Silent Sound Technology
Sound is the string that
tunes life… Sound is the spirit that connects souls… Sound is the inevitable
blend of music, words, love, care, and what not it is…
Since life began on earth, the living creatures
from microorganisms to human beings started communicating in their own ways.
Some make sounds, some produce hormones, some show expressions, i.e. each and
everyone on this earth has a mode of communication.Whatever the methods they
adopt, the supreme objective is to convey messages. Humans communicate via
sound and expressions mainly. Only people with voice could speak over the phone
so far. Now, it’s a good time for those who cannot speak, technology has
presented us a new technique called ‘Silent Sound Technology.’
Silence in some sense is the
best answer for all solutions. But not always. There are almost 70 million deaf
people who make sign language as their mother tongue or first language.
According to WHO, over 5% (about 360 million) of the total population all over
the world are facing hearing disabilities.Speaking over the phone is a dream
for many of them. The time has reached to turn that dream into reality. A team
of Scientists from Karlsruhe Institute of Technology (KIT), Germany has come up
with the concept of Silent Sound Technology and working on it to develop an
expedient device.Nowadays
whenever we are talking on a cell phone in a crowd, then actually we are not
talking, we are yelling because of lots of disturbance and noise around us. However,
there is no need to scream to convey our message and wasting our energy
anymore.For this purpose a new technology known as the “Silent Sound
Technology” has been introduced that will put an end to the noise pollution.
The Silent sound technology is a perfect solution for those people who have
lost their voice but wish to speak on mobile phones. It is developed at the
Karlsruhe Institute of Technology and you can expect to see it in the near
future. When this technology is used, it detects every lip movement and
internally converts the electrical pulses into sounds signals and sends them
neglecting all other surrounding noise. It is going to be really beneficial for
the people who hate talking loudly on cell phones. “Silent Sound technology”
aims to notice every movements of the lips and transform them into sounds,
which could help people who lose voices to speak, and allow people to make
silent calls without bothering others. Rather than making any sounds, your
handset would decipher the movements your mouth makes by measuring muscle
activity, then convert this into speech that the person on the other end of the
call can hear. So, basically, it reads our lips. Another important benefit of
this technology is that it allows you to communicate to any person in the world
as the electrical pulse is universal, it can be converted into any language
depending upon the users choice. This technology can be used for languages like
English, French & German but not for languages like Chinese because
different tones hold different meaning in Chinese language. This new technology
will be very helpful whenever a person loses his voice while speaking or allow
people to make silent calls without disturbing others, thus now we can speak
anything with our friends or family in private without anyone eavesdropping. At
the other end, the listener can hear a clear voice. This device works with 99%
efficiency, and can been seen in the market in another 5-10 years and once
launched it will have a drastic effect and with no doubt it will be widely
used.
Silence is the best answer for all the situations …even your mobile understands!
· The word Cell Phone has become
greatest buzz word in Cellular Communication industry.
· There are lots and lots of
technology that tries to reduce the Noise pollution and make the environment a
better place to live in.
· I will tell about a new technology
known as Silent Sound Technology that will put an end to Noise pollution.
It is a technology that helps you to transmit information without using your vocal cords . This technology aims to notice lip movements & transform them into a computer generated sound that can be transmitted over a phone . Hence person on other end of phone receives the information in audio.
In the 2010 CeBIT's "future park", a concept "Silent Sound" Technology demonstrated which aims to notice every movement of the lips and transform them into sounds, which could help people who lose voices to speak, and allow people to make silent calls without bothering others.
The device, developed by the
Karlsruhe Institute of Technology (KIT), uses electromyography, monitoring tiny
muscular movements that occur when we speak and converting them into electrical
pulses that can then be turned into speech, without a sound uttered.
‘Silent Sound’ technology aims to notice every
movements of the lips and transform them into sounds, which could help people
who lose voices to speak, and allow people to make silent calls without
bothering others. Rather than making any sounds, your handset would decipher
the movements your mouth makes by measuring muscle activity, then convert this
into speech that the person on the other end of the call can hear. So,
basically, it reads your lips.
“We
currently use electrodes which are glued to the skin. In the future, such
electrodes might for example by incorporated into cellphones,” said Michael
Wand, from the KIT.
The technology opens up a
host of applications, from helping people who have lost their voice due to
illness or accident to telling a trusted friend your PIN number over the phone
without anyone eavesdropping — assuming no lip-readers are around.
The
technology can also turn you into an instant polyglot. Because the electrical
pulses are universal, they can be immediately transformed into the language of
the user’s choice.
“Native speakers can silently utter a sentence
in their language, and the receivers hear the translated sentence in their
language. It appears as if the native speaker produced speech in a foreign
language,” said Wand.
The translation
technology works for languages like English, French and German, but for
languages like Chinese, where different tones can hold many different meanings,
poses a problem, he added.
Noisy people in your office? Not any more. “We are also working on technology to be used in an office environment,” the KIT scientist told AFP.
The engineers have got
the device working to 99 percent efficiency, so the mechanical voice at the
other end of the phone gets one word in 100 wrong, explained Wand.
“But we’re working to overcome the remaining technical difficulties. In five, maybe ten years, this will be useable, everyday technology,” he said.
Silent Sound Technology will put an end to embarrassed
situation such as-
·
An person answering his silent, but vibrating cell phone in a meeting, lecture
or performance, and whispering loudly, ‘ I can’t talk to you right now’ .
·
In the case of an urgent call, apologetically rushing out of the room in order
to answer or call the person back.
|
— The idea of interpreting silent speech
electronically or with a computer has been around for a long time, and was
popularized in the 1968 Stanley Kubrick science-fiction film ‘‘2001 – A Space
Odyssey” — A major focal point was the DARPA Advanced Speech
Encoding Program (ASE) of the early 2000’s, which funded research on low bit
rate speech synthesis ‘‘with acceptable intelligibility, quality, and aural
speaker recognizability in
acoustically harsh environments”,
|
The technology opens up a host of applications, from helping people who have lost their voice due to illness or accident to telling a trusted friend your PIN number over the phone without anyone eavesdropping — assuming no lip-readers are around. Native speakers can silently utter a sentence in their language, and the receivers hear the translated sentence in their language. It appears as if the native speaker produced speech in a foreign language.
Analysis of
remotely sensed data is done using various image processing techniques and
methods that includes:
- The Silent Sound Technology uses
electromyography, monitoring tiny muscular movements that occur when we
speak.
- Monitored signals are converted
into electrical pulses that can then be turned into speech, without a
sound uttered.
- Electromyography (EMG) is a
technique for evaluating and recording the electrical activity produced by
skeletal muscles.
- An electromyography detects
the electrical potential generated by muscle cells, when
these cells are electrically or neurologically activated.
- Electromyographic sensors
attached to the face records the electric signals produced by the facial
muscles, compare them with pre recorded signal pattern of spoken words
- When there is a match that sound
is transmitted on to the other end of the line and person at the other end
listen to the spoken words
- The simplest form of digital
image processing converts the digital data tape into a film image with
minimal corrections and calibrations.
- Then large mainframe computers
are employed for sophisticated interactive manipulation of the data.
- In the present context, overhead
prospective are employed to analyze the picture.
- In electrical engineering and computer science, image processing is any form of signal processing for which the input is an image, such as a photograph or video frame; the output of image processing may be either an image or, a set of characteristics or parameters related to the image. Most image-processing techniques involve treating the image as a two-dimensional signal and applying standard signal-processing techniques to it.
- Technique for evaluating and recording the electrical activity produced by skeletal muscles.
- Performed using an instrument called an “Electromyograph”, to produce a record called an “Electromyogram”.
- Electromyograph detects the electrical potential generated by muscle cells when these cells are electrically or neurologically activated.
- Monitored signals are converted into electrical pulses that can then be turned into speech
Electrical characteristics
· First documented experiments dealing with EMG started
with Francesco Redi’s works in 1666.
· He discovered that a highly specialized muscle of the
electric ray fish (Electric Eel) generated electricity.
· By 1773, it was demonstrated that the Eel’s muscle
tissue could generate a spark of electricity.
· In 1849, Dubois-Raymond discovered that it was also
possible to record electrical activity during a voluntary muscle contraction.
·
First
actual recording of this activity was made by Marey in 1890, who also
introduced the term “Electromyography”.
v The insertional activity provides valuable information
about the state of the muscle and its innervating nerve.
v Normal muscles at rest make certain, normal electrical
signals when the needle is inserted into them.
v Abnormal spontaneous activity might indicate some
nerve and/or muscle damage.
v The electrode is retracted a few millimeters, and
again the activity is analyzed until at least 10–20 units have been collected.
Muscle
tissue at rest is normally electrically inactive. After the electrical activity
caused by the irritation of needle insertion subsides, the electromyograph
should detect no abnormal spontaneous activity.
· Abnormal Results
An
action potential amplitude that is twice normal due to the increased number of fibres per motor unit because of reinnervation of denervated fibres.
· MUAPs from different motor units tend to have
different characteristic shapes, while MUAPs recorded by the same electrode
from the same motor unit are typically similar.
· MUAP size and shape depend on where the electrode is
located with respect to the fibers and so can appear to be different if the
electrode moves position.
Applications of
EMG:
EMG signals are used in
many clinical and biomedical applications. EMG is used as a diagnostics tool
for identifying neuromuscular diseases,
assessing low-back pain, kinesiology, and disorders of motor
control. EMG signals are also used as a control signal for prosthetic devices such as prosthetic hands, arms, and lower limbs.
EMG can be used to sense isometric muscular activity where
no movement is produced. This enables definition of a class of subtle
motionless gestures to control interfaces without being noticed and without
disrupting the surrounding environment. These signals can be used to control a
prosthesis or as a control signal for an electronic device such as a mobile
phone or PDA.
EMG signals have been
targeted as control for flight systems. The Human Senses Group at the NASA Ames Research Center at Moffett Field, CA seeks to advance man-machine interfaces by directly
connecting a person to a computer. In this project, an EMG signal is used to
substitute for mechanical joysticks and keyboards. EMG has also been used in
research towards a "wearable cockpit," which employs EMG-based gestures to manipulate switches and control sticks necessary for
flight in conjunction with a goggle-based display.
Unvoiced speech
recognition recognizes speech by observing the EMG activity of muscles
associated with speech. It is targeted for use in noisy environments, and may
be helpful for people without vocal cords and people with aphasia.
Then large
mainframe computers are employed for sophisticated interactive manipulation of
the data.
In the present context, overhead prospective are employed to analyze the picture.
In electrical engineering and computer s4cience, image processing is any form of signal processing for which the input is an image,
such as a photograph or video frame; the output of image processing may be
either an image or, a set of characteristics or parameters related to the
image. Most image-processing techniques involve treating the image as a two-dimensional signal and applying standard signal-processing techniques to it.
Image processing usually refers to digital image processing, but optical and analog image processing also are possible. This article is about general techniques that apply
to all of them. The acquisition of images (producing the input image in
the first place) is referred to as imaging.
The most common type of image
processing is photography. In this process, an image is captured using a camera
to create a digital or analog image. In order to produce a physical picture,
the image is processed using the appropriate technology based on the input
source type.
In digital
photography, the image is stored as a computer file. This file is translated using
photographic software to generate an actual image. The colors, shading, and
nuances are all captured at the time the photograph is taken the software translates
this information into an image.
When creating images using analog
photography, the image is burned into a film using a chemical reaction triggered by controlled
exposure to light. The image is processed in a darkroom, using special chemicals to create
the actual image. This process is decreasing in popularity due to the advent of
digital photography, which requires less effort and special training to product
images.
In addition to photography, there are
a wide range of other image processing operations. The field of digital imaging has created a whole range of new applications and tools that were
previously impossible. Face recognition software, medical image processing and
remote sensing are all possible due to the development of digital image
processing. Specialized computer programs are used to enhance and correct
images. These programs apply algorithms to the actual data and are able to
reduce signal distortion, clarify fuzzy images and add light to an underexposed
image.
Image processing techniques were
first developed in 1960 through the collaboration of a wide range of scientists
and academics. The main focus of their work was to develop medical imaging, character recognition and create
high quality images at the microscopic level. During this period, equipment and
processing costs were prohibitively high.
There
are three major benefits to digital image processing. The consistent high
quality of the image, the low cost of processing and the ability to manipulate
all aspects of the process are all great benefits. As long as computer
processing speed continues to increase while the cost of storage memory
continues to drop, the field of image processing will grow.
There two types of image processing:
1.Analog image processing
·
Analog image processing technique is
applied to hard copy of data such as photograph or print out.
- It
adopts certain elements of interpretation, such as primary element,
spatial arrangement etc.,
- With
the combination of multi-concept of examining remotely sensed data in
multispectral, multitemporal, multiscales and in conjunction with
multidisciplinary, allows us to make a verdict not only as to what an
object is but also its importance.
- Apart
from these it also includes optical photogrammetric techniques allowing
for precise measurement of the height, width, location, etc. of an object.
Analog processing
techniques
is applied to hard copy data such as photographs or printouts. Image analysis
in visual techniques adopts certain elements of interpretation, which are as
follow:
The use of these fundamental elements of depends not only on the area being
studied, but the knowledge of the analyst has of the study area. For example
the texture of an object is also very useful in distinguishing objects that may
appear the same if the judging solely on tone (i.e., water and tree canopy, may
have the same mean brightness values, but their texture is much different.
Association is a very powerful image analysis tool when coupled with the
general knowledge of the site. Thus we are adept at applying collateral data
and personal knowledge to the task of image processing. With the combination of
multi-concept of examining remotely sensed data in multispectral,
multitemporal, multiscales and in conjunction with multidisciplinary, allows us
to make a verdict not only as to what an object is but also its importance. Apart
from these analog image processing techniques also includes optical
photogrammetric techniques allowing for precise measurement of the height,
width, location, etc. of an object.
Image
processing usually refers to digital image processing,
but optical
and analog image processing
also are possible. This article is about general techniques that apply to all
of them. The acquisition of images (producing the input image in the
first place) is referred to as imaging.
Image
processing is a physical process used to convert an image signal into a
physical image. The image signal can be either digital or analog. The actual
output itself can be an actual physical image or the characteristics of an
image.
The
most common type of image processing is photography. In this process, an image
is captured using a camera to create a digital or analog image. In order to
produce a physical picture, the image is processed using the appropriate
technology based on the input source type.
Digital
Image Processing involves a collection of techniques for the manipulation of
digital images by computers. Digital
image processing is the use of computer algorithms
to perform image processing
on digital images.
As a subcategory or field of digital signal processing,
digital image processing has many advantages over analog image processing. It
allows a much wider range of algorithms to be applied to the input data and can
avoid problems such as the build-up of noise and signal distortion during
processing. Since images are defined over two dimensions (perhaps more) digital
image processing may be modeled in the form of Multidimensional
Systems.
Digital
processing is used in a variety of applications. The different types of digital
processing include image processing, audio processing, video processing, signal
processing, and data processing. In the most basic terms, digital processing
refers to any manipulation of electronic data to produce a specific effect.
In
a most generalized way, a digital image is an array of numbers depicting
spatial distribution of a certain field parameters (such as reflectivity of EM
radiation, emissivity, temperature or some geophysical or topographical
elevation. Digital image consists of discrete picture elements called pixels.
Associated with each pixel is a number represented as DN (Digital Number), that
depicts the average radiance of relatively small area within a scene. The range
of DN values being normally 0 to 255. The size of this area effects the
reproduction of details within the scene. As the pixel size is reduced more
scene detail is preserved in digital representation.
Remote sensing images are recorded in digital forms and
then processed by the computers to produce images for interpretation purposes.
Images are available in two forms - photographic film form and digital form.
Variations in the scene characteristics are represented as variations in
brightness on photographic films. A particular part of scene reflecting more
energy will appear bright while a different part of the same scene that
reflecting less energy will appear black. Digital image consists of discrete
picture elements called pixels. Associated with each pixel is a number
represented as DN (Digital Number), that depicts the average radiance of
relatively small area within a scene. The size of this area effects the
reproduction of details within the scene. As the pixel size is reduced more
scene detail is preserved in digital representation.
Data Formats
For Digital Satellite
Imagery
Digital data from the various satellite systems supplied to the user in the
form of computer readable tapes or CD-ROM. As no worldwide standard for the
storage and transfer of remotely sensed data has been agreed upon, though the
CEOS (Committee on Earth Observation Satellites) format is becoming accepted as
the standard. Digital remote sensing data are often organised using one of the
three common formats used to organise image data . For an instance an image
consisting of four spectral channels, which can be visualised as four
superimposed images, with corresponding pixels in one band registering exactly
to those in the other bands. These common formats are:
- Band Interleaved by
Pixel (BIP)
- Band
Interleaved by Line (BIL)
- Band
Sequential (BQ)
Digital image analysis is usually
conducted using Raster data structures - each image is treated as an array of
values. It offers advantages for manipulation of pixel values by image
processing system, as it is easy to find and locate pixels and their values.
Disadvantages becomes apparent when one needs to represent the array of pixels
as discrete patches or regions, where as Vector data structures uses polygonal
patches and their boundaries as fundamental units for analysis and manipulation.
Though vector format is not appropriate to for
digital analysis of remotely sensed data.
Image Resolution
Resolution can be defined as "the ability of an
imaging system to record fine details in a distinguishable manner". A
working knowledge of resolution is essential for understanding both practical
and conceptual details of remote sensing. Along with the actual positioning of
spectral bands, they are of paramount importance in determining the suitability
of remotely sensed data for a given applications. The major characteristics of
imaging remote sensing instrument operating in the visible and infrared
spectral region are described in terms as follow:
- Spectral
resolution
- Radiometric
resolution
- Spatial
resolution
- Temporal
resolution
Spectral Resolution refers to the width of the spectral
bands. As different material on the earth surface exhibit different spectral
reflectances and emissivities. These spectral characteristics define the
spectral position and spectral sensitivity in order to distinguish materials.
There is a tradeoff between spectral resolution and signal to noise. The use of
well -chosen and sufficiently numerous spectral bands is a necessity,
therefore, if different targets are to be successfully identified on remotely
sensed images.
Radiometric Resolution or radiometric sensitivity refers to
the number of digital levels used to express the data collected by the sensor.
It is commonly expressed as the number of bits (binary digits) needs to store
the maximum level. For example Landsat TM data are quantised to 256 levels
(equivalent to 8 bits). Here also there is a tradeoff between radiometric
resolution and signal to noise. There is no point in having a step size less
than the noise level in the data. A low-quality instrument with a high noise
level would necessarily, therefore, have a lower radiometric resolution
compared with a high-quality, high signal-to-noise-ratio instrument. Also
higher radiometric resolution may conflict with data storage and transmission
rates.
Spatial Resolution of an imaging system is defines through
various criteria, the geometric properties of the imaging system, the ability
to distinguish between point targets, the ability to measure the periodicity of
repetitive targets ability to measure the spectral properties of small targets.
The most commonly quoted quantity is the instantaneous field of view (IFOV),
which is the angle subtended by the geometrical projection of single detector
element to the Earth's surface. It may also be given as the distance, D
measured along the ground, in which case, IFOV is clearly dependent on sensor
height, from the relation: D = hb, where h is the height and b is the angular
IFOV in radians. An alternative measure of the IFOV is based on the PSF, e.g.,
the width of the PDF at half its maximum value.
A problem with IFOV definition, however, is that it is a purely geometric
definition and does not take into account spectral properties of the target.
The effective resolution element (ERE) has been defined as "the size of an
area for which a single radiance value can be assigned with reasonable
assurance that the response is within 5% of the value representing the actual
relative radiance". Being based on actual image data, this quantity may be
more useful in some situations than the IFOV.
Other methods of defining the spatial resolving
power of a sensor are based on the ability of the device to distinguish between
specified targets. Of the concerns the ratio of the modulation of the image to
that of the real target. Modulation, M, is defined as:
M = Emax -Emin / Emax + Emin
Where Emax and Emin are the maximum and minimum radiance values recorded over
the image.
Temporal
resolution
Temporal resolution refers to the frequency with which images of a given geographic location can be acquired. Satellites not only offer the best chances of frequent data coverage but also of regular coverage. The temporal resolution is determined by orbital characteristics and swath width, the width of the imaged area. Swath width is given by 2htan(FOV/2) where h is the altitude of the sensor, and FOV is the angular field of view of the sensor.
It
contain some flaws. To overcome the flaws and deficiencies in order to get the
originality of the data, it needs to undergo several steps of processing.
Digital
Image Processing undergoes three general steps:
· Pre-processing
· Display
and enhancement
· Information
extraction
- Pre-processing consists
of those operations that prepare data for subsequent analysis that
attempts to correct or compensate for systematic errors.
- Then
analyst may use feature extraction to reduce the dimensionality of the
data.
- Thus
feature extraction is the process of isolating the most useful components
of the data for further study while discarding the less useful aspects.
- It
reduces the number of variables that must be examined, thereby saving time
and resources.
Pre-processing consists of those operations that
prepare data for subsequent analysis that attempts to correct or compensate for
systematic errors. The digital imageries are subjected to several corrections
such as geometric, radiometric and atmospheric, though all these correction
might not be necessarily be applied in all cases. These errors are systematic
and can be removed before they reach the user. The investigator should decide
which pre-processing techniques are relevant on the basis of the nature of the
information to be extracted from remotely sensed data. After pre-processing is
complete, the analyst may use feature extraction to reduce the dimensionality
of the data. Thus feature extraction is the process of isolating the most
useful components of the data for further study while discarding the less
useful aspects (errors, noise etc). Feature extraction reduces the number of
variables that must be examined, thereby saving time and resources.
- Improves
the interpretability of the image by increasing apparent contrast among
various features in the scene.
- The
enhancement techniques depend upon two factors mainly
- The
digital data (i.e. with spectral bands and resolution)
- The
objectives of interpretation
- Common
enhancements include image reduction, image rectification, image
magnification, contrast adjustments, principal component analysis texture
transformation and so on.
Image Enhancement
operations are carried out to improve the interpretability of the image by
increasing apparent contrast among various features in the scene. The
enhancement techniques depend upon two factors mainly
- The
digital data (i.e. with spectral bands and resolution)
- The
objectives of interpretation
As an image enhancement technique
often drastically alters the original numeric data, it is normally used only
for visual (manual) interpretation and not for further numeric analysis. Common
enhancements include image reduction, image rectification, image magnification,
transect extraction, contrast adjustments, band ratioing, spatial filtering,
Fourier transformations, principal component analysis and texture
transformation.
INFORMATION
EXTRACTION:
- In
Information Extraction the remotely sensed data is subjected to
quantitative analysis to assign individual pixels to specific classes. It
is then classified.
- It
is necessary to evaluate its accuracy by comparing the categories on the
classified images with the areas of known identity on the ground.
- The
final result of the analysis consists of maps (or images), data and a
report. Then these are converted to corresponding signals.
Information Extraction is the last step toward the final output of the image analysis. After pre-processing and image enhancement the remotely sensed data is subjected to quantitative analysis to assign individual pixels to specific classes. Classification of the image is based on the known and unknown identity to classify the remainder of the image consisting of those pixels of unknown identity. After classification is complete, it is necessary to evaluate its accuracy by comparing the categories on the classified images with the areas of known identity on the ground. The final result of the analysis consists of maps (or images), data and a report. These three components of the result provide the user with full information concerning the source data, the method of analysis and the outcome and its reliability.
FEATURES OF SILENT SOUND TECHNOLOGY
Some of the features of
silent sound technology are
·
Native speakers can silently utter a sentence in their language, and the
receivers can hear the translated sentence in their language. It appears as if
the native speaker produced speech in a foreign language. The translation
technology works for languages like English, French and German, except Chinese,
where different tones can hold many different meanings.
·
Allow people to make silent calls without bothering others.
·
The Technology opens up a host of application such as mentioned below
·
Helping people who have lost their voice due to illness or accident.
·
Telling a trusted friend your PIN number over the phone without anyone
eavesdropping — assuming no lip-readers are around.
· Silent Sound Techniques is applied in Military for communicating secret/confidential matters to others.
— As we know in space there is no medium for sound to
travel therefore this technology can be best utilised by astronauts.
— We can make
silent calls even if we are standing in a crowded place.
— This technology is helpful for people without vocal
cord or those who are suffering from Aphasia (speaking disorder ).
— This technology can be used for communication in nasty
environment.
— To tell a secret PIN no. , or credit card no. on the
phone now be easy as there is no one eavesdrop anymore.
— Since the electrical signals are universal they can be translated into any language. Native speakers can translate it before sending it to the other side. Hence it can be converted into any language of choice currently being German, English & French.
— Translation into majority of languages but for
languages such as Chinese different tone holds different meaning, facial
movements being the same. Hence this technology is difficult to apply in such
situations.
— From security point of view recognising who you are
talking to gets complicated.
— Even differentiating between people and emotions
cannot be done. This means you will always feel you are talking to a robot.
— This device presently needs nine leads to be attached to our face which is quite impractical to make it usable.
v Silent sound technology gives way to a bright future
to speech recognition technology from simple voice commands to memorandum
dictated over the phone all this is fairly possible in noisy public places.
v Without having electrodes hanging all around your
face, these electrodes will be incorporated into cellphones .
v It may have features like lip reading based on image
recognition & processing rather than electromyography.
v Nano technology will be a mentionable step towards
making the device handy.
With all of the millions of phones in circulation, there is great potential for increasing earnings by saving 'lost calls' - telephone calls that go unanswered or uninitiated because the user is in a situation in which he or she cannot speak - not just in business meetings, but everyday situations. According to research, these 'lost calls' are worth $20 billion per year worldwide. For the cellular operator, these are potential earnings that are currently being left on the table. When these 'lost calls' become answerable, and can be conducted without making a sound, there is a tremendous potential for increased profits. Now the research is going on technology that can be used in Office Environment too.
The Silent Sound Technology,
one of the recent trends in the field of information technology implements “Talking
Without Talking”. Engineers claim that the device is working with 99 percent
efficiency. It is difficult to compare SSI technologies directly in a
meaningful way. Since many of the systems are still preliminary, it would not
make sense, for example, to compare speech recognition scores or synthesis
quality at this stage.
‘Silent Sound’ technology
aims to notice every movements of the lips and transform them into sounds,
which could help people who lose voices to speak, and allow people to make
silent calls without bothering others. Rather than making any sounds, your
handset would decipher the movements your mouth makes by measuring muscle
activity, then convert this into speech that the person on the other end of the
call can hear. So, basically, it reads your lips. It will be one of the
innovation and useful technology and in mere future this technology will be use
in our day to day life.
Aishu nice raaa
ReplyDeleteWaahh Too good
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