Hello everyone. My name is Suzanne Tolmeijer and welcome to our presentation
Female by Default? - Exploring the Effect of Voice Assistant
Gender and Pitch on Trait and Trust Attribution
Most leading voice assistants today are either exclusively female or female-by-default.
However, a recent report by UNESCO found that this perpetuates harmful gender stereotypes.
So what if instead of the voice being exclusively female, it can also be male,
Or maybe even that it's indistinguishable which gender the voice has.
In order to research this, we looked at the gender of a voice assistant
by manipulating the pitch of the voice,
to see how this would influence the perceived traits that the users felt the VA had,
how it influences the trust that they form towards the system
and also whether the perceived traits and trust actually depend
on the type of task that the user is doing with the VA.
In order to research this, we created five different voices
using a state-of-the-art text-to-speech tool by Google
called WaveNet.
The first voice that we have is a female high voice, which sounds like this:
"This is the high female voice."
We have a female low voice:
"This is the low female voice."
A male high voice:
"This is the high male voice."
A male low voice:
"This is the male low voice"
And finally, we created a gender-ambiguous voice by taking a gendered voice
and manipulating it until in a pretest participants couldn't agree
whether the voice was male or female.
It sounded like this:
"This is the gender-ambiguous voice."
Additionally, we created two types of tasks.
The first was an assistance task where the user had to book a flight with the help of the VA.
The second was a compliance task where the VA asked questions to the user
and the user could choose to answer or not.
In order to measure perceived traits and stereotype activation,
we used Bem's sex role inventory.
In order to measure trust, we used a validated trust scale.
For our design, we used a five by two between subjects design,
meaning that each participant got one type of voice with one type of task.
We had 234 participants that we recruited on crowdsourcing platform Prolific.
Now on to the results. First of all, we found evidence of indirect stereotype activation.
If it would have been direct, we would have expected, for example, people to say
that the male low voice sounds stereotypically male.
While we did not find that, we did find that only for the male low voice
people said that it's not NOT stereotypically male.
In other words, it's a double negation rather than a confirmation,
meaning that it's indirect rather than direct stereotype activation.
Secondly, we found that the gender of the user influences their perception.
Specifically, we found that female participants found the gender-ambiguous voice
significantly more friendly and polite than the male users.
Interestingly, we found equal values of reported trust.
In other words, the gender of the voice did not influence
the trust that the user had in the system.
And finally, we found that task context actually influences the perception of people.
Specifically, we found that for the female and the gender-ambiguous voice
the trust placed in them depended on the task
and for the male voice and the gender-ambiguous voice,
the level of perceived male traits depended on the task.
So for future work, we foresee first of all that more research is needed
on the interaction between pitch of the voice and other voice features
to see how this influences perception.
Also more research is needed on the gender-ambiguous voice.
While on the one hand, we got great results that trust did not diminish
when it was unclear what the gender was,
it also seemed that the gender-ambiguous voice was more sensitive to stereotype activation.
In order to see what the balance of positive and negative sides of this voice is,
more research is needed on it.
However, to be able to do that, we'll actually need a text-to-speech tool
that is able to create a gender-ambiguous voice,
since currently, this is not available and we had to take a gendered voice and manipulate it.
Rather, it would be better for the community if we have an inclusive design
where we try to be aware of bias by also offering a gender-ambiguous voice.
And with that, I'd like to that you for coming to our presentation
If you have any further questions, please feel free to contact any of us
and I hope you enjoy your time at CHI.