The transcribe button is not currently operational, but you’ll use this later to kick off a transcription of the selected recording. The detail controller will then let you play the audio file, recited by none other than our very own DJ Sammy D! Build and run and you’ll see the bones of the app.įrom the master controller, you can select a song. Choose your development team from the drop-down.Ĭonnect an iOS 10 (or later) device and select it as your run destination in Xcode. Select the project file, the Gangstribe target and then the General tab.

Open Gangstribe.xcodeproj in the starter project folder for this speech recognition tutorial for iOS. Getting Startedĭownload the sample project here. The Speech Recognition framework doesn’t work in the simulator, so be sure to use a real device with iOS 10 (or later) for this speech recognition tutorial for iOS. This session video explains many of the systems and terminology we’ll use in this speech recognition tutorial for iOS. The 2014 WWDC session AVAudioEngine in Practice is a great intro to this, and can be found at /28tATc1. If you haven’t used AVAudioEngine before, you may want to familiarize yourself with that framework first. The section on live recordings will use AVAudioEngine. It will also get users in the mood to record their own rap hits with a live audio transcriber that draws emojis on their faces based on what they say. In this speech recognition tutorial for iOS, you’ll build an app called Gangstribe that will transcribe some pretty hardcore (hilarious) gangster rap recordings using speech recognition.

You could also create an app that could automatically transcribe audio from Simpsons episodes so you could search for your favorite lines. For example, you could create an app that takes a photo when you say “cheese”. Speech Recognizer creates some truly amazing possibilities in your apps. This lets you react to voice input very quickly, regardless of context, unlike Keyboard Dictation, which is tied to a specific input object. It even adapts results to the user using information about their contacts, installed apps, media and various other pieces of data.Īudio fed to a recognizer is transcribed in near real time, and results are provided incrementally. The engine is fast and accurate and can currently interpret over 50 languages and dialects.

Speech to text api example