Speech to text – How machines understand human language & respond?
How long it has been when you asked a voice assistant to set a reminder for you or checked the weather with Alexa, Siri or Ok Google? Adobe Analytics study finds that the most common voice activities are asking for music (70%) and the weather forecast (64%) via smart speakers. Other popular activities include asking fun questions (53%), online search (47%), checking the news (46%), basic research/confirming info (35%), and asking directions (34%). The statistics hint that speech to text is becoming more than just a tool used for ease of access, maybe a virtual companion (or encyclopaedia) who knows-it-all!
Its success is based on the simple fact that people find it easier to use voice commands rather than type it all in a search box. It listens, understands and gives you the desired output. But how does it work? Speech recognition is one of the most fascinating topics in AI. It helps to translate the human language into text. Now we can see that speech recognition is used in many day-to-day applications in Banking, Healthcare, Marketing, IoT devices (Internet of Things) etc.
To know how to convert audio to text using Python, read the blog on ‘How to convert speech to Text?’ on IndiaAI. Learn the use of Speech Recognition API and PyAudio library in Python in a step-by-step approach. Understand how ML and Deep neural network models are used for converting voice commands.