Exercise - Create a single-shot recognition speech to text application

• 10 minutes

In this exercise, you'll create an application that uses single-shot recognition to transcribe a sample audio file that you'll download.

Create your speech to text application

1. In the Cloud Shell on the right, create a directory for your application, then change to your new directory:

   mkdir speech-to-text
   cd speech-to-text
   

2. Create a new .NET Core application:

   dotnet new console
   

   This command should take a few seconds to complete.

3. When your .NET Core application has been created, add the Speech SDK package to your application:

   dotnet add package Microsoft.CognitiveServices.Speech
   

   This command should take a few seconds to complete.

Download a WAVE file for recognition

In the Cloud Shell on the right, run the following command to download a sample WAV file that contains a series of quotes from William Shakespeare's play "As You Like It."

curl -L https://aka.ms/ShakespeareWAV -o Shakespeare.wav

You'll use this WAV file for the application in this exercise and the application in the next exercise.

Add the code for your text to speech application

1. In the Cloud Shell on the right, open the Program.cs file:

   code Program.cs
   

2. Remove all the existing code and add the following using statements, which enable the Azure AI Speech APIs for your application:

   using System.Text;
   using Microsoft.CognitiveServices.Speech;
   using Microsoft.CognitiveServices.Speech.Audio;
   

3. Add the following code, which uses Azure AI Speech APIs to convert the contents of the WAV file that you created earlier to create a text file with the transcribed speech. Replace the azureKey and azureLocation values with the values you copied in the last exercise.

   string azureKey = "ENTER YOUR KEY FROM THE FIRST EXERCISE";
   string azureLocation = "ENTER YOUR LOCATION FROM THE FIRST EXERCISE";
   string textFile = "Shakespeare.txt";
   string waveFile = "Shakespeare.wav";
   
   try
   {
       FileInfo fileInfo = new FileInfo(waveFile);
       if (fileInfo.Exists)
       {
           Console.WriteLine("Speech recognition started.");
           var speechConfig = SpeechConfig.FromSubscription(azureKey, azureLocation);
           using var audioConfig = AudioConfig.FromWavFileInput(fileInfo.FullName);
           using var speechRecognizer = new SpeechRecognizer(speechConfig, audioConfig);
           var result = await speechRecognizer.RecognizeOnceAsync();
   
           FileStream fileStream = File.OpenWrite(textFile);
           StreamWriter streamWriter = new StreamWriter(fileStream, Encoding.UTF8);
           streamWriter.WriteLine(result.Text);
           streamWriter.Close();
           Console.WriteLine("Speech recognition stopped.");
       }
   }
   catch (Exception ex)
   {
       Console.WriteLine(ex.Message);
   }
   

   This code uses your key and location to initialize a connection to Azure AI Speech. It then reads the contents of the WAV file that you downloaded, then uses the RecognizeOnceAsync() method of the SpeechRecognizer to convert the audio to text, then it uses a stream writer to save the results to a text file.

4. When you've finished adding all of the code, your file should resemble the following example:

   using System.Text;
   using System.Threading.Tasks;
   using Microsoft.CognitiveServices.Speech;
   using Microsoft.CognitiveServices.Speech.Audio;
   
   string azureKey = "ENTER YOUR KEY FROM THE FIRST EXERCISE";
   string azureLocation = "ENTER YOUR LOCATION FROM THE FIRST EXERCISE";
   string textFile = "Shakespeare.txt";
   string waveFile = "Shakespeare.wav";
   
   try
   {
       FileInfo fileInfo = new FileInfo(waveFile);
       if (fileInfo.Exists)
       {
           Console.WriteLine("Speech recognition started.");
           var speechConfig = SpeechConfig.FromSubscription(azureKey, azureLocation);
           using var audioConfig = AudioConfig.FromWavFileInput(fileInfo.FullName);
           using var speechRecognizer = new SpeechRecognizer(speechConfig, audioConfig);
           var result = await speechRecognizer.RecognizeOnceAsync();
   
           FileStream fileStream = File.OpenWrite(textFile);
           StreamWriter streamWriter = new StreamWriter(fileStream, Encoding.UTF8);
           streamWriter.WriteLine(result.Text);
           streamWriter.Close();
           Console.WriteLine("Speech recognition stopped.");
       }
   }
   catch (Exception ex)
   {
       Console.WriteLine(ex.Message);
   }
   

   Make sure that you update the values for the azureKey and azureLocation variables with your key and location from the previous exercise.

5. To save your changes, press Ctrl+S to save the file, and then press Ctrl+Q to exit the editor.

Run your application

1. To run your application, use the following command in the Cloud Shell on the right:

   dotnet run
   

2. If you don't see any errors, your application has run successfully, and you should see the following responses displayed:

   Speech recognition started.
   Speech recognition stopped.
   

3. Run the following command to get a list of files in the directory:

   ls -l
   

   You should see a response like the following example, and you should see the Shakespeare.txt in the list of files:

   drwxr-xr-x 3 user   user     4096 Oct  1 11:11 bin
   drwxr-xr-x 3 user   user     4096 Oct  1 11:11 obj
   -rw-r--r-- 1 user   user     1476 Oct  1 11:11 Program.cs
   -rw-r--r-- 1 user   user       98 Oct  1 11:11 Shakespeare.txt
   -rwxr-xr-x 1 user   user   978242 Oct  1 11:11 Shakespeare.wav
   -rw-r--r-- 1 user   user      348 Oct  1 11:11 speech to text.csproj
   

   You'll notice that the size of the text file is small; in this example, it's only 98 bytes.

4. To view the contents of the Shakespeare.txt file, use the following command:

   cat Shakespeare.txt
   

   You should see a response like the following example:

   The following quotes are from Act 2, scene seven of William Shakespeare's play as you like it.
   

   If you listened to the sample WAV file, you'd notice that this text is only the first few seconds of the audio. Because we used the RecognizeOnceAsync() method of the SpeechRecognizer, the speech to text recognition stopped when the speaker paused.

In the next exercise, you'll learn how to continue the speech to text recognition for the entire audio file.