The paper describes the recognition of diphthong and triphone signs useful in automatic generation of English text from Pitman
Shorthand Language (PSL) document. The PSL is used to note down the dictated/spoken text and is widely practiced in all organizations
where English is the transaction medium. This has a built- in practical advantage because of which it is universally acknowledged.
This recording medium will continue to exist in spite of considerable developments in Speech Processing Systems, which are
not universally established yet. Because of wide usage of PSL and the effort in its automation, PSL processing has emerged
as a potential problem for research in the areas of Pattern Recognition, Image Processing, Artificial Intelligence and Document
There are six long and six short vowels in PSL. These vowels are represented by signs /symbols that over ride a stroke symbol
and require recognition for composing English text from phonetic text documented through PSL. The work pertaining to other
constructs of PSL is already carried out at word level by the authors [7,8]. But during dictation, it is common that the vowels are joined to form one syllable, called Diphthong. The diphthong appended
with a tick-mark is called Triphone and represents any vowel that immediately follows the diphthong in a stroke. The diphthongs
are to be cognized and recognized to generate the correct English equivalent text. The present work comprises of the definition
of diphthong primitives, creation of knowledge base and the development of an algorithm for their recognition. A suitable
shape recognition algorithm is assumed available here. This work is new and this module serves as a prerequisite for the complete
recognition of PSL document and generation of an equivalent and correct English text.
[Show abstract][Hide abstract] ABSTRACT: A verbatim written transcript of speech would have many applications in the office, in verbatim reporting and as an aid for the deaf. Unfortunately, the automatic recognition of unlimited vocabulary speech is not likely to be possible for a number of years. An alternative strategy, investigated at Southampton University, is to attempt the less complex task of automatically transcribing handwritten notes made using the Pitman shorthand notation.Pitman shorthand outlines can be split into two classes of characters, shortforms (comprising over 90 of the most frequently used words and phrases in the English language) and vocalised outlines which can represent any word pseudo-phonetically. The shortforms represent as much as 50% of normal shorthand and are recognised directly using a dynamic programming technique with typical recognition accuracy of over 90%. Vocalised outlines are recognised using a syntactic method which interacts with a knowledge source derived from analysis of a large number of shorthand outlines. This paper describes the recognition strategy for Pitman shorthand shortforms which uses the dynamic programming template matching technique.
Data provided are for informational purposes only. Although carefully collected, accuracy cannot be guaranteed. The impact factor represents a rough estimation of the journal's impact factor and does not reflect the actual current impact factor. Publisher conditions are provided by RoMEO. Differing provisions from the publisher's actual policy or licence agreement may be applicable.