unethical mortgage loan modification company
Complaint
tom hoyt
Country: United States
I received a call from JetDirectfunding. they sounded legit and I decided I would work with them. Once they had important information from me, the main contact email no longer worked or would anyone answer the phone or return calls. here is then name of the person. I strongly caution anyone from dealing with this company in the future!
Ryan A. Quadrel
Modification Consultant
Jet Direct Funding Corp.
www.jetdirectfunding.com
139 South 11th St.
Lindenhurst, NY 11757
Office (800) 721-9919 x619
Fax (631) 574-1450
Cell (973) 668-9262
Ryan A. Quadrel
Modification Consultant
Jet Direct Funding Corp.
www.jetdirectfunding.com
139 South 11th St.
Lindenhurst, NY 11757
Office (800) 721-9919 x619
Fax (631) 574-1450
Cell (973) 668-9262
Comments
concerned with assisting individuals with severe physical and language
impairments to communicate more effectively. Existing AAC systems make
use of a variety of approaches to accelerate sentence generation,
including different selection methods, encoding strategies, and
natural language processing. Augmented communicators continue to
produce words at a very slow rate, and have difficulty participating
actively in conversation.
However, only recently have AAC systems begun to make use of the
predictable patterns that occur in conversation. To date, such systems
have focussed on either highly constrained and relatively content-free
utterances, or on loosely structured, monologue type text.
This thesis develops an alternative but compatible approach to
facilitating conver sational participation in AAC which attempts to
target a broader range of conversations, representing both their
content and structure. Motivated by schema theory, this approach
applies schema structures to the domain of conversation. A set of
structures is proposed with which text from past conversations can be
made available for reuse.
To demonstrate this approach, a prototype is developed and
evaluated. The prototype behaves as an interface that augments a
user's current AAC system by providing access to conversational
schemata created and updated by the user. In the evaluation study, two
individuals used the interface while taking part in a series of mock
job interviews. Results of the study were encouraging.
Chapter 1
INTRODUCTION
An individual who uses an augmentative communication system gains an
alternative voice, one that can augment and complement a natural
voice that is difficult to pro duce or to understand. In order to
"speak" with this alternative voice, augmentative communication
systems require the individual to physically select symbols
representing the words to be spoken, either by hand or using some
other motor channel. Dependence on motor abilities that are also
impaired, however, means that utterances can take much time and effort
to produce.
To reduce this time to speak, systems could make sentences or larger
segments of text available as single units. Such "reusable" text could
then be spoken, as is, with very little effort. Alternatively, when
reusable text is not available, the individual could select fewer
items and speak in short, or incomplete, sentences. Although these two
strategies might both reduce the time to produce a sentence, speaking
with incomplete sentences, or with noticeably "canned" sentences that
are not quite context-appropriate, can be interpreted by unfamiliar
listeners as signs of cognitive impairment.
The challenge to the designers of augmentative and alternative
communication (AAC) systems, therefore, becomes one of increasing the
rate of spoken output without compromising the image of the augmented
communicator, the individual using the system. Contextual information
is very important during conversation for determining both the meaning
and the appropriateness of an utterance. Within the proper context,
then, reusable text that is made available and selected by the user
will not sound canned. However, such precise contextual information is
not available, in an automatic fashion, to current AAC systems.
It is, however, available to the individual who is speaking through
the system. The individual is aware of the situation in which the
conversation is taking place, and of the intended self-image. The
challenge for the system becomes one of making context-appropriate
reusable text available to the individual in a reasonable amount of
time and without excessive cognitive load. This interaction between
system and user should involve as little effort as possible during a
conversation, so that the individual can concentrate on the topic and
on the other participants.
I suggest that there are three requirements for an AAC system to
facilitate conversational interaction:
(1) the augmented communicator produces text at some time prior to
the conversation, and stores it in the system;
(2) the AAC system supports an organization for stored text that is
consis tent with observed features and patterns in conversation;
(3) during a conversation, and with very little effort, the augmented
communicator is able to retrieve desired and appropriate
pre-stored text.
Requirement (1), the pre-storage of text, is already a common feature
in many systems. However, few systems offer real support for (2) and
(3), structuring and retrieving this text for conversation. Notable
exceptions are the systems CHAT and TOPIC that were developed at the
University of Dundee (and their realization as a commercial product,
Talk:About, manufactured by Don Johnston Inc.). CHAT (Alm et al.,
1992) supported quick production of simple utterances, including
greetings, small talk, and farewells, applicable in many
conversational contexts. TOPIC (Alm et al., 1989) provided a database
of reusable text, taken from previous conversations and linked by
topic, and was concerned mainly with the monologue-type segments that
occur in the body of a conversation.
This thesis discusses an alternative, possibly complementary, approach
to organizing and retrieving pre-stored conversational text in an AAC
system. This approach is motivated by Schank's (1982) description of
schemata, representing the dependence of how we behave and think on
how we behaved and thought in similar situations in the
past. Situations that are judged similar are grouped together to form
the basis for expectations about future instances of similar
situations. These can include expectations about what people or things
will be involved in a situation, what events will occur, and in what
order they will occur. An individual's cognitive system can store
experiences more efficiently in this "schematized" form, and can
organize new experiences around these schemata.
In this thesis, I explore the notion of storing reusable text for
schematized situations in a manner similar to that described by
Schank's schemata. The intuition is that an AAC system which
represents conversation similarly to our own cognitive system should
be able to offer the user access to conversational text in a way that
is both intuitive and efficient. In pursuit of this goal, a prototype
interface, SchemaTalk, has been developed that adds schematic
organization to a text-based AAC system, and enables the user to
access that information. The effectiveness of this configuration was
investigated in a study in which two participants, involved in mock
job interviews, communicated using the interface and sentences they
had organized into schemata.
Chapter 2
AUGMENTATIVE AND ALTERNATIVE COMMUNICATION
In North America, there are over two million people unable to speak
adequately to meet their communication needs (American
Speech-Language-Hearing Association, 1991; cited in Beukelman &
Mirenda, 1992, p. 4). The field of augmentative and alternative
communication is concerned with developing methods and devices, tuned
to the abilities of each individual, to facilitate active and
effective participation in conversation and other forms of
communication (e.g., writing). In this thesis, I will focus on
augmenting spoken conversation, and on electronic AAC systems with
speech synthesis capabilities.
2.1 AAC Users
The American Speech-Language-Hearing Association (ASHA) gives the
following definition for the population of individuals who might use
AAC systems:
Individuals with severe communication disorders are those who may bene
fit from [AAC] -- those for whom gestural, speech, and/or written
communication is temporarily or permanently inadequate to meet all of
their communication needs. (American Speech-Language-Hearing
Association, 1991, p. 10; quoted in Beukelman & Mirenda, 1992, p. 4)
Emphasis is placed on the individual's natural modes of communication
not being adequate to meet all of their needs. In some situations,
and with some conversational partners, individuals may prefer to
communicate with their natural voice or gestures, and may find it more
effective to do so.
Communication may be severely impaired as a consequence of a
congenital neurologic dysfunction, such as cerebral palsy, mental
retardation, autism, developmental verbal apraxia, and specific
language disorders (Mirenda & Mathy-Laikko, 1989, p. 3). Severe
communication impairment may also be acquired as a result of
amyotrophic lateral sclerosis (ALS), multiple sclerosis (MS), brain
injury, stroke, or spinal cord injury (SCI) (Beukelman & Yorkston,
1989, pp. 42-47).
These same neurological conditions may impair non-language motor
abilities and perception, as well. Motor deficits, such as hypertonic
muscle tone, often accompany cerebral palsy, as do visual and hearing
deficits (Mirenda & Mathy-Laikko, 1989, p. 4). Acquired brain or
spinal injuries may result in limited mobility or sensory losses. The
ability to control a communication device that relies on motor input
will, in many cases, be affected.
2.2 Communicative Competence
The goal of AAC is to assist the user in becoming a competent
communicator. Light defines communicative competence as the ability
"to initiate and maintain daily interactions within the natural
environment" (1989, pp. 138) adequately to meet daily needs. This
presupposes knowledge, judgment, and skill in four areas (Light, 1989,
pp. 139):
(1) linguistic competence, using the rules of the language code
(phonology, morphology, syntax, and semantics);
(2) operational competence, using the AAC system itself (e.g.,
controlling the volume, retrieving and producing a word);
(3) social competence, interacting with others (e.g., initiating a
conversation, reacting to what another person says);
(4) strategic competence, adapting to a situation and compensating
for any difficulties that may arise (e.g., rephrasing an
utterance if the listener did not understand it, rather than
simply repeating it).
As well, communicative competence is relative, not absolute. An
individual may be competent interacting with one partner but not with
another, in one situation but not another, or at one stage of the
conversation but not another.
People interact for a variety of reasons: to communicate their wants
or needs, to convey or receive other information, to increase social
closeness, and to fulfil the require ments of social etiquette (Light,
1988, p. 76). Interactions with different goals may differ in many
ways. Social etiquette and expression of wants and needs, for example,
may be characterized by highly predictable interactions in which
communication rate is very im portant. Communication rate may also be
important when the goal of the interaction is to convey or receive
information (Light, 1988, p. 76).
AAC systems need to recognize these varying demands in order to
support communication more effectively.
2.3 Components of an AAC System
An AAC system (Figure 2.1) can be described in terms of its language
model, and its input and output interfaces (Demasco & Mineo,
1995). The input interface provides the user with a method for
selecting symbols (letters, words, or icons) represented in the
system. How symbols are represented, organized and processed is
specified in the language model. The user's message is presented by
the output interface.
Currently, AAC systems can accept input from a wide variety of
devices. Keys on a keyboard can be selected with the user's hands, or
with a stick fastened to a head-mount or held in the user's mouth. For
users with more limited motion, switch devices can be activated by
movement of the hand, foot, or eyebrow. A beam of light, emitted from
a head mounted source and detected by receivers on the AAC system, can
be used to make selections on a switch or a keyboard. There is even
work in progress to detect and follow the user's eye gaze (Sandler,
1994).
Figure 2.1: Components of an AAC system
[Figure Diagram]
LANGUAGE MODEL: - representation - organization - processing
PHYSICAL INPUT INTERFACE: - input devices - selection methods
PHYSICAL OUTPUT INTERFACE: - output devices
Selection methods can be generally classified as either direct or
scanning. With direct selection, the user indicates the desired item
from a set of items (Beukelman & Mirenda, 1992, p. 58). Spelling words
on a computer keyboard is an example of direct selection. Each key
represents a letter in the alphabet and is selected by the user via a
key stroke. Using a scanning method, items in the set are displayed in
some predetermined or der by the system, or by a conversational
partner or facilitator, and the user indicates when the desired item
has been presented (Beukelman & Mirenda, 1992, p. 62). In row-column
scanning, for example, symbols are organized into rows and columns and
the system high lights rows until the user indicates the row
containing the desired symbol. The system then highlights columns
until the user indicates the column containing the desired symbol. The
system selects the symbol located at the point where that row and
column intersect.
Scanning input can be slower than direct selection, because the user
must wait while the system traverses undesired items. However, direct
selection of even a relatively small number of items requires a fair
amount of motor dexterity. With scanning, an individual with severely
limited motor abilities is potentially able to select any symbol repre
sented in the system using only a single key or switch.
The words and messages of the language model that are available for
selection on an AAC system can be represented in a variety of symbol
sets. The most appropriate set for a specific user will depend on that
user's age, cognitive and language abilities, and perceptual abilities
(see Beukelman & Mirenda, 1992, pp. 21-27, for a discussion on
"representational symbols"). Letters, pictures, abstracted icon sets,
or combinations of all three are used by different systems.
The symbols available in a system must be organized and displayed to
the user in some fashion. For instance, in a letter-based system
performing row-column scanning, decisions must be made about how many
rows and columns to use, and in which order the letters should occur
in the columns. A system may contain more symbols than it can display
at one time. Symbols must then be organized to provide the user with a
consistent method for accessing them. This organization includes how
symbols are physically distributed on the system display, as well as
how hidden symbols are reached.
In addition to providing this vocabulary of symbols, an AAC system may
provide processing capabilities to facilitate its use. For instance, a
vocabulary symbol may have a phrase or sentence associated with it
which is retrieved by the system when the symbol is selected. Several
strategies of processing to increase communication rate are discussed
in Section 2.4.
Both visual and spoken output are available on many AAC
systems. Visual output methods include displaying symbols on a
computer screen, or printing symbols out on paper. Spoken output is
achieved with either digitized or synthesized speech. Digitized speech
is pre-recorded and fixed, while synthesized speech is generated at
the time of message production and is not constrained in terms of
message content. However, the voice quality of digitized speech is far
more natural than that of synthesized speech in current AAC systems.
2.4 Strategies for Accelerating Message Production
One of the great challenges to AAC has been to increase the rate of
message production by augmented communicators. With AAC systems,
production rates of between 2 and 20 words per minute are not
uncommon, an order of magnitude slower than for un augmented speakers
using their natural voices (Kraat, 1987, p. 63). This slow production
rate may affect how augmented communicators participate in
conversations, and how they are viewed by their conversational
partners.
Two acceleration strategies used in existing AAC systems are message
encoding and message prediction. Compansion, a third acceleration
strategy, in which the user in puts a sentence in "telegraphic" style
and the system completes the sentence, is discussed in Section 2.5.1.
Message encoding refers to retrieving a word, or a longer unit of
text, by using an associated code that requires fewer
selections. Codes can consist of letters, numbers, icons, or some
combination of these. For example, "Please open the door" may be
associated with the code "OD", the initial letters of the salient
words "open" and "door" (salient letter codes, Light & Lindsay, 1992,
p. 35). An alternate encoding might be "DD", be cause the sentence is
giving "directions" regarding the "door" (letter category codes, Light
& Lindsay, 1992, p. 35).
Flexible abbreviation expansion (Stum & Demasco, 1992) is an
alternative letter coding system for abbreviating words. In a standard
coding or abbreviation scheme, there is a fixed set of codes which is
stored by the user ahead of time. The processing done by the system is
a simple table look-up. In contrast, flexible abbreviation expansion
has no fixed table of codes. Instead, the user and system follow rules
to expand the letter codes.
Message prediction is a dynamic strategy, whereby the system makes use
of earlier portions of the message to interpret and predict the next
icon, letter, word, or larger segment of text (Beukelman & Mirenda,
1992, pp. 42-44). On a spelling-based system, for example, after the
user selects the letters "s", "t", and "u", the system may predict the
word in progress to be "student", "stupid", or "studying". If the
intended word is in this list, the user can select it immediately
rather than continuing to spell it. A system could also make use of
syntax rules (VanDyke et al., 1992) to better predict the intended
word.
2.5 Example AAC Techniques
To illustrate possible techniques for AAC, two systems are described
here in detail. The first, Compansion, is different from other
systems in that it uses natural language processing techniques to
complete a telegraphic sentence once the user has entered it. The
second system, the Liberator TM (Prentke Romich Company), is an
example of a commercially available system, and contains a variety of
tools with which the user can edit and navigate through stored
text. One participant in the evaluation study, discussed in Chapter 5,
normally communicates using the Liberator.
concerned with assisting individuals with severe physical and language
impairments to communicate more effectively. Existing AAC systems make
use of a variety of approaches to accelerate sentence generation,
including different selection methods, encoding strategies, and
natural language processing. Augmented communicators continue to
produce words at a very slow rate, and have difficulty participating
actively in conversation.
However, only recently have AAC systems begun to make use of the
predictable patterns that occur in conversation. To date, such systems
have focussed on either highly constrained and relatively content-free
utterances, or on loosely structured, monologue type text.
This thesis develops an alternative but compatible approach to
facilitating conver sational participation in AAC which attempts to
target a broader range of conversations, representing both their
content and structure. Motivated by schema theory, this approach
applies schema structures to the domain of conversation. A set of
structures is proposed with which text from past conversations can be
made available for reuse.
To demonstrate this approach, a prototype is developed and
evaluated. The prototype behaves as an interface that augments a
user's current AAC system by providing access to conversational
schemata created and updated by the user. In the evaluation study, two
individuals used the interface while taking part in a series of mock
job interviews. Results of the study were encouraging.
Chapter 1
INTRODUCTION
An individual who uses an augmentative communication system gains an
alternative voice, one that can augment and complement a natural
voice that is difficult to pro duce or to understand. In order to
"speak" with this alternative voice, augmentative communication
systems require the individual to physically select symbols
representing the words to be spoken, either by hand or using some
other motor channel. Dependence on motor abilities that are also
impaired, however, means that utterances can take much time and effort
to produce.
To reduce this time to speak, systems could make sentences or larger
segments of text available as single units. Such "reusable" text could
then be spoken, as is, with very little effort. Alternatively, when
reusable text is not available, the individual could select fewer
items and speak in short, or incomplete, sentences. Although these two
strategies might both reduce the time to produce a sentence, speaking
with incomplete sentences, or with noticeably "canned" sentences that
are not quite context-appropriate, can be interpreted by unfamiliar
listeners as signs of cognitive impairment.
The challenge to the designers of augmentative and alternative
communication (AAC) systems, therefore, becomes one of increasing the
rate of spoken output without compromising the image of the augmented
communicator, the individual using the system. Contextual information
is very important during conversation for determining both the meaning
and the appropriateness of an utterance. Within the proper context,
then, reusable text that is made available and selected by the user
will not sound canned. However, such precise contextual information is
not available, in an automatic fashion, to current AAC systems.
It is, however, available to the individual who is speaking through
the system. The individual is aware of the situation in which the
conversation is taking place, and of the intended self-image. The
challenge for the system becomes one of making context-appropriate
reusable text available to the individual in a reasonable amount of
time and without excessive cognitive load. This interaction between
system and user should involve as little effort as possible during a
conversation, so that the individual can concentrate on the topic and
on the other participants.
I suggest that there are three requirements for an AAC system to
facilitate conversational interaction:
(1) the augmented communicator produces text at some time prior to
the conversation, and stores it in the system;
(2) the AAC system supports an organization for stored text that is
consis tent with observed features and patterns in conversation;
(3) during a conversation, and with very little effort, the augmented
communicator is able to retrieve desired and appropriate
pre-stored text.
Requirement (1), the pre-storage of text, is already a common feature
in many systems. However, few systems offer real support for (2) and
(3), structuring and retrieving this text for conversation. Notable
exceptions are the systems CHAT and TOPIC that were developed at the
University of Dundee (and their realization as a commercial product,
Talk:About, manufactured by Don Johnston Inc.). CHAT (Alm et al.,
1992) supported quick production of simple utterances, including
greetings, small talk, and farewells, applicable in many
conversational contexts. TOPIC (Alm et al., 1989) provided a database
of reusable text, taken from previous conversations and linked by
topic, and was concerned mainly with the monologue-type segments that
occur in the body of a conversation.
This thesis discusses an alternative, possibly complementary, approach
to organizing and retrieving pre-stored conversational text in an AAC
system. This approach is motivated by Schank's (1982) description of
schemata, representing the dependence of how we behave and think on
how we behaved and thought in similar situations in the
past. Situations that are judged similar are grouped together to form
the basis for expectations about future instances of similar
situations. These can include expectations about what people or things
will be involved in a situation, what events will occur, and in what
order they will occur. An individual's cognitive system can store
experiences more efficiently in this "schematized" form, and can
organize new experiences around these schemata.
In this thesis, I explore the notion of storing reusable text for
schematized situations in a manner similar to that described by
Schank's schemata. The intuition is that an AAC system which
represents conversation similarly to our own cognitive system should
be able to offer the user access to conversational text in a way that
is both intuitive and efficient. In pursuit of this goal, a prototype
interface, SchemaTalk, has been developed that adds schematic
organization to a text-based AAC system, and enables the user to
access that information. The effectiveness of this configuration was
investigated in a study in which two participants, involved in mock
job interviews, communicated using the interface and sentences they
had organized into schemata.
Chapter 2
AUGMENTATIVE AND ALTERNATIVE COMMUNICATION
In North America, there are over two million people unable to speak
adequately to meet their communication needs (American
Speech-Language-Hearing Association, 1991; cited in Beukelman &
Mirenda, 1992, p. 4). The field of augmentative and alternative
communication is concerned with developing methods and devices, tuned
to the abilities of each individual, to facilitate active and
effective participation in conversation and other forms of
communication (e.g., writing). In this thesis, I will focus on
augmenting spoken conversation, and on electronic AAC systems with
speech synthesis capabilities.
2.1 AAC Users
The American Speech-Language-Hearing Association (ASHA) gives the
following definition for the population of individuals who might use
AAC systems:
Individuals with severe communication disorders are those who may bene
fit from [AAC] -- those for whom gestural, speech, and/or written
communication is temporarily or permanently inadequate to meet all of
their communication needs. (American Speech-Language-Hearing
Association, 1991, p. 10; quoted in Beukelman & Mirenda, 1992, p. 4)
Emphasis is placed on the individual's natural modes of communication
not being adequate to meet all of their needs. In some situations,
and with some conversational partners, individuals may prefer to
communicate with their natural voice or gestures, and may find it more
effective to do so.
Communication may be severely impaired as a consequence of a
congenital neurologic dysfunction, such as cerebral palsy, mental
retardation, autism, developmental verbal apraxia, and specific
language disorders (Mirenda & Mathy-Laikko, 1989, p. 3). Severe
communication impairment may also be acquired as a result of
amyotrophic lateral sclerosis (ALS), multiple sclerosis (MS), brain
injury, stroke, or spinal cord injury (SCI) (Beukelman & Yorkston,
1989, pp. 42-47).
These same neurological conditions may impair non-language motor
abilities and perception, as well. Motor deficits, such as hypertonic
muscle tone, often accompany cerebral palsy, as do visual and hearing
deficits (Mirenda & Mathy-Laikko, 1989, p. 4). Acquired brain or
spinal injuries may result in limited mobility or sensory losses. The
ability to control a communication device that relies on motor input
will, in many cases, be affected.
2.2 Communicative Competence
The goal of AAC is to assist the user in becoming a competent
communicator. Light defines communicative competence as the ability
"to initiate and maintain daily interactions within the natural
environment" (1989, pp. 138) adequately to meet daily needs. This
presupposes knowledge, judgment, and skill in four areas (Light, 1989,
pp. 139):
(1) linguistic competence, using the rules of the language code
(phonology, morphology, syntax, and semantics);
(2) operational competence, using the AAC system itself (e.g.,
controlling the volume, retrieving and producing a word);
(3) social competence, interacting with others (e.g., initiating a
conversation, reacting to what another person says);
(4) strategic competence, adapting to a situation and compensating
for any difficulties that may arise (e.g., rephrasing an
utterance if the listener did not understand it, rather than
simply repeating it).
As well, communicative competence is relative, not absolute. An
individual may be competent interacting with one partner but not with
another, in one situation but not another, or at one stage of the
conversation but not another.
People interact for a variety of reasons: to communicate their wants
or needs, to convey or receive other information, to increase social
closeness, and to fulfil the require ments of social etiquette (Light,
1988, p. 76). Interactions with different goals may differ in many
ways. Social etiquette and expression of wants and needs, for example,
may be characterized by highly predictable interactions in which
communication rate is very im portant. Communication rate may also be
important when the goal of the interaction is to convey or receive
information (Light, 1988, p. 76).
AAC systems need to recognize these varying demands in order to
support communication more effectively.
2.3 Components of an AAC System
An AAC system (Figure 2.1) can be described in terms of its language
model, and its input and output interfaces (Demasco & Mineo,
1995). The input interface provides the user with a method for
selecting symbols (letters, words, or icons) represented in the
system. How symbols are represented, organized and processed is
specified in the language model. The user's message is presented by
the output interface.
Currently, AAC systems can accept input from a wide variety of
devices. Keys on a keyboard can be selected with the user's hands, or
with a stick fastened to a head-mount or held in the user's mouth. For
users with more limited motion, switch devices can be activated by
movement of the hand, foot, or eyebrow. A beam of light, emitted from
a head mounted source and detected by receivers on the AAC system, can
be used to make selections on a switch or a keyboard. There is even
work in progress to detect and follow the user's eye gaze (Sandler,
1994).
Figure 2.1: Components of an AAC system
[Figure Diagram]
LANGUAGE MODEL: - representation - organization - processing
PHYSICAL INPUT INTERFACE: - input devices - selection methods
PHYSICAL OUTPUT INTERFACE: - output devices
Selection methods can be generally classified as either direct or
scanning. With direct selection, the user indicates the desired item
from a set of items (Beukelman & Mirenda, 1992, p. 58). Spelling words
on a computer keyboard is an example of direct selection. Each key
represents a letter in the alphabet and is selected by the user via a
key stroke. Using a scanning method, items in the set are displayed in
some predetermined or der by the system, or by a conversational
partner or facilitator, and the user indicates when the desired item
has been presented (Beukelman & Mirenda, 1992, p. 62). In row-column
scanning, for example, symbols are organized into rows and columns and
the system high lights rows until the user indicates the row
containing the desired symbol. The system then highlights columns
until the user indicates the column containing the desired symbol. The
system selects the symbol located at the point where that row and
column intersect.
Scanning input can be slower than direct selection, because the user
must wait while the system traverses undesired items. However, direct
selection of even a relatively small number of items requires a fair
amount of motor dexterity. With scanning, an individual with severely
limited motor abilities is potentially able to select any symbol repre
sented in the system using only a single key or switch.
The words and messages of the language model that are available for
selection on an AAC system can be represented in a variety of symbol
sets. The most appropriate set for a specific user will depend on that
user's age, cognitive and language abilities, and perceptual abilities
(see Beukelman & Mirenda, 1992, pp. 21-27, for a discussion on
"representational symbols"). Letters, pictures, abstracted icon sets,
or combinations of all three are used by different systems.
The symbols available in a system must be organized and displayed to
the user in some fashion. For instance, in a letter-based system
performing row-column scanning, decisions must be made about how many
rows and columns to use, and in which order the letters should occur
in the columns. A system may contain more symbols than it can display
at one time. Symbols must then be organized to provide the user with a
consistent method for accessing them. This organization includes how
symbols are physically distributed on the system display, as well as
how hidden symbols are reached.
In addition to providing this vocabulary of symbols, an AAC system may
provide processing capabilities to facilitate its use. For instance, a
vocabulary symbol may have a phrase or sentence associated with it
which is retrieved by the system when the symbol is selected. Several
strategies of processing to increase communication rate are discussed
in Section 2.4.
Both visual and spoken output are available on many AAC
systems. Visual output methods include displaying symbols on a
computer screen, or printing symbols out on paper. Spoken output is
achieved with either digitized or synthesized speech. Digitized speech
is pre-recorded and fixed, while synthesized speech is generated at
the time of message production and is not constrained in terms of
message content. However, the voice quality of digitized speech is far
more natural than that of synthesized speech in current AAC systems.
2.4 Strategies for Accelerating Message Production
One of the great challenges to AAC has been to increase the rate of
message production by augmented communicators. With AAC systems,
production rates of between 2 and 20 words per minute are not
uncommon, an order of magnitude slower than for un augmented speakers
using their natural voices (Kraat, 1987, p. 63). This slow production
rate may affect how augmented communicators participate in
conversations, and how they are viewed by their conversational
partners.
Two acceleration strategies used in existing AAC systems are message
encoding and message prediction. Compansion, a third acceleration
strategy, in which the user in puts a sentence in "telegraphic" style
and the system completes the sentence, is discussed in Section 2.5.1.
Message encoding refers to retrieving a word, or a longer unit of
text, by using an associated code that requires fewer
selections. Codes can consist of letters, numbers, icons, or some
combination of these. For example, "Please open the door" may be
associated with the code "OD", the initial letters of the salient
words "open" and "door" (salient letter codes, Light & Lindsay, 1992,
p. 35). An alternate encoding might be "DD", be cause the sentence is
giving "directions" regarding the "door" (letter category codes, Light
& Lindsay, 1992, p. 35).
Flexible abbreviation expansion (Stum & Demasco, 1992) is an
alternative letter coding system for abbreviating words. In a standard
coding or abbreviation scheme, there is a fixed set of codes which is
stored by the user ahead of time. The processing done by the system is
a simple table look-up. In contrast, flexible abbreviation expansion
has no fixed table of codes. Instead, the user and system follow rules
to expand the letter codes.
Message prediction is a dynamic strategy, whereby the system makes use
of earlier portions of the message to interpret and predict the next
icon, letter, word, or larger segment of text (Beukelman & Mirenda,
1992, pp. 42-44). On a spelling-based system, for example, after the
user selects the letters "s", "t", and "u", the system may predict the
word in progress to be "student", "stupid", or "studying". If the
intended word is in this list, the user can select it immediately
rather than continuing to spell it. A system could also make use of
syntax rules (VanDyke et al., 1992) to better predict the intended
word.
2.5 Example AAC Techniques
To illustrate possible techniques for AAC, two systems are described
here in detail. The first, Compansion, is different from other
systems in that it uses natural language processing techniques to
complete a telegraphic sentence once the user has entered it. The
second system, the Liberator TM (Prentke Romich Company), is an
example of a commercially available system, and contains a variety of
tools with which the user can edit and navigate through stored
text. One participant in the evaluation study, discussed in Chapter 5,
normally communicates using the Liberator.
Complaint Categories
Copyright complaintwire.org
I apologize for the experience you had with the company I used to represent. As it stands, I am no longer affiliated with Jet Direct Funding. Once we processed your file, it was determined that you were not qualified for our services and you were supposed to receive a courtesy call from underwriting. I am not sure why you were not contacted.
I have already submitted a request to Complaint Wire to remove this message, as it is a defamation to my character. I am currently working for a different company in the same industry and if you Google my name it comes up with this message. I am respectfully asking you to delete this posting, as your information was never disclosed, sold, or misused by Jet Direct or any other company to my knowledge.
Thank you,
Ryan
Read this story before paying money for a modification. What they don't know is banks take the names of the 3rd parties that call in on the behalf of you and report them to the FTC and other federal agencies. They will get what's coming to them sooner or later.