International Journal of Online and Biomedical Engineering (iJOE),
Journal Year:
2023,
Volume and Issue:
19(12), P. 49 - 61
Published: Aug. 31, 2023
This
paper
introduces
an
innovative
technique
for
creating
a
cough
detection
system
that
relies
on
speech
recognition
algorithms.
The
strategy
utilizes
the
Kaldi
platform,
which
is
open
source
and
incorporates
hybrid
of
Gaussian
Mixture
Model-based
Hidden
Markov
Models
(GMM-HMM)
through
straightforward
monophone
training
model.
Additionally,
study
examines
effectiveness
two
different
feature
extraction
approaches,
Mel
Frequency
Cepstral
Coefficient
(MFCC)
Perceptual
Linear
Prediction
(PLP).
proposed
can
function
as
collection
tool
gathering
natural
spontaneous
data
from
conversations
or
continuous
speech.
also
compares
CMU
Sphinx4
toolkits,
concluding
Kaldi’s
use
GMM-HMM
outperforms
Sphinx4.
Financial Engineering and Risk Management,
Journal Year:
2023,
Volume and Issue:
6(6)
Published: Jan. 1, 2023
The
stock
market
is
the
place
where
issued
stocks
are
transferred,
traded
and
circulated,
including
exchange
over-the-counter
market.
Because
it
based
on
issuance
market,
also
called
secondary
structure
trading
activities
of
more
complex
than
(the
primary
market),
its
role
influence
greater.
It
precisely
because
systems
processes
that
achieving
accurate
predictions
very
difficult
challenging.
Hidden
Markov
Model
not
a
commonly
used
model
in
predicting
next
day's
price.
Hence,
I
will
focus
with
four
luxury
giants
to
prove
whether
HMM
suitable
for
industry,
which
company
fitted
most.
International Journal of Online and Biomedical Engineering (iJOE),
Journal Year:
2023,
Volume and Issue:
19(12), P. 49 - 61
Published: Aug. 31, 2023
This
paper
introduces
an
innovative
technique
for
creating
a
cough
detection
system
that
relies
on
speech
recognition
algorithms.
The
strategy
utilizes
the
Kaldi
platform,
which
is
open
source
and
incorporates
hybrid
of
Gaussian
Mixture
Model-based
Hidden
Markov
Models
(GMM-HMM)
through
straightforward
monophone
training
model.
Additionally,
study
examines
effectiveness
two
different
feature
extraction
approaches,
Mel
Frequency
Cepstral
Coefficient
(MFCC)
Perceptual
Linear
Prediction
(PLP).
proposed
can
function
as
collection
tool
gathering
natural
spontaneous
data
from
conversations
or
continuous
speech.
also
compares
CMU
Sphinx4
toolkits,
concluding
Kaldi’s
use
GMM-HMM
outperforms
Sphinx4.