Voice
artificial
intelligence
(AI)
technology
becomes
increasingly
common
in
everyday
life,
for
example,
automated
phone
services,
voice
assistive
systems
(e.g.,
Siri),
and
social
chat
bots.
However,
most
research
has
focused
on
how
younger
adults
perceive
modern
AI
speech,
leaving
the
development
of
this
age-uninformed.
Recent
work
indicates
that
older
are
less
able
to
identify
speech
compared
adults,
but
underlying
causes
unclear.
The
current
study
with
(N=133;
22-39
years)
(N=146;
54-79
investigated
potential
factors
could
explain
age-related
reduction
identification.
In
Experiment
1,
we
whether
high-frequency
information
–
which
have
access
due
hearing
loss
contributes
age-group
differences,
our
results
showed
were
both
full-bandwidth
above
4
kHz
was
removed.
This
result
makes
contribution
likely.
2,
known
ability
process
prosodic
predicts
Indeed,
greater
individuals
who
also
a
emotions
from
information,
after
accounting
function
self-rated
experience
systems.
suggest
is
related
accurate
processing
information.
Food Quality and Preference,
Journal Year:
2024,
Volume and Issue:
116, P. 105149 - 105149
Published: Feb. 27, 2024
A
study
designed
to
investigate
the
ability
of
individuals
differentiate
between
AI-generated
and
authentic
food
images,
as
well
impact
disclosing
this
information
on
consumer
perception
appeal
these
images
is
reported.
Two
online
experiments
were
conducted
with
real
stretching
across
unprocessed,
processed,
ultra-processed
continuum.
Study
1
was
assess
accuracy
which
people
could
identify
while
2
explored
how
disclosure
an
image's
origin
influenced
depicted
food.
The
participants
in
found
it
very
easy
recognize
particularly
case
foods.
Notably,
without
disclosure,
often
preferred.
At
same
time,
however,
that
a
image
genuine
significantly
boosted
its
appeal,
whereas
revelation
had
been
generated
by
AI
mitigated
effect.
These
insights
help
understand
psychology
rapidly-evolving
digital
marketing
landscape,
highlighting
nuanced
effects
technological
advancements
image-generation
human
perception.
Neural
activity
in
auditory
cortex
tracks
the
amplitude-onset
envelope
of
continuous
speech,
but
recent
work
counterintuitively
suggests
that
neural
tracking
increases
when
speech
is
masked
by
background
noise,
despite
reduced
intelligibility.
Noise-related
amplification
could
indicate
stochastic
resonance
–
response
facilitation
through
noise
supports
tracking,
a
comprehensive
account
lacking.
In
five
human
electroencephalography
experiments,
current
study
demonstrates
generalized
enhancement
due
to
minimal
noise.
Results
show
(1)
enhanced
for
at
very
high
signal-to-noise
ratios
(~30
dB
SNR)
where
highly
intelligible;
(2)
this
independent
attention;
(3)
it
generalizes
across
different
stationary
maskers,
strongest
12-talker
babble;
and
(4)
present
headphone
free-field
listening,
suggesting
neural-tracking
real-life
listening.
The
paints
clear
picture
enhances
representation
onset-envelope,
contributes
tracking.
further
highlights
non-linearities
induced
make
its
use
as
biological
marker
processing
challenging.
Journal of Speech Language and Hearing Research,
Journal Year:
2025,
Volume and Issue:
68(05), P. 2499 - 2516
Published: April 15, 2025
Speech
is
often
masked
by
background
sound
that
fluctuates
over
time.
Fluctuations
in
masker
intensity
can
reveal
glimpses
of
speech
support
intelligibility,
but
older
adults
have
frequently
been
shown
to
benefit
less
from
than
younger
when
listening
sentences.
Recent
work,
however,
suggests
may
leverage
as
much,
or
more,
naturalistic
stories,
potentially
because
the
availability
semantic
context
stories.
The
current
study
directly
investigated
whether
helps
released
a
fluctuating
(modulated)
more
adults.
In
two
experiments,
we
reduced
and
extended
information
sentence
stimuli
modulated
unmodulated
maskers
for
intelligibility
was
assessed.
We
found
improves
both
Both
age
groups
also
exhibit
better
an
(stationary)
masker,
compared
Semantic
amplified
gained
glimpses,
there
no
indication
amplification
led
greater
If
anything,
benefitted
more.
results
suggest
deficit
masking-release
generalizes
situations
which
available.
That
previous
research
during
story
other
factors,
such
thematic
knowledge,
motivation,
cognition,
amplify
under
conditions.
Deleted Journal,
Journal Year:
2024,
Volume and Issue:
6(2), P. 667 - 684
Published: June 13, 2024
Using
naturalistic
spoken
narratives
to
investigate
speech
processes
and
comprehension
is
becoming
increasingly
popular
in
experimental
hearing
research.
Yet,
little
known
about
how
individuals
engage
with
story
materials
listening
experiences
change
age.
We
investigated
absorption
the
context
of
stories,
explored
predictive
factors
for
engagement,
examined
utility
a
scale
developed
written
assess
auditory
materials.
Adults
aged
20–78
years
(N
=
216)
participated
an
online
study.
Participants
listened
one
ten
stories
intended
be
engaging
different
degrees
rated
terms
enjoyment.
ages
similarly
absorbing
enjoyable.
Further,
higher
mood
scores
predicted
enjoyment
ratings.
Factor
analysis
showed
items
approximately
grouped
according
original
dimensions,
suggesting
that
may
similar
although
certain
discriminated
less
effectively
between
more
or
engaging.
The
present
study
provides
novel
insights
into
adults
supports
using
stimuli
Speech Language and Hearing,
Journal Year:
2024,
Volume and Issue:
unknown, P. 1 - 18
Published: July 7, 2024
Assessment
of
speech
intelligibility
in
noise
is
critical
for
measuring
the
impact
age-related
hearing
loss.
However,
quantifying
often
requires
a
human
to
manually
process
responses
provided
by
participant
or
patient
obtain
speech-intelligibility
score
–
typically
proportion
correctly
heard
words.
This
manual
can
be
time-consuming
and
thus
costly.
The
current
study
investigates
whether
state-of-the-art
Natural
Language
Processing
(NLP)
models
from
Google
OpenAI
could
used
calculate
scores
as
an
alternative
scoring.
It
was
specifically
tested
NLP
capture
common
speech-in-noise
perception
phenomena
younger
older
adults
(N
=
144)
listening
masked
modulated
unmodulated
babble
noise.
results
show
that
closely
matched
scorer
(r
∼0.95).
main
difference
is,
on
average,
∼2%
underestimation
relative
moderate
high
signal-to-noise
ratios.
participants
making
minor
errors
related
misspellings,
gender,
tense,
which
are
sensitive,
but
scorers
correct
prior
Critically,
known
reduction
benefit
masker.
OpenAI's
ADA2
appears
perform
best
out
models,
showing
no
compared
suggests
modern
data.
Heliyon,
Journal Year:
2025,
Volume and Issue:
11(2), P. e42083 - e42083
Published: Jan. 1, 2025
Sentence
stimuli
pervade
psycholinguistics
research.
Yet,
limited
attention
has
been
paid
to
the
automatic
construction
of
sentence
stimuli.
Given
their
linguistic
capabilities,
this
study
investigated
efficacy
ChatGPT
in
generating
and
AI
tools
producing
auditory
In
three
psycholinguistic
experiments,
examined
acceptability
validity
AI-formulated
sentences
written
one
two
languages:
English
Arabic.
Experiment
1
3,
participants
gave
AI-generated
similar
or
higher
ratings
than
human-composed
2,
Arabic
received
lower
counterparts.
The
AI-developed
relied
on
design,
with
only
2
demonstrating
target
effect.
These
results
highlight
promising
role
as
a
developer,
which
could
facilitate
research
increase
its
diversity.
Implications
for
were
discussed.
Audiology Research,
Journal Year:
2025,
Volume and Issue:
15(1), P. 14 - 14
Published: Feb. 8, 2025
Background/Objectives:
Voice
artificial
intelligence
(AI)
technology
is
becoming
increasingly
common.
Recent
work
indicates
that
middle-aged
to
older
adults
are
less
able
identify
modern
AI
speech
compared
younger
adults,
but
the
underlying
causes
unclear.
Methods:
The
current
study
with
and
investigated
factors
could
explain
age-related
reduction
in
identification.
Experiment
1
whether
high-frequency
information
speech—to
which
often
have
access
due
sensitivity
loss
at
high
frequencies—contributes
age-group
differences.
2
an
ability
process
prosodic
predicts
Results:
Results
for
show
both
full-bandwidth
above
4
kHz
removed,
making
contribution
of
hearing
unlikely.
shows
greater
individuals
who
also
a
emotions
from
information,
after
accounting
function
self-rated
experience
voice-AI
systems.
Conclusions:
results
suggest
related
accurate
processing
information.