127 results about "Transliteration" patented technology

The transliteration scheme developed as the present invention is contingent upon two languages, namely the keyboard language and the target language. While the invention is independent of the actual languages in question, save to the extent that they must be phonetic or pseudo-phonetic and the keyboard language must possess a script, it is nonetheless convenient to cast the invention within the framework of two specific languages. In this regard, English has been chosen as the keyboard language, and Hindi (a language widely spoken in India) has been chosen as the target language. An understanding of the current invention is possible without any knowledge of Hindi by a practitioner skilled in the art.

A method for transliteration includes receiving input such as a word, a sentence, a phrase, and a paragraph, in a source language, creating source language sub-phonetic units for the word and converting the source language sub-phonetic units for the word to target language sub-phonetic units, retrieving ranking for each of the target language sub-phonetic units from a database and creating target language words for the word in the source language based on the target language sub-phonetic units and ranking of the each of the target language sub-phonetic units. The method further includes identifying candidate target language words based predefined criteria, and displaying candidate target language words.

The present invention provides a method and apparatus for training a parsing statistic model, a method and apparatus for transliteration. Said parsing statistic model is to be used in transliteration between a single-syllable language and a multi-syllable language and includes sub-syllable parsing probabilities of said multi-syllable language. Said method for training the parsing statistic model comprising: inputting a bilingual proper name list as corpus, said bilingual proper name list includes a plurality of proper names of said multi-syllable language and corresponding proper names of said single-syllable language respectively; parsing each of said plurality of proper names of multi-syllable language in said bilingual proper name list into a sub-syllable sequence using parsing rules; determining whether said parsing is correct according to the corresponding proper name of said single-syllable language in said bilingual proper name list; and training said parsing statistic model base on the result of parsing that is determined as correct.

A method, apparatus, and computer instructions for a method in a portable device for transliterating text. An image of the text is generated using a camera function in the portable device. The image is sent with an identification of a source language and a target language to a transliteration service using a wireless communications link. A response is received from the transliteration service, wherein the response contains a transliteration of the text in the target language. The transliteration is then presented on the portable device. The presentation may be, for example, text displayed on the portable device or in the form of speech presented audibly to the user.

A system for translating a body of text in an initial language into a target language, that comprises an input device for imputing a body of text comprising a plurality of elements, a first analyzer for analyzing said text and identifying one or more possible characters of said initial language corresponding to respective said elements, a second analyzer for analyzing a stream of said identified characters to identify known characters or recognizable patterns thereof and assign thereto one or more potential translations into said target language, a third analyzer for analyzing the potential translations in conjunction with one or more determinatives representative of a conceptual framework of said text to determine which potential translations correspond with said conceptual framework, and an output device for outputting one or more potential translations determined to correspond with said conceptual framework.

The present invention provides a method and apparatus for training a parsing statistic model, a method and apparatus for transliteration. Said parsing statistic model is to be used in transliteration between a single-syllable language and a multi-syllable language and includes sub-syllable parsing probabilities of said multi-syllable language. Said method for training the parsing statistic model comprising: inputting a bilingual proper name list as corpus, said bilingual proper name list includes a plurality of proper names of said multi-syllable language and corresponding proper names of said single-syllable language respectively; parsing each of said plurality of proper names of multi-syllable language in said bilingual proper name list into a sub-syllable sequence using parsing rules; determining whether said parsing is correct according to the corresponding proper name of said single-syllable language in said bilingual proper name list; and training said parsing statistic model base on the result of parsing that is determined as correct.

A system that incorporates teachings of the subject disclosure may include, for example, receiving a graphical representation of an object surface having a number of inscriptions indicative of information encoded upon the object surface. The graphical representation of the object surface is transcribed by the system to determine markings from the inscriptions. A number of alternative corresponding symbols are determined by the system. The alternative corresponding cuneiform symbols are determined from a number of the markings. A number of alternative transliterations are determined by the system. The alternative transliterations are determined from of a symbol of the multiple alternative corresponding symbols. A number of alternative translations are also determined by the system of a transliteration of the multiple translations transliterations. Other embodiments are disclosed.

A computer-implemented method for selecting a desired Roman or non-Roman-alphabet character or objects from a set of non-Roman characters or objects may include steps of providing an association database that includes, for each non-Roman-alphabet character of the set, a Roman alphabet or other phonetic transliteration associated with each said non-Roman-alphabet character and a plurality of entries that are associated with each said non-Roman-alphabet character; receiving a phonetic transliteration of the desired non-Roman-alphabet character or data object and at least one associated entry that is associated with the desired non-Roman-alphabet character or other similar symbolic input; accessing the association database and identifying as candidate characters those characters of the set that are associated with the received phonetic transliteration and with the at least one received associated entry; if a number of candidate characters is greater than one, receiving additional associated entries and repeating the accessing and identifying step until a number of candidate characters is narrowed down to a single candidate character, and providing the single candidate character as the desired non-Roman-alphabet character. Also, derived from the principles described above, this invention includes a variety of methods for improving the efficiency of search engines through use of associations and other means of providing context for the item(s) being searched.

Described within are systems and methods for transliterating and translating source non-Romanized language text strings from a plurality of electronic sources to Romanized target language text strings by converting the source non-Romanized language text strings to a standard document encoding format, splitting the source non-Romanized language text strings into smaller units, transforming the smaller units into entity profiles, processing the entities profiles with data from external databases, translating the entities in the entity profiles into a Romanized target language, and outputting the entities into a plurality of data formats for external systems.

The invention provides a multimedia transliteration method is applied to a multimedia transliteration system and comprises the following steps of: S1, receiving a demonstration manuscript, and constructing a key information tree of the demonstration manuscript; S2, receiving voice data, carrying out voice identification on the voice data, and obtaining transliteration texts of the voice data; S3, synchronizing the voice data and the transliteration texts with the demonstration manuscript by means of the key information tree; and S4, displaying the demonstration manuscript with the synchronized voice data and transliteration texts to a user. The user can hear the voices of a speaker and see the texts transliterated by the voices of the speaker while seeing the demonstration manuscript, and furthermore, the transliteration texts are segmented according to sub-themes included in each page of the transliteration texts, the transliteration texts of the same sub-theme is in one segment, and the transliteration texts of different sub-theme serve as different segments, so that the user can conveniently understand the transliteration texts, and the experience of the user is further improved.

The invention relates to a reverse Chinese-English transliteration method and a device thereof. A Chinese transliteration name to be translated is converted into a pinyin sequence, and a statistics transliteration module is used for generating transliteration candidates; the transliteration candidates are revised into real English words by a revision module, and the revision module uses real English words collected from a great quantity of webpages to form a vocabulary; revised real English words are used to be inquiry to verify translation results, and webpage resources obtained with a search engine are used to rearrange the revised transliteration candidates; words which appear as a named entity role on the webpage are given high marks so as to filter common English words. The method can overcome the problems that a statistic model loses aphonic syllables or chooses wrong same pronouncing syllables in the process of transliteration and the like, and effectively improves precision rate of transliteration. Experiences prove that the precision rate of transliteration is improved by 17.55% in open beta.

An electronic messaging system for both participating institutions and nonparticpating institutions and their populations. When an institution is participating in the system of the present invention, both message senders and recipients are authenticated and known and verified before any communication can take place. Messages for institutions not currently participating in the system are converted to printed mail for delivery to the non-participating institution using traditional postal systems. The present invention also teaches novel message processing techniques that take advantage of the electronic format of the messages to provide automated security and translation and / or transliteration services and further teaches the novel feature of marking incoming messages with a code to assist in accurately and secure delivery of reply messages to the appropriate party.