1. NATURAL LANGUAGE
PROCESSING IN ALTERNATIVE
AND AUGMENTATIVE
COMMUNICATION
S.R.JHANANI
S.DIVYA
3RD YEAR B.TECH – IT
MEENAKSHI SUNDARARAJAN
ENGINEERING COLLEGE

2. NATURAL LANGUAGE PROCESSING
 HUMAN-COMPUTER INTERACTION
 Goal - “to achieve human-like language processing”.
 Encompasses the automation of linguistic forms, activities or
methods of communication.
 Presently implemented using machine learning algorithms.
Previously – Decision trees
Now – Statistical methods
 Future – Unsupervised, Semi-supervised algorithms.
HUMAN COMPUTER
PROCESSING
COMMUNICATE
AI
Ling
uistic
s
NLP

3. LEVELS
PHONOLOGY
MORPHOLOGY
LEXICAL
SYNTACTIC
SEMANTIC
DISCOURSE
PRAGMATIC
-Interprets sounds within and across words
-Breaks down words into morphemes
-Assign meanings to individual words
-Check if sentence is grammatically correct
-Performs disambiguation of words
-Makes connection between sentences
-Uses contextual and situational meanings

4. APPROACHES
1. Symbolic
 Explicit depiction of facts about language through well-understood
knowledge schemes and algorithms
 Deep analysis of linguistic phenomena
2. Statistical
 Uses mathematical techniques and large texts of corpora without
incorporating world knowledge
 Output produced by each state has a definitive probability
3. Connectionist
 Combines statistical learning with various representation theories
 Allows transformation, inference and logic formulae manipulation
 Less constrained architecture

5. STAGES
PARSING TRANSLATING
GENERATING
INPUT
1. Phonology
2. Morphology
3. Lexical
4. Syntactic
5. Semantic
6. Discourse
7. Pragmatic

6. EVALUATION TYPES
• In terms of gold-standard
• In terms of overall tasks
Intrinsic vs.
Extrinsic
• Quality of process, result
• Design, Algorithm, Resources
Black-box
vs. White-
box
• Objective Evaluation
• Subjective Evaluation
Automatic
vs. Manual

7. DATA FLOW DIAGRAM - NLP

8. AUGMENTATIVE AND ALTERNATIVE
COMMUNICATION
 Way to communicate when one does
not have the physical ability to use
verbal speech or writing.
 AAC systems - Designed to help
people express their thoughts, needs,
wants and ideas.
 Access methods used - direct selection
by pointing / reaching /canning using a
switch connected to the device / eye
gaze
 Two groups of communication
 Unaided – Gestures, hand signs,
expressions
 Aided – Communication boards /
devices

9. ROLE OF NLP IN AAC
 Common concept – INFORMATION RETRIEVAL
 Obtains information relevant to the input
 Factors : Syntactic, Ambiguity
 ME / SEE / CAT / TO EAT = I saw the cat eating.
 CAT / TO EAT / SEE / ME =The cat ate and I saw it (or) The cat
that ate saw me.
 Goal – Enhance communication rate without limiting their
expressing capability.
 Solutions –
 Improving Pragmatics, Contextual resources
 Lexicon and Methodology
 Efficient keyboard setup, Proper word prediction, Structure
prediction.

10. Cont’d…
The sentence “Work I Done” is presented as follows
 Step 1: The words in the sentence are broken separately. The
result is: “Work, I, Done”.
 Step 2: The semantic parser parses the words and matches the
words with the appropriate grammar. Subsequently, the context is
also analyzed.
 Step 3: The words are also compared with relevant aids such as
pictures to identify the relations and patterns of them.
 Step 4: The semantic strategy gives the result as “Work Is Done
by Me”.
 Step 5: The results of the strategy are considered and the
individual’s cognitive level is evaluated.
 Step 6: If the cognitive level is very low, the picture-based
communication is made. If it is medium, then paper based or even
speech-based communication can be made to convey the end
result.

11. COMPANSION
 Includes abbreviation expansion, character prediction, word
and string prediction, reduced disambiguation and special
keywords, symbolic entry and coding methods.
 Text-Entry inteface driven by continuous pointing gestures
 Eye-trackers, Joysticks and Touch-screen
 Mouse; Novices- 25 words per minute, experienced users - 39
words per minute.
Uninflected content
words
Full phrase or
Sentence
I am typing my di………
1. dish
2. divide
3. distance
4. dissertion
5. dimple
ABC DEF GHI
MNO PQR
STU VW XYZ
JKL
error space . , / ?

12. ASSESSMENT
 AAC system tends not only to serve as an aid for communication
but also to improve the language intelligibility.
Issues in AAC :
 No pre-stored samples to the patients in the AAC systems
 No option for dynamic choice of the vocabulary in an AAC system.
Application of NLP to AAC :
 The language representation of NLP is easier
 Enables better interpretation and automatic content maintenance
Two majorly useful fields :
 Interface design
 Word prediction

13. CONCLUSION
 Natural Language Processing can be effectively integrated
into Augmentative and Alternative Communication.
 Techniques are developed to overcome the issue of Data
Collection
 AAC systems are more flexible, expressive tools with
enhanced rate of computation when incorporated with NLP
methodologies.
 AAC system assures clarity of information through different
means for users.
 The application of NLP in AAC is expected to develop a new
world of communication in terms of clarity and ease in
understanding and capabilities.

14. REFERENCES
 Jurafsky, James (2008). Speech and Language Processing. An
Introduction to Natural Language Processing, Computational
Linguistics, and Speech Recognition (in English) (2nd ed.). Upper
Saddle River (N.J.): Prentice Hall.
 Roger Schank, 1969, A conceptual dependency parser for natural
language Proceedings of the 1969 conference on Computational
linguistics, Sång-Säby, Sweden pages 1-3
 McCorduck 2004, p. 286, Crevier 1993, pp. 76−79, Russell &
Norvig 2003, p. 19
 http://en.wikipedia.org/wiki/Natural_language_processing
 http://en.wikipedia.org/wiki/Augmentative_and_alternative_commu
nication
 http://www.asha.org/NJC/faqs-aac-basics.htm