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You can also rename it to something nicer if you wish! Follow the same steps as before to enable the Cloud Text-to-Speech API as well. Make sure you save the credentials file to somewhere in your XSA application so that you can use it later.
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The nice thing is that when you make a new account, you get $300 free credit to use their services! Once you have an account, you can follow the steps at this link to set up a new project, enable Cloud Speech API, connect it to a service account, and download the credentials file. For my demo in this blog, I am going to use GCP!īefore you can start, you need to sign up for GCP if you don’t already have an account. You are welcome to check out the other API providers since some of them might suit your needs better. The documentation for GCP APIs is also quite easy to navigate and understand. It just requires you to have all your credentials accessible in a JSON file. You do not need to deal with authorization tokens or API keys or anything. The client also handles security for all HTTP and web socket communication itself. I have personally worked with Microsoft, IBM, and GCP, and would recommend GCP as it comes with a python client which makes programming much simpler. There are various API providers you can choose from for speech-to-text and text-to-speech processing including Amazon Web Services (AWS), Microsoft Azure, IBM Watson, and Google Cloud Platform (GCP). Once the required actions are completed, the back-end can synthesize an audio response using a text-to-speech API and send that back as voice feedback for the user. This transcript is analyzed using Natural Language Processing tools, yielding commands that can be executed. The back-end module then sends the audio stream to the speech-to-text API which responds with the transcript. If that is not the case, please refer to my first few blogs to be up-to-speed with everything!įor making voice-enabled web applications, the development workflow in general involves configuring a microphone on the front-end browser to capture audio stream from the user, encoding the stream to a valid audio format for the speech recognition API and transferring it to the back-end module.
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I am going to assume you know how to set up a basic python XSA application. Not to mention, conversational interfaces have become very common in commercial applications, it is about time they make their way into enterprise applications as well! Getting Started In addition, voice commands and audio playback options come in very handy when saying is much easier than typing, or worse, selecting from long menus. This helps diversify the user interface allowing users greater flexibility for input options. With rapid growth in speech analysis and audio processing technology, it has become much easier for developers to incorporate conversational interfaces in their applications. In addition, the Server can also initiate communication with the client and send updates as opposed to simple HTTP where a client must always initiate communication often leading to polling interfaces. They do not need to make explicit HTTP calls to check for status updates. Numerous clients can be connected to the same server through which they receive live updates as events. For those that are not familiar, web sockets are used for live bi-directional communication between clients and a server. I am also going to briefly cover how web sockets work in python for XSA applications. It’s Subhan here with another exciting episode of developing in python with XSA! In this blog, I am going to talk about how to build conversational interfaces in XSA applications by integrating speech-to-text and text-to-speech APIs.