the resulting audio stream. Again this can be a number of varieties, which we will look into in a later chapter.

Following the constructor, there are three public methods we will create. These will generate an authentication token, generate some HTTP headers, and finally execute our call to the API. Before we create these, you should add two helper methods to be able to raise our events. Call them the RaiseOnAudioAvailable and RaiseOnError methods. They should accept AudioEventArgs and AudioErrorEventArgs as parameters.

Next, add a new method called the GenerateHeaders method:

        public void GenerateHeaders() 
            _headers.Add(new KeyValuePair<string, string>("Content-Type", "application/ssml+xml")); 
            _headers.Add(new KeyValuePair<string, string>("X-Microsoft-OutputFormat", _outputFormat)); 
            _headers.Add(new KeyValuePair<string, string>("Authorization", _authorizationToken)); 
            _headers.Add(new KeyValuePair<string, string>("X-Search-AppId", Guid.NewGuid().ToString("N"))); 
            _headers.Add(new KeyValuePair<string, string>("X-Search-ClientID", Guid.NewGuid().ToString("N"))); 
            _headers.Add(new KeyValuePair<string, string>("User-Agent", "Chapter1")); 

Here we add the HTTP headers, to our previously created list. These headers are required for the service to respond, and if any is missing it will yield an HTTP/400 response. What we are using as headers is something we will cover in more detail later. For now, just make sure they are present.

Following this we want to add a new method called GenerateAuthenticationToken:

        public bool GenerateAuthenticationToken(string clientId, string clientSecret) 
            Authentication auth = new Authentication(clientId, clientSecret); 

This method accepts two string parameters, one ID for the client (typically your application name) and one client secret (your API key). First we create a new object of the Authentication class, which we looked at earlier:

            _token = auth.Token; 
            if (_token != null) 
                _authorizationToken = $"Bearer {_token.access_token}"; 
                return true; 
                RaiseOnError(new AudioErrorEventArgs("Failed to generate authentication token.")); 
                return false; 

We use the authentication object to retrieve an access token. This token is used in our authorization token string, which, as we saw earlier, is being passed on in our headers. If the application for some reason fails to generate the access token, we trigger an error event.

Finish this method by adding the associated catch clause. If any exceptions occur, we want to raise a new error event.

The last method we need to create in this class we are going to call the SpeakAsync method. This will be the method that actually performs the request to the Speech API:

        public Task SpeakAsync(string textToSpeak, CancellationTokencancellationToken) 
            varcookieContainer = new CookieContainer(); 
            var handler = new HttpClientHandler() { CookieContainer = cookieContainer }; 
            var client = new HttpClient(handler);  

The method takes two parameters. One string, which will be the text we want to be spoken. The next is a cancellation token. This can be used to propagate that the given operation should be cancelled.

When entering the method, we create three objects, which we will use to execute the request. These are classes from the .NET library, and we will not be going through them in any more detail:

            foreach(var header in _headers) 
                client.DefaultRequestHeaders.TryAddWithoutValidation (header.Key, header.Value); 

We generated some headers earlier and we need to add these to our HTTP client. We do this by adding the headers in the preceding foreach loop, basically looping through the entire list:

            var request = new HttpRequestMessage(HttpMethod.Post, RequestUri) 
                Content = new StringContent(string.Format(SsmlTemplate, _gender, _voiceName, textToSpeak)) 

Next we create an HTTP Request Message, specifying that we will send data through the POST method, and specifying the request URI. We also specify the content, using the SSML template we created earlier and adding the correct parameters (gender, voice name, and the text we want to be spoken):

            var httpTask = client.SendAsync(request, HttpCompletionOption.ResponseHeadersRead, cancellationToken); 

We use the HTTP client to send the HTTP request asynchronously:

            var saveTask = httpTask.ContinueWith(async (responseMessage, token) => 
                    if(responseMessage.IsCompleted && responseMessage.Result != null && responseMessage.Result.IsSuccessStatusCode) 
                        var httpStream = await responseMessage. Result.Content.ReadAsStreamAsync().ConfigureAwait(false); 
                         RaiseOnAudioAvailable(new AudioEventArgs (httpStream)); 
                         RaiseOnError(new AudioErrorEventArgs($"Service returned {responseMessage.Result.StatusCode}")); 
                  catch(Exception e) 
                      RaiseOnError(new AudioErrorEventArgs (e.GetBaseException().Message)); 

The preceding code is a continuation of the asynchronous send call we made previously. This will run asynchronously as well, and check the status of the response. If the response is successful, it will read the response message as a stream, and trigger the audio event. If everything succeeded, then that stream should contain our text in spoken words.

If the response indicates anything else than success, we will raise the error event.

We also want to add a catch clause, as well as a finally clause to this. Raise an error if an exception is caught, and dispose of all objects used in the finally clause.

The final code we need is to specify that the continuation task is attached to the parent task. Also we need to add the cancellation token to this task as well. Go on to add the following code to finish off the method:

            }, TaskContinuationOptions.AttachedToParent, cancellationToken); 
            return saveTask; 

With that in place we are now able to utilize this class in our application, and we are going to do that now. Open the MainViewModel.cs file and declare a new class variable:

        private TextToSpeak _textToSpeak; 

Add the following code in the constructor, to initialize the newly added object:

            _textToSpeak = new TextToSpeak(); 
            _textToSpeak.OnAudioAvailable +=  _textToSpeak_OnAudioAvailable; 
            _textToSpeak.OnError += _textToSpeak_OnError; 
            if (_textToSpeak.GenerateAuthenticationToken("Chapter1", "API_KEY_HERE")) 

After we have created the object, we hook up the two events to event handlers. Then we generate an authentication token, specifying the application name and the API key for the Bing Speech API. If that call succeeds, we generate the HTTP headers required.

We need to add the event handlers, so create the method called _textToSpeak_OnError first:

            private void _textToSpeak_OnError(object sender, AudioErrorEventArgs e) 
                StatusText = $"Status: Audio service failed -  {e.ErrorMessage}"; 

It should be rather simple, just to output the error message to the user, in the status text field.

Next, we need to create a _textToSpeak_OnAudioAvailable method:

        private void _textToSpeak_OnAudioAvailable(object sender, AudioEventArgs e) 
            SoundPlayer player = new SoundPlayer(e.EventData); 

Here we utilize the SoundPlayer class from the .NET framework. This allows us to add the stream data directly and simply play the message.

The last part we need for everything to work is to make the call to the SpeakAsync method. We can make that by adding the following at the end of our DetectFace method:

    await _textToSpeak.SpeakAsync(textToSpeak, CancellationToken.None); 

With that in place you should now be able to compile and run the application. By loading a photo and clicking Detect face, you should be able to get the number of faces spoken back to you. Just remember to have audio on!