Lastly, we need to implement try and exceptblock to handle errors such as when the API is unreachable or unresponsive after sending requests, or when our speech is unrecognizable. To handle ambient noise, you’ll need to use the adjust_for_ambient_noise()method of the Recognizer class in order for the library to recognize your voice.Īfter running the adjust_for_ambient_noise()method, wait for a second and let it analyze the audio source collected in order to handle ambient noise and capture correct speech.
In this implementation, I recorded my voice using own microphone and SpeechRecognizer accessed the microphone (Install PyAudio package to access the microphone) and recognized my voice accordingly.Ĭheck out the code snippet below to understand the full implementation as they are relatively self-explanatory.įunction to recognize speech from microphone
In the following writing, I’ll show you how I implemented this API step-by-step by following the article.īut first, you need to install SpeechRecognitionlibrary using pip install SpeechRecognition.Īnd we can use the Google Web Speech API that comes from this library itself.
To avoid boring you with technical details on how speech recognition works, you can read this great article that talks about the mechanism in general and how to implement the API. Building speech recognition with Python using Google Speech Recognition API (Source) Note that if you’re running an app or a website that’s calling the API consistently, then you may need to consider getting a paid service from either of the APIs above. This fits our use case if we just want to use this API for experimentation purposes. However, the convenience of Google Web Speech API also comes with certain limitations: The API quota for your own keys is 50 requests per day, and there is currently no way to raise this limit. That means you can get started right away without having to get authentication with either an API key or a username/password combination for other APIs.
The answer is that there are also other APIs available either for free or paid services as below: You may be wondering, “Is this the only API available given the growing demand and popularity of speech recognition?”
Instead, I used Google Speech Recognition API to perform the speech-to-text tasks with Python (check out the demo below which I showed you how the speech recognition worked - LIVE!).īy the end of this article, I hope you’ll have a better understanding of how speech recognition works in general and most importantly, how to implement that using Google Speech Recognition API with Python.įeel free to check out the source code here if you’re interested. Therefore, that made me very interested in embarking on a new project to build a simple speech recognition with Python.Īnd of course, I won’t build the code from scratch as that would require massive training data and computing resources to make the speech recognition model accurate in a decent manner. Gary Vaynerchuk: Voice Lets Us Say More Faster