Posts Tagged ‘watson’

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How to transcribe and analyse a phone call in real-time

Saturday, July 16th, 2022

In this post, I want to share an example of how to stream phone call audio through IBM Watson Speech to Text and IBM Watson Natural Language Understanding services, and show some ideas of what you could use this for.

Let’s start with a demo

That’s what I want to show you how to build.

At a high-level, this is what you will have seen in that video:

1.
Faith made a phone call to a phone number managed by Twilio.

2.
Twilio routed the phone call to me, and I answered the call.

We then started talking to each other. And while we were doing this:

3.
Twilio streamed a copy of the audio from the phone call to a demo Node.js app

4.
The Node.js app sent audio to the Watson Speech to Text service for transcribing.

5.
Watson Speech to Text asynchronously sent transcriptions to the Node.js app as soon as they were available.

6.
The app then submitted the transcription text to Watson Natural Language Understanding for analysis.

7.
All of this – the transcriptions and analyses – were displayed on the demo web page.

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Building a Question Answering game in Scratch

Saturday, April 17th, 2021

I added a new project worksheet to Machine Learning for Kids today.

It has step-by-step instructions for how to make a quiz show game in Scratch that uses a machine learning model to understand questions on any topic the student chooses, and find the answer in Wikipedia pages.

It’s a fun little project, super simple to make, and works surprisingly well. It doesn’t get every question right, but it does a lot better than I expected.

I don’t normally write blog posts when I write new ML for Kids worksheets, but this one was a bit interesting.

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Teaching artificial intelligence using Scratch

Friday, May 18th, 2018

This is a recording of a talk I did at DevoxxUK last week. Devoxx is a community developer event, run in London. I had 50 minutes to talk about what I’m doing with Machine Learning for Kids.

Groups like Code Club, CoderDojo, Code.org and many others are doing amazing work in helping to introduce kids to coding. Initiatives like Hour of Code have highlighted how those of us in tech can help to support and inspire the next generation of developers.

How can we extend this to include artificial intelligence and machine learning?

How can we use the cloud-based machine learning APIs that are increasingly available to us as developers to extend the tools used to teach kids about coding?

In this session, I’ll share the work I’ve been doing to introduce machine learning to kids, and demo the resources that are available to give kids hands-on experiences at training and using machine learning models for themselves.

If you’re familiar with AI and ML technologies, this session will hopefully enable you to share your expertise with local schools, colleges and coding groups.

If you’re not as familiar with ML, this session will show you how quick and simple cloud-based machine learning APIs are today, and perhaps inspire you to use them in your next project.

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How I ended up making MachineLearningForKids

Sunday, October 29th, 2017

I write a lot about what I’m doing with machine learning for kids, but in this post, I want to share a little about how I ended up doing it and why.

I tend to write about *what* I’ve done. I rarely write how things happened though, or what made me do them. I just assume that people would be less interested in that.

But, if I think about what I find interesting, it tends to be the backstory to projects. To use Nick as an example, I’ve seen him give loads of talks about Node-RED. And I’ve enjoyed the ones where he talks about how Node-RED happened more than where he gives demos of what Node-RED is.

Inspired by that, I thought I should at least try to capture a few breadcrumbs for how I ended up where I am now with machinelearningforkids.co.uk.

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Machine Learning for Kids event at Hursley

Wednesday, August 30th, 2017

On Tuesday, a couple of dozen children (aged 8-14) spent the afternoon at Hursley so I could give them an intro to machine learning using some of the activities I’ve written for machinelearningforkids.co.uk.

I think it went pretty well, so I thought it’d be good to share what we did.


This was what the room looked like before the kids arrived… with just my two kids helping me set up. It all got a lot busier after this!

The general approach was letting them all work at computers, guided by a worksheet to build something that illustrated an aspect of machine learning. And then following this with a group discussion to draw out what they observed and what it meant.

We did this all together for the first couple of activities. Because of the large age range in the group, after this I let them split up and tackle different activities at different speeds, and followed this up by discussing their projects with them in smaller groups.

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Introducing Machine Learning to kids

Tuesday, July 4th, 2017

Today, I was helping out with a Computing summer school for teachers in London.

As part of this, I gave a presentation about machine learning to a room full of school teachers – about what it is, why I think we should be introducing it in the classroom, and how I think we could do that.

My slides are on Slideshare, but they might not make a lot of sense by themselves, so I’ll jot down here roughly what I said.

slide 1

This morning I want to talk to you about machine learning. In particular, I want to talk with you about machine learning in the context of education and how it could be introduced in the classroom.

slide 2

I’m going to try and cover three main points.

Firstly, a quick level set on what I mean by machine learning.
Then I’d like to talk about why I believe it’s important that we do this.
Finally, I want to talk about the practicalities of how we could effectively introduce machine learning in an accessible way.

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I-Spy (using Watson services from Scratch projects)

Wednesday, February 22nd, 2017

It’s half-term week, so that means more time for geekiness with the kids.

This is something Grace made this week: a game of “I spy” built using Scratch, that uses the Watson Vision Recognition API to let the game dynamically pick objects that it recognises in photos, so you can then make guesses.

Apart from being a fun game to make in it’s own right, I wanted to share why I particularly think it’s useful to be able to use Watson API’s from Scratch projects.

Screen Shot 2017-02-22 at 13.43.53

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Owlbot: Faith’s first chatbot (and barcamp)

Sunday, November 13th, 2016

For her talk at Barcamp Southampton yesterday, Faith did a presentation on owls, together with a chatbot she trained to answer questions about owls.

I’ve brought Grace to a couple of barcamps with me before: Barcamp Berkshire and Barcamp Bournemouth. But this was Faith’s first time.

She decided that she wanted to do a talk on owls. That wasn’t a big surprise… she’s a little bit obsessed with owls.

Some of Faith's owls

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