434 results about "First language" patented technology

The present invention allows subscribers to an online information service to participate in real-time conferencing or chat sessions in which a message originating from a subscriber in accordance with a first language is translated to one or more languages before it is broadcast to the other conference areas. Messages in a first language are translated automatically to one or more other languages through language translation capabilities resident at online information service host computers. Access software that subscribers use for participating in conference is integrated with speech recognition and speech generation software such that a subscriber may speak the message he or she would like to share with other participants and may hear the messages from the other participants in the conference. Speech-to-speech translation may be accomplished as a message spoken into a computer microphone in accordance with a first language may be recited by a remote computer in accordance with a second language.

A domain-based speech recognition method and apparatus, the method including: performing speech recognition by using a first language model and generating a first recognition result including a plurality of first recognition sentences; selecting a plurality of candidate domains, by using a word included in each of the first recognition sentences and having a confidence score equal to or higher than a predetermined threshold, as a domain keyword; performing speech recognition with the first recognition result, by using an acoustic model specific to each of the candidate domains and a second language model and generating a plurality of second recognition sentences; and selecting at least one or more final recognition sentence from the first recognition sentences and the second recognition sentences. According to this method and apparatus, the effect of a domain extraction error by misrecognition of a word on selection of a final recognition result can be minimized.

A voice query extension method and system. The voice query extension method includes: detecting voice activity of a user from an input signal and extracting a feature vector from the voice activity; converting the feature vector into at least one phoneme sequence and generating the at least one phoneme sequence; matching the at least one phoneme sequence with words registered in a dictionary, extracting a string of the matched words with a linguistic meaning, and selecting the string of the matched words as a query; determining whether the query is in a predetermined first language, and when the query is not in the first language as a result of the determining, converting the query using a phoneme to grapheme rule, and generating a query in the first language; and searching using the query in the first language.

A text-to-speech system adapted to operate on text in a first language including sections in a second language, includes a grapheme / phoneme transcriptor for converting the sections in the second language into phonemes of the second language; a mapping module configured for mapping at least part of the phonemes of the second language onto sets of phonemes of the first language; and a speech-synthesis module adapted to be fed with a resulting stream of phonemes including the sets of phonemes of the first language resulting from mapping and the stream of phonemes of the first language representative of the text, and to generate a speech signal from the resulting stream of phonemes.

A first recognizing unit recognizes a first-language speech as a first-language character string, and outputs a first recognition result. A second recognizing unit recognizes the first-language speech as a most probable first-language example from among first-language examples stored in an example storing unit, and outputs a second recognition result. A retrieving unit retrieves, when a similarity between the first recognition result and the second recognition result exceeds a predetermined threshold, a second-language example corresponding to the second recognition result from the example storing unit.

Systems and methods to process and correct spelling errors for non-Roman based words such as in Chinese, Japanese, and Korean languages using a rule-based classifier and a hidden Markov model are disclosed. The method generally includes converting an input entry in a first language such as Chinese to at least one intermediate entry in an intermediate representation, such as pinyin, different from the first language, converting the intermediate entry to at least one possible alternative spelling or form of the input in the first language, and determining that the input entry is either a correct or questionable input entry when a match between the input entry and all possible alternative spellings to the input entry is or is not located, respectively. The questionable input entry may be classified using, for example, a transformation rule based classifier based on transformation rules generated by a transformation rules generator.

The present invention discloses a speech-to-speech translation device which allows one or more users to input a spoken utterance in one language, translates the utterance into one or more second languages, and outputs the translation in speech form. Additionally, the device allows for translation both directions, recognizing inputs in the one or more second languages and translating them back into the first language. The device recognizes and translates utterances in a limited domain as in a phrase book translation system, so the translation accuracy is essentially 100%. By limiting the domain the system increases the accuracy of the speech recognition component and thus the accuracy of the overall system. However unlike other phrase book systems, the device also allows wide variations and paraphrasing in the input, so that the user is much more likely to find the desired phrase from the stored list of phrases. The device paraphrases the input to a basic canonical form and performs the translation on that canonical form, ignoring the non-essential variations in the surface form of the input. The device can provide visual and / or auditory feedback to confirm the recognized input and makes the system usable for non-bilingual users with absolute confidence.

A method for speech synthesis of a word in a first language, comprising dividing the word into a first sequence of pronunciation phonemes in the first language, mapping the first phoneme sequence to a second sequence of pronunciation phonemes in at least one second language, and generating an audio output of the phonemes in the second phoneme sequence using prosody models adapted for the at least one second language. According to this method, an audio output of a word in a first language can be generated by a speech synthesizing engine not having actual support for this language. Instead, the pronunciation phonemes of the word are mapped onto phonemes of at least one second language, for which the speech synthesizing engine does have support.

A system for automating the quality evaluation of a translation. The system may include a computer having a processor and memory device operably connected to one another. A source text in a first language may be stored within the memory device. A target text comprising a translation of the source text into a second language may also be stored within the memory device. Additionally, a plurality of executables may be stored on the memory device and be configured to, when executed by the processor, independently identify a test sample comprising one or more blocks, each comprising a matched set having a source portion selected from the source text and a corresponding target portion selected from the target text.

A string matching method, system, and a computer-readable medium storing instructions for determining and obtaining a representative string for a plurality of strings that are written in various manners but share the same meaning. The string matching method includes: converting the input string into one or more second-language strings with reference to a language mapping table, which stores a plurality of pieces of mapping information for mapping a first-language string to a second-language string, and generating a conversion list; searching a representative list database, which storing a plurality of records each with a representative string and a corresponding second-language representative string, for records including the same second-language representative strings as the respective second-language strings in the conversion list and generating a candidate list; and determining a representative string from the candidate list to be an output representative string. Therefore, the string matching can provide string-based multimedia data classification scenarios.

A computer implemented method translates a textual input in a first language to a textual output in a second language. An input logical form is generated based on the textual input. When a plurality of transfer mappings in a transfer mapping database match the input logical form (or at least a portion thereof) one or more of those plurality of matching transfer mappings is selected based on a predetermined metric. Textual output is generated based on the selected transfer logical form.

A machine translation method for translating source text from a first language to target text in a second language includes receiving the source text in the first language and accessing a library of bi-fragments, each of the bi-fragments including a text fragment from the first language and a text fragment from the second language, at least some of the bi-fragments comprising non-contiguous bi-fragments in which at least one of the text fragment from the first language and the text fragment from the second language comprises a non-contiguous fragment.

An apparatus includes a first search unit that searches a storage unit for a first example of a first language based on a sentence in the first language; a second search unit that searches for a second example of a second language corresponding to the first example, the second language containing the same meaning as the first example; a determining unit that determines whether a plurality of the second examples exist; a first acquisition unit that acquires the first example corresponding to each of the second example from the storage unit; a second acquisition unit that acquires the second example corresponding to the first example acquired from the storage unit; and a choice generating unit that generates the first example acquired associated with the least number of the second examples acquired as a choice of the first example to be output.

A computer system with an appropriate set of instructions to allow the computer system to serve as a translation device for use in a structured interview between an interviewer using a first language and an interviewee in a second language in order to minimize or eliminate that need for a human translator during the acquisition of routine information. Problems addressed include: determination of the appropriate language for use as the second language, the use of a single display screen through the use of a toggle function to toggle from the first language to the second language, delivery of context sensitive audio files while controlling the number of screens to be created and presented to the interviewer, and the creation of a set of discharge instructions. A preferred set of hardware and a mobile cart is discussed.

A machine translation method includes receiving source text in a first language and retrieving text fragments in a target language from a library of bi-fragments to generate a target hypothesis. Each bi-fragment includes a text fragment from the first language and a corresponding text fragment from the second language. Some of the bi-fragments are modeled as elastic bi-fragments where a gap between words is able to assume a variable size corresponding to a number of other words to occupy the gap. The target hypothesis is evaluated with a translation scoring function which scores the target hypothesis according to a plurality of feature functions, at least one of the feature functions comprising a gap size scoring feature which favors hypotheses with statistically more probable gap sizes over hypotheses with statically less probable gap sizes.

Methods and systems for changing language characters of graphical user interfaces and application programming interfaces are disclosed. Embodiments comprise a method of changing the characters of a first language displayed on a device interface screen to a second language upon activation of an element on the device. In some embodiments, the element for changing the language is a menu bar item. In one embodiment, the element for changing the language is a mechanical switch. In another embodiment, the element for changing the language of the displayed characters is a touch-screen target. Some embodiments comprise systems such as industrial and personal computers, while other embodiments comprise smaller electronic devices such as cellular telephones, handheld computers, and portable gaming devices.

A method of testing a computer program written for use in a foreign language can include identifying text presented upon a display screen, wherein the text is in a first language, and automatically acquiring the text from the display screen. The text can be translated from the first language to a second language. The translated text can be presented in the second language upon the display screen.

A method and apparatus for enabling communication between a first user and a second user speaking different natural languages, comprising the steps of: providing a first apparatus; initiating a conversation between a first user and a second user speaking different languages; capturing a first audio file from a first user speaking a first language; transmitting the first audio file to the language translation software; translating the first audio file to a second language using the language translation software to provide a first audio file translation; and returning the first audio file translation to the first user through the output of translator device such that the first audio file translation is only audible to the first user.

A method of and a system for processing an enterpise an application request on an end user application and an application server. This is accomplished by initiating the application request on the end user application in a first language (such as a markup language) with a first application program (such as a Web browser), and transmitting the application request to the server and converting the application from the first language of the first end user application to a language running on the application server, processing the application request on the application server, and transmitting the response from the application server back to the end user application, and converting the response from the language running on the application server to the language of the end user application. The end user application and the application server have at least one connector between them, and the steps of (i) converting the application request from the language of the end user application (as a source language) to the language running on the application server (as a target language), and (ii) converting the response to the application request from the language running on the application server (as a source language) to the language of the end user application (as a target language), each include the steps of invoking connector metamodels of the respective source and target languages, populating the connector metamodels with metamodel data of each of the respective source and target languages, and converting the source language to the target language.

Systems and processes for language identification from short strings are provided. In accordance with one example, a method includes, at a first electronic device with one or more processors and memory, receiving user input including an n-gram and determining a similarity between a representation of the n-gram and a representation of a first language. The representation of the first language is based on an occurrence of each of a plurality of n-grams in the first language and an occurrence of each of the plurality of n-grams in a second language. The method further includes determining whether the similarity between the representation of the n-gram and the representation of the first language satisfies a threshold.

A method of machine translation, using a bilingual corpus containing translation pairs each consisting of a sentence of a first language and a sentence of a second language, for translating an input sentence of the first language to the second language, including the steps of: receiving the input sentence of the first language and extracting, from the bilingual corpus, a sentence of the second language forming a pair with a sentence of the first language with highest similarity to the input sentence; applying an arbitrary modification among a plurality of predetermined modifications to the extracted sentence of the second language, and computing likelihood of sentences resulting from the modification; selecting a prescribed number of sentences having high likelihood from among the sentences resulting from the modification; repeating, on each of the sentences selected in the step of selecting, the steps of extracting, computing and selecting, until the likelihood no longer improves; and outputting, as a translation of the input sentence, a sentence having the highest likelihood among the sentences of the second language left at the end of the step of repeating.

A method of and a system for processing an enterprise application request on an end user application and an application server. This is accomplished by initiating the application request on the end user application in a first language (such as a markup language) with a first application program (such as a Web browser), and transmitting the application request to the server and converting the application from the first language of the first end user application to a language running on the application server, processing the application request on the application server, and transmitting the response from the application server back to the end user application, and converting the response from the language running on the application server to the language of the end user application. The end user application and the application server have at least one connector between them, and the steps of (i) converting the application request from the language of the end user application (as a source language) to the language running on the application server (as a target language), and (ii) converting the response to the application request from the language running on the application server (as a source language) to the language of the end user application (as a target language), each include the steps of invoking connector metamodels of the respective source and target languages, populating the connector metamodels with metamodel data of each of the respective source and target languages, and converting the source language to the target language.

The present invention is related to systems and methods for translating language text on a mobile camera device offline without access to the Internet. More specifically, the present invention relates to systems and methods for displaying text of a first language and a translation of the first language text into a second language text which is displayed in real time in augmented reality on the mobile device. The processing can use a single line or a multiline algorithm designed with a plurality of processing innovations to insure accurate real-time translations without motion jitter. The invention may be used to help travelers in a foreign country with difficulties in reading and understanding text written in the local language of that country. The present invention may be utilized with wearable computers or glasses, producing seamless augmented reality foreign language translations. Some embodiments are particularly useful in translations from Asian languages to English.

A dialogue supporting apparatus is provided which carries out a trade-off between the speed of the translation process and the fluency of the translation result, in accordance with the contents of a dialogue. The dialogue supporting apparatus includes a first input accepting unit 101 which accepts an utterance of a user 1 in a first language, a first translation processing unit 102 which translates the accepted utterance into a predetermined second language so as to output first translated utterance information, a first output unit 103 which conveys the first translated utterance information to a user 2, a second input accepting unit 104 which accepts an utterance of the user 2, a second translation processing unit 105 which translates the accepted utterance of the user 2 into the first language so as to output second translated utterance information, a second output unit 106 which conveys the second translated utterance information to the user 1, an output time determination unit which analyzes a characteristic included in the utterance of the user 1 and determines the upper limit for the translation time for an utterance to be accepted following the utterance of the first user. The second translation processing unit 105 outputs second translated utterance information acquired within such translation time.

A recognition and translation method of character image and a device are disclosed. The method comprises the following steps: obtaining one or a plurality of first language character image or video; detecting the character areas of each first language character from the image or video; recognizing the characters in each character area; dividing the terms formed by the recognized characters into one of a plurality of booked categories and adopting a translation rule corresponding to the divided category to translate the terms into a second language or more other languages; and displaying the translation result. By adopting the invention, the key characters in a natural scene image or video such as instructions in road nameplates, advertisements, bulletins, menus and the like can be automatically recognized and translated by a mobile terminal conveniently and rapidly.

A writing advisor program (20) receives a proposed text in an author's second language (L2) and determines at least one candidate replacement word for a selected word based on a determined language model (p(c)) and a determined corruption model (p(r|c)). The determined language model reflects correct usage of the text in the second language, independent of the native or first language (L1) of the author, based on (L2) corpora. The determined corruption model is based on some a priori knowledge about probable corruption paths leading the author to realize some inadequate expression in the second language instead of the correct, intended expression. Different types of corruption paths may be used that include bidirectional translations, false-friends, synonyms, common semantic features, second language internal cognates, preposition alternatives, and first language inserts.

Computer implemented speech processing generates one or more pronunciations of an input word in a first language by a non-native speaker of the first language who is a native speaker of a second language. The input word is converted into one or more pronunciations. Each pronunciation includes one or more phonemes selected from a set of phonemes associated with the second language. Each pronunciation is associated with the input word in an entry in a computer database. Each pronunciation in the database is associated with information identifying a pronunciation language and / or a phoneme language.

A writing advisor program (20) receives a proposed text in an author's second language (L2) and determines at least one candidate replacement word for a selected word based on a determined language model (p(c)) and a determined corruption model (p(r|c)). The determined language model reflects correct usage of the text in the second language, independent of the native or first language (L1) of the author, based on (L2) corpora. The determined corruption model is based on some a priori knowledge about probable corruption paths leading the author to realize some inadequate expression in the second language instead of the correct, intended expression. Different types of corruption paths may be used that include bidirectional translations, false-friends, synonyms, common semantic features, second language internal cognates, preposition alternatives, and first language inserts.

An improved method, apparatus, and computer instructions displaying search results. A query is received in a first language. A snippet in the document containing the word is selected in response to identifying a document in a second language in which the document contains a word matching a query word in the query. This snippet is translated into the first language.