It’s no secret that a large number of companies are trying to re-imagine how to improve their application user experience and build a conversational interface so that the users can interact with their application through voice or text commands.
AWS Lex Ecosystem
Amazon Lex can build conversational using voice and text. Lex uses advanced deep learning techniques like Natural Language Processing (NLP) to understand the meaning of the text and Automatic Speech Recognition (ASR) using which you can convert speech to text. In simple terms, users can create a chatbot of their choice without having any prior knowledge of complex technologies.
Users can build powerful interfaces to use with mobile applications and build highly interactive & conversational user experiences for connective devices in the Internet of Things (IoT). You can also build enterprise chatbots to check sales data, marketing performance & much more.
Benefits of our AWS Lex
Aws Lex also offers an easy-to-use console & predefined bot. Using this you can create your own chatbots just in a few minutes.
Employ advanced deep learning functionalities so, you have to just apply your example phrases and Amazon Lex will train your bot to the next level.
Provide seamless deploying & scaling so, businesses don’t have to worry about scaling your bot for the later applications.
Offers built-in integration with AWS platforms like Lambda, DynomoDB, amazon poly, and many others.
With Lex, you have no upfront costs you have only charged for text or the speech request that you make.
How Amazon Lex Works?
When the chatbot receives an input it either replies with a relevant message or it will complete the desired task for the user.
The Amazon Bot
An artificial intelligence program that simulates an interactive conversation.
An intent represents an action that the user wants to perform for example if you want to order a service then ordering the service is your intent and every intent has a descriptive name. It has utterances which means how you want to convey your intent for example if you want to order a service you can say can I order a service? Or do I want to order a service?
Slots are petameters that intent might require for example if you want to order or buy a service you need to specify a service name, its type, and other specifications that serve nothing but a slot.
Every slot has a slot type; you can go and create a built-in or custom slot type.
For example, if you consider a service type then you have development tools, databases, storage, networking, migration, etc.
It is nothing but how you want to fulfill the intent after the user provides the necessary information.
Complete Solution for Business
Amazon Lex – Features
The latest core feature of Amazon Lex is sentiment analysis which analyzes a piece of text to understand the emotion behind that text to send an appropriate response to the user. It is a machine learning-based feature that is used to analyze the user emotions like anger, happiness, and sadness to understand this concept in AWS let’s first discuss amazon comprehend which is a natural language processing service which is based on machine learning to understand the relationship in textual data, in addition to sentiment analysis. AWS Comprehend can also be used for language detection, Topic modeling, and Key phrases extraction.
Here are some points about more features of Amazon Lex to show its importance for your business:
Text and speech-language understanding: Powered by the same technology as Alexa.
Build once and integrate with multiple platforms.
Designed for builders: efficient and intuitive tools to build conversation; scale automatically.
Enterprise Ready: Scalable, Versioning, and alias support.
Continuous Learning: Monitor and improve your bot.
Amazon Lex Customers
The chatbot feature is used by many organizations to uplift their business and boost their sales. It provides SDKs for Android, and IOS, which support speech and text input.
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Author: Huma Tariq
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