Learn to code in Python: Alexa Skills Workshop

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During my time working at Amazon Alexa, I designed and ran an Alexa Skills workshop to encourage teenagers into coding. This workshop can be adapted to all levels and ages — our youngest participant was 12 — and all you need is a computer with a browser and an internet connection. When you finish, you’ll have an Alexa skill which can tell you facts about famous folk along with some of their quotes.

NB: A more in-depth instruction booklet is available here, from a collaboration with Feminist Internet, which taught undergraduate students to build a skill about famous feminists.

Prerequisites

Each participant should set these up before the workshop:

  • An account on https://developer.amazon.com/ which is where you setup the definition of the Alexa Skill
  • An account on https://aws.amazon.com to write the Lambda function which responds to the Skill
  • A laptop
  • Some way of running Python code — good options are Python in a terminal, Jupyter notebook, or Trinket in the browser
  • An Alexa device (optional as you can use the browser to test)
  • Access to the code — the original open sourced version from Amazon is here on Github, and the latest version that this workshop is based on can be found here
  • If running as a workshop, volunteers who understand Python to help the participants

Schedule

A typical workshop schedule is

  • 1 hour Python introduction (students typically split into groups of 2–3, and work together for the duration of the workshop)
  • Half hour Introduction to Alexa Skills and VUI design
  • 2–3 hours to build and improve an Alexa skill

Python Introduction

The first part of the workshop is an introduction to Python tutorial. This is in the form of a Jupyter notebook and covers some basics of Python which are useful to build the Alexa skill. The code from the tutorial can be run in several ways — one of the easiest is to copy and paste into an online coding platform in your browser like Trinket. It takes about an hour to work through the tutorial with help from some experienced volunteers.

Introduction to Alexa Skills & VUI Design

To design an Alexa Skill, we need to know about some basic concepts — utterances, intents and slots.

An ‘utterance’ is something that someone says — it isn’t necessarily a full sentence as people don’t always speak grammatically. For example:

“Play some music”

“Who is Serena Williams”

“Tell me about London”

When designing a voice interface, the computer has to know what the user asked for, and decide how to reply. Language is complex and ambiguous, so different people ask for the same thing in many different ways. We have to somehow categorise the user’s utterance so we can decide how to reply. An ‘intent’ is the name for a group of utterances which mean the same sort of thing. For example,

PlayMusicIntent

“play some music”

“i want to hear music”

“please make music play”

GetWeatherForecastIntent

“what’s the weather forecast”

“what will the weather be like”

“tell me about the weather”

GetFactIntent

“tell me an interesting fact”

“can i hear a fact”

“i want to know a fun fact”

A ‘slot’ is a specific thing (usually a noun) that the user is asking about, like a music artist, a song name, a city, a time, or a person.

PlayMusicIntent

“play some music by the beatles

“i want to hear hey jude

“please make summertime by nina simone play”

GetWeatherForecastIntent

“what’s the weather forecast tomorrow

“what will the weather be like in london

“tell me about the weather next week in cambridge”

GetFactIntent

“tell me an interesting fact about Mae Jemison

“can i hear a fact about Amelia Earhart

“i want to know a fun fact about london

An utterance can have more than one slot in it. Sometimes the same words can be a different type of slot in different utterances, e.g. “play the song new york” vs “what’s the weather in new york “.

Alexa Skill Building

We use the basic Alexa skill from the workshop Github repository as the basis for the skill building. This is a fully working skill, which can be built by the participants and then improved. The instructions below are minimal — there’s full documentation for setting up a skill at Amazon but get in touch if you need more help. The goal is to setup both an Alexa Skill and a Lambda function, and have them talk to each other.

Our example skill has three intents:

  • saySomethingIntent
  • personalFactIntent
  • giveMeQuoteIntent

The skill in the Github repository has several files which are used in https://developer.amazon.com/ to build the Alexa skill. Most of the information from Github is copied and pasted into the skill development interface:

  • The list of example utterances for the skill in utterances.txt
  • A list of people names for the slot “ Person” in LIST_OF_PERSON
  • A list of subjects for the slot “ Subject” in LIST_OF_SUBJECT
  • The intent schema in intent_schema.json — this lists the three intents for this skill with some information about the slots in each, in a computer readable json format. From this file we only need the names of the intents.

The repository also has the code for the Lambda function in lambda_function.py. This code is setup in a Lambda function on https://aws.amazon.com, and it composes the skill’s response to the three intents. This is where participants will begin to make changes to see what they can change.

Once the skill and the lambda function are both setup and talking to each other, it’s possible to test the skill in the skill developer interface or on an Alexa device that’s connected to your Amazon account.

Extensions

Some ideas for improving the skill during the workshop are:

  1. Change the output of saySomethingIntent so that Alexa’s response changes
  2. Look for the get_person_fact() function and try adding information about some more people
  3. Look for the get_quote() function and try adding some extra quotes for each topic
  4. Try adding a new topic that you can ask for quotes about
  5. Invent a new intent and add it to both the skill and the lambda function code

If you run this workshop, let me know how you get on!

Originally published at https://www.catherinebreslin.co.uk.

Machine Learning scientist & consultant :: voice and language tech :: powered by coffee :: www.catherinebreslin.co.uk

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