CSIS Shorthand Handwriting Recognition for PenCentric Interfaces Charles

CSIS Shorthand Handwriting Recognition for Pen-Centric Interfaces Charles C. Tappert 1 and Jean R. Ward 2 1 School of CSIS, Pace University, New York, USA 2 Pen Computing Consultant, Massachusetts, USA PLT 2007

CSIS Thesis: Pen-Centric, Chatroom-Like Shorthand Interfaces • Will provide critical infrastructure for many pen-centric applications • Will provide fast text input • Will have greatest impact on applications running on small mobile devices PLT 2007

CSIS Agenda • Handwriting – Fundamental Property of Writing – Handwriting Recognition Difficulties • Historical Shorthand Alphabets • Online (Pen-Centric) Handwriting Recognition – Online more accurate than Offline Recognition – Online Info Can Complicate Recognition Process – Design Tradeoffs/Decisions • Pen-Centric Shorthand Alphabets • Pen-Centric Word/Phrase Shorthand • Allegro/Chatroom Experimental Shorthand System PLT 2007

CSIS Fundamental Property of Writing • Differences between different characters are more significant than differences between different drawings of the same character • This makes handwritten communication possible PLT 2007

CSIS Fundamental Property of Writing • Property holds within subalphabets of uppercase, lowercase, and digits, but not across them • “I”, “l”, and “ 1” written with single vertical stroke • “O” and “ 0” written similarly with an oval PLT 2007

CSIS Handwriting Recognition Difficulties • Shape, size, and slant variation • Similarly shaped characters – U and V • Careless writing – in the extreme, almost illegible writing • Resolving difficult ambiguities requires sophisticated recognition algorithms, syntax/semantics PLT 2007

CSIS Historical Shorthand Alphabets (prior to pen computing) • Famous writings were written in shorthand – Cicero’s orations – Martin Luther’s sermons – Shakespeare’s and George Bernard Shaw’s plays • We focus on shorthand appropriate for PDAs • Two main types of shorthand – Non-geometric shorthand – Geometric shorthand • Small number of basic shapes • Shapes reused in multiple orientations PLT 2007

CSIS Tironian Alphabet, 63 B. C. PLT 2007

CSIS Stenographie Alphabet, 1602 PLT 2007

CSIS Stenographie Alphabet, 1602 Geometric shorthand – basic shapes/orientations PLT 2007

CSIS Moon Alphabet, 1894 • Geometric shorthand – basic shapes/orientations PLT 2007

CSIS Other Historical Shorthand Systems • Phonetic alphabets – Pitman (1837) – Gregg (1885) • Systems for the blind – Braille (1824) • Cursive shorthands – Gabelsberger (1834) PLT 2007

CSIS Online (Pen-Centric) Handwriting Recognition • Machine recognizes the writing as the user writes • Digitizer equipment captures the dynamic information of the writing – Stroke number, order, direction, speed – A stroke is the writing from pen down to pen up PLT 2007

CSIS Online (Pen-Centric) more accurate than Offline (Static) Recognition • Can use both dynamic and static information • Can often distinguish between similarly shaped characters – E. g. , 5 versus S where the 5 is usually written with two strokes and the S with one stroke PLT 2007

CSIS Online Information Can Complicate Recognition Process • Segmentation ambiguities – Character-within-character problem – cl versus d • Large number of possible variations – E can be written with one, two, three, or four strokes, and with various stroke orders and directions – Four-stroke E has 384 variations (4! stroke orders x 24 stroke directions) PLT 2007

CSIS Design Tradeoffs/Decisions • No constraints on the user – Machine recognizes user's normal writing • User severely constrained – Must write in particular style such as handprint – Must write strokes in particular order, direction, and graphical specification • Simplest is one stroke per character, one stroke direction, one shape PLT 2007

CSIS Pen-Centric Shorthand Alphabets • Some of the earliest were for CAD/CAM • Others developed for text input on PDAs • We review geometric and non-geometric shorthands appropriate for small devices • Historical alphabets presented above could be used for machine recognition • In addition to shape and orientation, stroke direction can differentiate among symbols PLT 2007

CSIS Allen Alphabet PLT 2007

CSIS Allen Alphabet Basic Shapes and Orientations PLT 2007

CSIS Goldberg Alphabet PLT 2007

CSIS Goldberg Alphabet Basic Shapes and Orientations PLT 2007

CSIS Graffiti Alphabet (non geometric ) PLT 2007

CSIS Allegro Alphabet (non geometric) PLT 2007

CSIS Simplified Design Tradeoffs/Decisions for Graffiti and Allegro PDA Alphabets • Small alphabet – one case rather than both upper and lowercase • Small number of writing variations per letter – preferably one • One stroke per character (character = stroke) – allows machine to recognize each character upon pen lift • Separate writing areas for letters and digits – avoids confusion of similarly shaped letters and digits PLT 2007

CSIS Graffiti and Allegro Commercially Successful Shorthands • High correspondence to Roman alphabet – Easier to learn – Graffiti used in Palm OS devices • notably the Palm Pilot and Handspring models – Allegro used in Microsoft Windows devices • Geometric alphabets not successful PLT 2007

CSIS Pen-Centric Word/Phrase Shorthand e. g. , Chatroom Shorthand • Further increase speed of text entry • Potential applications – Where input speed important – Where word/phrase abbreviations occur frequently – e. g. , email PLT 2007

CSIS Allegro/Chatroom Shorthand System • Developed for M. S. dissertation – Student was hearing impaired – Developed as output component of communication system • Handwriting to text to speech • Two input writing areas – One for Allegro (all-purpose) – One for chatroom-like words/phrases (e. g. , CUL, F 2 F) PLT 2007

CSIS Allegro/Chatroom Shorthand System PLT 2007

CSIS Allegro/Chatroom Shorthand System PLT 2007

CSIS Allegro/Chatroom Shorthand System Preliminary Experimental Results • Allegro/Chatroom pen-centric shorthand input faster than typing text and comparable to typing text and chatroom shorthand characters PLT 2007

CSIS Conclusions: Pen-Centric, Chatroom-Like Shorthand Interfaces • Will provide critical infrastructure for many pen-centric applications • Will provide fast text input • Will have greatest impact on applications running on small mobile devices PLT 2007