Why Was Sign Abandoned?
The core of the Oralists' argument is that
sign is not known to the general public, so it is of limited use and segregates
the deaf. This argument would fall apart if you could translate your signs
instantly.
Oralism was declared a failure in 1964.
Sign has seen a revival since then, and there are around 100,000 people fluent
in British Sign Language (BSL).
British
Sign Language (BSL)
Deaf people have already benefited from
technology. The first sign language was invented in 530AD by Benedictine monks
to get round their vows of silence. In 1964, the teletypewriter was invented so
the deaf could talk on the phone through typing. 1972 saw the first TV
captions. The advent of texts and email has removed some of the communication
barriers between the deaf and hearing worlds. YouTube now adds closed captions
to its videos.
Oliver Sacks, author of Seeing Voices,
noted that the deaf are abandoning deaf clubs because of email, meaning they no
longer practice sign as much - a worrying development. This may no longer be a
problem thanks to free video calling via Facetime or Skype. The deaf will be
able to have sign conversations in real time and will not need as much
bandwidth, because they don't need audio. They will also be able to send texts
by signing, though obviously they would have to use a dual-camera phone.
Could sign interpreters be made redundant
by apps? Khalid Ashraf, a BSL on-screen presenter for ITV, is sceptical:
"To our knowledge, it is completely impossible for computers to translate
a gesture into text, considering the complexities of certain non-manual
features, etc. Please note that deaf people do not just use hands for their
communication but also use their facial expressions and body movements as part
of conversation. Imagine how a spoken English language using double meanings
would translate into French or other foreign languages." He believes the
only solution is for BSL to be made compulsory in school.
American
Sign Language (ASL)
Interactive Solutions is a technology
company that has been translating American Sign Language (ASL) for 13 years.
The company explained its beginnings: "In October 1999, Interactive
Solutions was approached by a family whose son was profoundly deaf. The young
man, Morgan Greene, was 16 years old and a sophomore in high school. Though
Morgan had a full-time sign language interpreter, he still had a fourth grade
literacy level in tenth grade. He had requested that his parents help him find
a company to design and develop a computer that would enable him to communicate
with the hearing world when a sign language interpreter was not
available."
At the time, there was no speech-to-sign
software. It had created its own by March 2000, which could translate speech to
text and sign language in real time. It could also translate speech or text
into a computer voice transmitted to hearing aids and cochlear implants, though
this feature is of no use to those born deaf. In March 2005, it bought
iCommunicator, now in its fifth version, and built a database of 30,000 words
and 9,000 signs. What it could not do was translate signs into speech or text.
Interactive Solutions is explicitly not
after translators' jobs: "The iCommunicator is not intended to replace
sign language interpreters, but to serve as an alternative access technology
for some persons who communicate in sign language. The iCommunicator is a fully
integrated system that consists of a high-end laptop computer, iCommunicator
software, a wireless microphone system and peripherals, and underlying software
programs."
The company expects its software to be used
for emergencies, in mainstream schools, random encounters and by families
learning ASL.
In May 2008, there was another attempt to
automate sign translation. HandTalk is a glove with five embedded Flex sensors,
which translate gestures into a raw signal, which is converted to digital data,
via Bluetooth to a mobile. The mobile runs Java 2 Micro Edition (J2ME), an app
that converts the data to text then speech. It was built by engineering
students at Carnegie Mellon University using very cheap components.
David Sarji, the head of the project
explained how their software works: "An algorithm on the BlueSentry module
converts the analogue data received from the sensors to digital data, in the
form of numbers ranging from 0 to 65500. The HandTalk MIDIet in turn divides
this data into segments that correspond to specific ranges of numeric values
representing finger positions such as fully extended, fully bent, or partially
bent... The team 'trained' HandTalk to recognise symbols by recording sensor
data while a researcher held the glove in various sign positions, correlating
these with specific signs, and mapping them to a database."
This method has a disadvantage: it requires
the purchase of a new gadget, whereas the PSLT and uKinect are apps running on
commonly used hardware - consoles, smartphones and tablets. In the future,
embedded computing may become the norm. Bluetooth ear pieces are common, so why
not gloves?
