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Roar to explore

Vicky S says "This still-work-in-progress project uses voice search as aÌýway for kids to independently explore content and learn about animals by making their sounds. It also allows us to explore interesting new UI approaches which we think aren't currently being examined by products available on the market todayÌý

Where this came from

This interesting use case for CBeebies came from the Future Media UX&D team. It’s a search tool that allows young children to make the sound of an animal to get content about that animal. For instance, to get lions, roar like a lion.Ìý

R&D got involved to help develop the thinking.Ìý

Why we think this is interesting

Young children find it difficult to use a keyboard and mouse, they can’t easily use a search box and browsing doesn’t scale.

ÌýWe would like to understand if voice search could be a useful navigation tool for kids, and could help them explore content independently.

ÌýThere is a lot of research about voice and speech recognition but not involving kids expressing themselves with sounds, which also makes this work interesting.Ìý

What we’ve done so far

ÌýFeasibility study & demo:ÌýR&D explored the technical feasibility. Chris P, Chris L & Yves built an audio classification system using sample data of 30 children making 12 different animal sounds to see if a computer could be trained to accurately classify the sounds into the 12 classes.

ÌýFindings

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·ÌýÌýÌýÌýÌýÌýÌýÌý ÌýIt is possible to train a classifier to detect animal noises

·ÌýÌýÌýÌýÌýÌýÌýÌý ÌýReal world performance of the system is considerably worse than in the lab.

·ÌýÌýÌýÌýÌýÌýÌýÌý ÌýCareful choice of the algorithms is necessary.

·ÌýÌýÌýÌýÌýÌýÌýÌý Web sites do not have access to the host computer’s microphone by default

UX research:ÌýAs our classifier demo isn’t robust enough to test with kids and the aims of the engineering research are different from the user experience research, we have split UX and engineering into two research tracks.ÌýFor the UX research we are developing ideas for an experience prototype, which aims to test the concept and gain a better understanding of the behaviours and needs of our audience.Ìý

We began with some background research relating to information retrieval and behaviour in young children, and found the following:

·Ìý Young children are easily bored, emotionally driven, drawn to accessible info they understand/ recognize and find it hard to switch cognition between 2 places (i.e. looking at screen/looking at keyboard).

Ìý·ÌýÌýÌýÌýÌýÌýÌýÌý They find metaphorical and highly textual interfaces very difficult.

Ìý·ÌýÌýÌýÌýÌýÌýÌýÌý Formulating a search query is difficult for children, because they have little knowledge to ‘recall’ concepts or terms from their long-term memory.Ìý

·ÌýÌýÌýÌýÌýÌýÌýÌý Young children tend not to plan out their searches but rather react to results they receive from the IR system - behaviour is a conversation. They are easily distracted and their actions are reactions to the information & interface.Ìý

·ÌýÌýÌýÌýÌýÌýÌýÌý Generally, their search strategies are not analytical and do not aim precisely at one goal. Instead, they make associations while browsing. This is a trial-and-error strategy.Ìý

·ÌýÌýÌýÌýÌýÌýÌýÌý They find the home page comforting to start a new journey from – once confidence and familiarity is built with the page.

ÌýWe did some sketching and thinking about how to develop and evaluate an experience prototype, thinking in particular about 3 things:ÌýInitialisation of the task, type of primary feedback and aiding further exploration

Ìý

Pilot study

We ran a quick pilot study with 4 & 5 yr olds, to test a prototype approach and evaluation method and to answer some initial questions.ÌýÌýCan they make the sound of the animal they want to see from a selection on screen?ÌýÌýDo they know (think) they are controlling the device with their voice?Ìý ÌýDo they want to explore further (after the first go) - If it holds their interest or their attention starts to wander.

ÌýWorking with small groups of 2 or 3 children at a time, we showed the children a selection of 4 animals on a TV monitor. Three were recognizable CBeebies characters and one was a generic animal from a live action natural history programme. We asked the children to make the sound of the animal they liked best/wanted to pick.Ìý

We learned that kids interpret the animal sounds quite differently.This has an impact on how the system should be designed to give control to the user to make their own interpretations of sounds, rather than having to learn the ‘correct’ generic sound. That way, the kids can train the system to work for them. ÌýWe also observed that kids touch the screen intuitively – even if the device they are using doesn’t afford touch (I was using a hybrid TV/computer monitor).ÌýFinally, the prototype needs to be very convincing for this audience. They will not suspend disbelief and they are curious about how things work.Ìý

In my test, I initiated the conversation with the children and gave them instructions. For the next iteration of our experience prototype, we would like to try different ways of initialising the task with children. We could ask the parent to direct the child, we could use an avatar to initiate a conversation and ask the child to mimic what they do and we could use a prop that affords sound input like a microphone to see which is most successful.

Ìý

The aim of our research is to understand the following:

Ìý

·ÌýÌýÌýÌýÌýÌýÌýÌý How can we encourage children to use their voice as a controller?

·ÌýÌýÌýÌýÌýÌýÌýÌý Do children understand cause and effect - (that their input has a direct effect on the results)?

·ÌýÌýÌýÌýÌýÌýÌýÌý Where is voice good/ better than other forms of input like touch or gesture?

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Technical considerations & recommendations

Further engineering work that would need to be done beyond the initial feasibility study

·ÌýÌýÌýÌýÌýÌýÌýSingle user classifier

·Ìý Ìý Ìý ÌýImprove acoustic model

·Ìý Ìý Ìý ÌýStudy impact of recording equipment on the result"

dddIn other project news:

Michael S

This week I have been primarily working on debugging and making sustainable

the social bookmarks system - ie twitter harvesting and /programmes correlation.

Whilst looking at throughput numbers, I've noticed that there are 100,000

tweets per day for Ö÷²¥´óÐã national TV and radio stations, and 75,000 of those

per day correlate back to specific times in specific programmes.

Chris Needham

Attended an HTML5 event at Google on Thursday, learning about WebRTC (), WebGL (), and Web Intents ().Ìý

Prepared a presentation for the FI-Content plenary meeting that we are hosting.

Olivier

Web Audio standards: the W3C working group has been very active thisÌýweek, talking about expanding its scope to look at standardising MIDI inÌýthe browser, exchanging thoughts and feedback about the specs.ÌýMeanwhile, our project to start a Ö÷²¥´óÐã-centric prototype which will testÌýand stretch the APIs got the green light, and we (ChrisL, Matt and I)Ìýwill be starting work in earnest next week

Vicky B

This week I've been continuing to analyse the data from the NoTube 'Social Web and TV' survey,Ìý and using the initial findings to structure a user research workshop which will explore various themes around NoTube's Beancounter user profiling service () in more depth. The survey is still open if you'd like to be part of our research:

Andrew N

This week Andrew's been continuing work on the FI-Content dashboard including trying to diagnose a problem that was causing it to crash Safari. It turned out it was due to the Ö÷²¥´óÐã network which made him sad.ÌýAt Google's HTML5 day Web Intents () looks very promising as a mechanism for decoupling common web actions e.g. "share this page" with the web service that performs it. If it takes off, it's another step towards a more flexible web of loosely connected 'apps'.ÌýInteresting link:Ìý"The Web Is a Customer Service Medium"Ìý

Thought-provoking essay dismisses the notion of the web as a meta-medium that mimics TV, radio, print and asks "what is the question that the web as a medium is answering?"

Pete

Last Wednesday through Friday, I was helping oversee the Fusion Trainee Lab 2012 at Ö÷²¥´óÐã Academy: a brief was set on Wednesday and presented back Friday afternoon to the commissioners. As a mentor, I encouraged the teams to focus their ideas thinking, gave them tips around developing clear solutions and showed them ways to communicate their propositions simply and clearly.

FI Content: This week I have been guiding the development of the Dashboard, helping clarify the script for the lab study sessions next week and designing TV interface mockups to show the participants.

Yves

We ended our third work package this week, so we spent a bit of time writing deliverables and preparing for the review meeting, which went very well. I have been working this week on quick prototype to expose all the data we have generated within ABC-IP so far, which will hopefully become the basis for the UX work we are doing right now. The prototype is now mostly done, using Rails on top of a triple store accessed via SPARQL, and using RedStore for tests. I packaged all I needed for that prototype in my PPA (Ìý)

Meeting with I&A people to talk them through the work we've done so far.ÌýÌýLots of review deadlines this week, so I spent some time reviewing papers for various workshops/conferences. Lots of very high quality papers in there - I hope they get through! Giving a Prolog crash-course to the engineering team today - should be fun!Ìý

Chris L

This week Chris has been continuing work on the automatic segmentationÌýinvestigation. The approach he is taking is to determine regions ofÌýsimilarity within a piece of audio using the C99 algorithm (ÌýÌý)and thenÌýevaluate the performance of the algorithm using the WindowDiffÌýmetric ().

Initial results are not encouraging with the C99 algorithmÌýpositing too many segments when compared to the ground truth data. He'sÌýbeen looking at collapsing neighbouring segments if they are shorterÌýthan a certain threshold to see if this improves the performance.Ìý

Jo

Next week we are carrying out user evaluations on attitudes to data privacy with 12 participants, 6 in our London lab, and 6 in our Salford lab. This week we have been preparing the final structure of the sessions, and putting together the materials that the participants will use.Ìý

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