Alexa Book 2: Peak Oil (Alexa - The Series)

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  2. Alexa Brazilian
  3. Alexa : Book 2 : Peak Oil
  4. Werner Vogels' weblog on building scalable and robust distributed systems.
  5. New Ways to Discover and Use Alexa Skills - All Things Distributed

When the service completes, it responds back to the Alexa skill to allow Alexa to respond back to the user. This will launch a skills wizard.

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The skill name can be any name that will be displayed to customers in the skill store. The invocation name is important. This becomes the verbal trigger of your skill, i. Amazon has standards that apply to invocation names, but also think about the user and how they might easily remember the name of your skill.

Be creative. There will be an application ID — copy this down. This number will be needed when building the Lambda function. The Beta Skill Builder interface makes it easier to build out the intents for an Alexa skill. This is the name of the function call in the AWS Lambda piece that we will create later. For this action, we need to associate a set of utterances that will cause it to trigger and pass in key information the user will say.

Create a number of utterances or phrases that your users will say when using the skill to ask about a particular superhero. Get creative! The concept of slots is a placeholder value when the user asks about a particular hero. Within the utterance text, you can use slots to allow the skill to use that as a sort of validated data field that allows the value to be passed to the Node.

Alexa Brazilian

Creating a number of utterances in Alexa with the phrase of each character would be a lot of work. This can be numeric, date, times, lists or even a customizable list. For the hero names, click Add Intent Slot and give it a name. There is no need to create a custom slot type as we can use the Amazon. FictionalCharacter slot type.

Alexa : Book 2 : Peak Oil

Select the Amazon. Save the skill model, then build it. We will come back to the final configuration of the skill to tie it into the AWS Lambda function. AWS Lambda is a serverless code platform that can deploy and run your code on demand without it running all the time.

It is a great platform for part-time code computations, batch processes, or, in our case, an Alexa skill. There are also tradeoffs based on how often your functions run and the technology language stack you choose. Lambda supports Node. For this example, we will pick Node. The Lambda wizard will prompt you for a set of questions. It is a basic template, and we will replace the template code with our own. Keep the template code for now and skip to giving security access to our Lambda function.

If you have never created an IAM role, it is pretty easy. There are more instructions on how this is done at Setting up your first Lambda Role. Copy this number to add it to your Alexa skill configuration. Add the ARN number to the Alexa skill's configuration page. The number goes into the Global Endpoint default field. This article will not go into a line-by-line tutorial of how to write a Node. The basic code is all available on GitHub. This file can be copied into the Lambda online code editor with the necessary modifications. This is still the case if your applications has additional module dependencies.

Notice that alexa-sdk is imported. If you are creating a clean slate Alexa Lambda function, you will need this one import. The Marvel public and private API keys, which Marvel issues when you sign up for an account, will need to be placed in the appropropriate constant values. This is used by the Alexa handler call to toggle language resources based on the user's origin. For English, the values are defaulted to EN, and any overriding values are specifically declared for that country.

The core of our Alexa Lambda implementation is the handlers.

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Notice in the Alexa interaction model dashboard that the Intent names map to the various handler functions. The following illustrates that the various functions in the handler are mapped to the Amazon intents in the Alexa interaction builder. The handlers are various function calls that the Alexa lifecycle and intents may call. When a user says, "Alexa, open Marvel," for instance, the LaunchRequest will display and emit a response back to Alexa. In this example, it is outputing the welcome message, and some help. The getHeroIntent function call is the main driver of this Alexa skill.

It is also the same name of the intention. Therefore, if the intention in the Alexa skill was named "GetMyHero", then this function call should have the same name. The function gets the value of the slot from the request intent, called heroname. This value is passed to the Marvel REST service to query for characters with a name starting with the value in the heroname slot. The httpGet function call also hashes the public and private key and makes the request, limiting it to only the first Marvel character returned.

Here is the basic code block for the httpGet function call. The final part of the Alexa Node.

Werner Vogels' weblog on building scalable and robust distributed systems.

The Alexa handler also needs the Alexa skill ID that was created in the first step of creating a skill. Finally, we need to register our own handlers to the Alexa handler. The full code is here , and you can copy and paste the index. And so the cloak-and-dagger adventure began. That was only known to one person in the company. The next stage was a series of phone interrogations down the line from California, one from the person leading the project he now knows as Nehal Meshal, cryptically described by the company as a program manager.

It was only when he was selected and turned up again at Freshminds to join seven others, the final team, that he was told the client was Amazon. Not what they had been selected to do. There he was told in detail about the Alexa project, but only after he had signed a non-disclosure agreement. He and his colleagues were to go round the country sampling regional accents so the digital assistant they planned to launch in the UK could understand diverse brogues and respond properly.

We operated from a blacked-out room.

New Ways to Discover and Use Alexa Skills - All Things Distributed

It took them a week to be trained. Voice recognition software works by analysing the airwaves you make when you speak, translating that into digital data. Samples of the waves are taken at frequent intervals — hundredths or thousandths of a second — the higher the sampling and precision rates the higher the quality.

These samples of words are then compared with the same words already stored in digital templates and matched, modified, together with other elements of technological wizardry known only to the 1, and more developers who worked on Alexa. The first stop for Thynne and the team was Manchester.

The bloke from Oz, Richard Ingram, was the trailblazer going on ahead to each of the designated cities. There he would book two flats or houses through Airbnb — the group had now been split into two teams of four — and line up participants for the study, who, of course, were not told why they were taking part. Those taking part had been asked to come with the titles of five books, five films and five favourite pieces of music in their heads.

The sessions were in three parts. Finally each participant was asked to ask Alexa their own questions. To simulate a real household environment Thynne and the others would occasionally switch on a TV or a washing machine as the person was speaking. In all there were between and prompts and responses in each session by each one of the more than 1, people taking part, all if it recorded and shipped off to the States.

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After Manchester it was Leeds for two weeks, followed by the fortnight in Glasgow , the same in Birmingham with the last stint back in London. Clearly Amazon were pleased with the result. We may then apply our discretion under the user terms to amend or delete comments. Post moderation is undertaken full-time 9am-6pm on weekdays, and on a part-time basis outwith those hours.