Call Center First Contact
This sample is a basic mock-up for a call center app that takes a customer's spoken request, converts it to text, translates it to English (if necessary), gauges the emotion behind the text, and then parses it for key phrases. This data could be used to assist in routing the call to a:
- Speaker of the customer's preferred language
- Senior Customer Service Representative to work with an especially upset caller
- Subject matter expert for the subject of the call
This project framework provides the following features:
- Text translation: Translation of text is provided by Translator Text via JSON returned from a request sent to the Translate method
- Language detection: Language detection of text is provided by Text Analytics via the Microsoft.Azure.CognitiveServices.Language.TextAnalytics NuGet package
- Emotion detection: Emotion underlying text is provided by Text Analytics via the Microsoft.Azure.CognitiveServices.Language.TextAnalytics NuGet package
- Key phrases: Parsing text for key phrases is provided by Text Analytics via the Microsoft.Azure.CognitiveServices.Language.TextAnalytics NuGet package
- Speech-to-text: In the context of the scenario of this sample, where customers are telephoning a call center, the "speech to text" functionality could be handled via any number of methods. For the sake of convenience and simplicity, we are using the built-in voice input features of Windows 10 as a placeholder for those methods.
Due to the use of Windows 10's voice input features, you'll also need to make a few changes to your Windows installation in order to test the sample:
- To test the translation feature, you'll need to install one or more non-English language packs. You can do so by selecting Settings > Time & Language > Region & language, and then Add a language.
- To select the language you'll use when speaking, select Settings > Time & Language > Speech, and then the desired language under the Speech language setting.
- To allow voice input, select Settings > Privacy > Speech, inking, & typing, and then Turn on speech services and typing suggestions. Select Turn on in the confirmation dialog box.
- From a shell or command line:
git clone https://github.com/Azure-Samples/cognitive-services-dotnet-call-center.git
CallCenterSample.slnto open the solution in Visual Studio
- Ensure that the platform the solution is building for is set to
To run the sample, follow these steps:
- Run the project from Visual Studio
- On the main page, click Settings so that you can enter your API keys and region info, and then click Close
- On the main page, click the microphone button so that the app begins listening for speech; when you're done speaking, click the stop button so that the text representation of your speech can be tested for source language (and translated to English if necessary) and emotion, and parsed for key terms and phrases
- Click the reset button to begin the process again