AWS Machine Learning Blog

Category: Amazon Lex

Building natural conversation flows using context management in Amazon Lex

Understanding the direction and context of an ever-evolving conversation is beneficial to building natural, human-like conversational interfaces. Being able to classify utterances as the conversation develops requires managing context across multiple turns. Consider a caller who asks their financial planner for insights regarding their monthly expenses: “What were my expenses this year?” They may also […]

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AWS expands language support for Amazon Lex and Amazon Polly

At AWS, our mission is to enable developers and businesses with no prior machine learning (ML) expertise to easily build sophisticated, scalable, ML-powered applications with our AI services. Today, we’re excited to announce that Amazon Lex and Amazon Polly are expanding language support. You can build ML-powered applications that fit the language preferences of your […]

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Intelligently connect to customers using machine learning in the COVID-19 pandemic

The pandemic has changed how people interact, how we receive information, and how we get help. It has shifted much of what used to happen in-person to online. Many of our customers are using machine learning (ML) technology to facilitate that transition, from new remote cloud contact centers, to chatbots, to more personalized engagements online. […]

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Building a real-time conversational analytics platform for Amazon Lex bots

Conversational interfaces like chatbots have become an important channel for brands to communicate with their customers, partners, and employees. They offer faster service, 24/7 availability, and lower service costs. By analyzing your bot’s customer conversations, you can discover challenges in user experience, trending topics, and missed utterances. These additional insights can help you identify how […]

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Expanding Amazon Lex conversational experiences with US Spanish and British English

Amazon Lex provides the power of automatic speech recognition (ASR) for converting speech to text, along with natural language understanding (NLU) for recognizing user intents. This combination allows you to develop sophisticated conversational interfaces using both voice and text for chatbots, IVR bots, and voicebots. This week, we’re announcing Amazon Lex support for British English […]

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Creating a sophisticated conversational experience using Amazon Lex in Australian English

Amazon Lex is a service for building conversational interfaces into any application using voice and text. To build truly engaging conversational experiences, you need high quality speech recognition and natural language understanding that understands the intent of the customer accurately. We are excited to announce that Amazon Lex now supports Australian English. With Australian English, […]

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Announcing the express testing capability in Amazon Lex

Amazon Lex now provides the express testing capability on the AWS Management Console to expedite building your chatbot. You can start testing your bot soon after you initiate the build process without having to wait for the entire build to complete. You can use the new testing option to check the basic interaction elements such […]

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How Citibot’s chatbot search engine uses AI to find more answers

Citibot is a technology company that builds AI-powered chat solutions for local governments such as Fort Worth, Texas; Charleston, South Carolina; and Arlington, Virginia. With Citibot, local residents can quickly get answers to city-related questions, report issues, and receive real-time alerts via text responses. To power these interactions, Citibot uses Amazon Lex, a service for building conversational interfaces for text and voice applications. Citibot built the chatbot to handle basic call queries, which allows government employees to allocate more time to higher-impact community actions.

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Build more effective conversations on Amazon Lex with confidence scores and increased accuracy

In the rush of our daily lives, we often have conversations that contain ambiguous or incomplete sentences. For example, when talking to a banking associate, a customer might say, “What’s my balance?” This request is ambiguous and it is difficult to disambiguate if the intent of the customer is to check the balance on her […]

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Create a multi-region Amazon Lex bot with Amazon Connect for high availability

AWS customers rely on Amazon Lex bots to power their Amazon Connect self service conversational experiences on telephone and other channels. With Amazon Lex, callers (or customers, in Amazon Connect terminology) can get their questions conveniently answered regardless of agent availability. What architecture patterns can you use to make a bot resilient to service availability issues? In this […]

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