Update v4/examples/aiVoiceAgents.mdx

Co-authored-by: Jonathan Irwin <[email protected]>

v4/examples/aiVoiceAgents.mdx

@@ -6,8 +6,8 @@ description: "Deploy a real-time AI voice agent"
 In this tutorial, I am going to create a real-time voice agent that can respond to any query via speech, in speech, in ~500ms. This is an extremely flexible implementation where you have the
 ability to swap in any LLM's or Text-to-speech (TTS) model of your liking. This is extremely useful for use cases involving voice such as customer support bots and receptionists.
 
-In order to create this application, we use the [PipeCat](https://www.pipecat.ai/) framework that takes care of stringing together all these components as well as handles some of the functionality we
-might need such as handling user interuptions, dealing with audio data etc. We will show this functionality by joining a meeting room with our voice agent using [Daily](https://daily.co) (the creators of Pipecat) and will deploy this application on Cerebrium to show how it handles deploying and scaling our application seamlessly.
+To create this application, we use the [PipeCat](https://www.pipecat.ai/) framework that takes care of stringing together all the components and it handles some of the functionality we
+might need such as user interruptions, dealing with audio data etc. We will show this functionality by joining a meeting room with our voice agent using [Daily](https://daily.co) (the creators of Pipecat) and will deploy this application on Cerebrium to show how it handles deploying and scaling our application seamlessly.
 
 You can find the final version of the code [here](TODO)