WO2008086889A1 - Dispositif de transcription pour la transcription et le transphrasage automatisés, et procédé correspondant - Google Patents

Dispositif de transcription pour la transcription et le transphrasage automatisés, et procédé correspondant Download PDF

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Publication number
WO2008086889A1
WO2008086889A1 PCT/EP2007/050418 EP2007050418W WO2008086889A1 WO 2008086889 A1 WO2008086889 A1 WO 2008086889A1 EP 2007050418 W EP2007050418 W EP 2007050418W WO 2008086889 A1 WO2008086889 A1 WO 2008086889A1
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WO
WIPO (PCT)
Prior art keywords
transcription
module
elements
generated
parameters
Prior art date
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PCT/EP2007/050418
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German (de)
English (en)
Inventor
Emil Müller
Francois RÜF
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Netbreeze Gmbh
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Publication date
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Priority to PCT/EP2007/050418 priority Critical patent/WO2008086889A1/fr
Publication of WO2008086889A1 publication Critical patent/WO2008086889A1/fr

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Classifications

    • G—PHYSICS
    • G06—COMPUTING; CALCULATING OR COUNTING
    • G06F—ELECTRIC DIGITAL DATA PROCESSING
    • G06F40/00—Handling natural language data
    • G06F40/10—Text processing
    • G06F40/12—Use of codes for handling textual entities
    • G06F40/126—Character encoding
    • G06F40/129—Handling non-Latin characters, e.g. kana-to-kanji conversion
    • G—PHYSICS
    • G06—COMPUTING; CALCULATING OR COUNTING
    • G06F—ELECTRIC DIGITAL DATA PROCESSING
    • G06F40/00—Handling natural language data
    • G06F40/40—Processing or translation of natural language
    • G06F40/42—Data-driven translation
    • G06F40/47—Machine-assisted translation, e.g. using translation memory
    • G—PHYSICS
    • G06—COMPUTING; CALCULATING OR COUNTING
    • G06F—ELECTRIC DIGITAL DATA PROCESSING
    • G06F40/00—Handling natural language data
    • G06F40/40—Processing or translation of natural language
    • G06F40/53—Processing of non-Latin text

Definitions

  • the invention relates to a transcription device and a corresponding method for the computer-aided transcription and / or transphrasing of non-bijectively assignable elements of a first and second group.
  • the invention relates to transcription devices for transcription and / or transphrasing in automated search engines and conversion devices, wherein first search terms and / or first search sentences can be linked to second search terms and / or search sentences by means of a transcription device.
  • Edition sciences the letter-exact transcription of a text, in film analysis the transfer of a film into a written form, or in business the usual name for the typification of the spoken word by a transcriptionist, the company-internal typing service or an external writing office, etc. etc.
  • Font-based transcription may e.g. the representation of certain terms from a font using a phonetic transcription or adapted to the pronunciation rules of a target language.
  • Each transcription system is geared to users who speak a target language.
  • Transcription can serve as a guideline for the reproduction of Cyrillic written names.
  • the same can apply, for example, to Greek names or phrases.
  • a distinction is usually made in the prior art: a) Transcription as a pronunciation-based representation of speech by means of a phonological notation or a phonetic phonetic transcription, or another basic alphabet as a phonetic substitution. Advantages are that, for example, non-native speakers are allowed a reasonably correct pronunciation of the word; b) Transliteration as a font-based, literal translation that can be reversed if necessary a word from one scripture (eg Cyrillic) to another (eg Latin), often with the help of diacritical marks.
  • Tables of transcription and transliteration systems exist for many languages such as Bulgarian, Ardian, Russian, Serbian, Ukrainian, Belorussian. In Japanese, the transcription of the Japanese into the Latin script P - ⁇ ⁇ ⁇ R ⁇ maji Roman characters). There are several transcription systems. Two well-known and well-recognized are the Hebrews system (in German: Hepburn system) and the Kunreishiki system (in German: Kunrei system). The former was distributed by the American missionary Hepburn; The latter was devised by the then Japanese government and follows the systematics of the Cana table.
  • the rules for transcription from one element to another are usually not unique, but can only be found in the context of language usage. This has made automation of transcription difficult or impossible in most cases. Encoding was difficult to create because languages can typically be very large. At the same time, the codings (one to one assignment of the elements in a lookup table) had to be kept up-to-date permanently and at great expense.
  • the available search engines of the state of the art can roughly be divided into four categories: robots / crawlers, metacrawlers, search catalogs with search options and catalogs or link collections.
  • robots / crawlers ie search robots or crawlers
  • crawler a process that moves through the network, eg the Internet, from network node to network node or from web site Web site, sending the content of every Web document it finds back to its host.
  • the host computer indexes the web documents sent by the crawler and stores the information in a database. Every search
  • the prior art crawlers usually consider every piece of information to be relevant, so any web documents found anywhere are indexed by the host machine. Examples of such robots / crawlers include i.a. Google TM, Altavista TM and Hotbot TM.
  • the so-called metacrawlers differ from the robots / crawlers in being able to search using a single search facility, the answer being additionally generated by a variety of other systems of the network.
  • the Metacrawler thus serves as a front-end to a variety of other systems.
  • the response to a search request from a Metacrawler is typically limited by the number of its other systems. Examples of Metacrawlers include u.a. MetaCrawler TM, LawCrawler TM and LawRunner TM.
  • catalogs with or without search options are characterized by a special selection of links, which are structured and / or organized by hand and stored in a corresponding database.
  • the manually stored information is searched by the system for the desired search term in a search request.
  • the user In the case of a catalog without search options, the user must search for the desired information himself from the list of stored links, for example by manually clicking through the list or scrolling. In the latter case, the user himself decides which information from the list is relevant to him and which is less relevant to him.
  • Catalogs are naturally limited by the volume of performance and the priorities of the editor (s). Examples of such catalogs include Yahoo! TM and FindLaw TM. Catalogs fall under the category of portals and / or vortals.
  • Portals manually attempt to gain an overview of selected computer sites by "surfing" editors through the Internet, ie having the content judged, and compiling relevant data sources or sites.
  • the editors are able to search, read and evaluate an average of about 10-25 sites per day, of which 25 usually only just 1 or 2 sites contain documents with the desired quality or information. It is clear that portals are very inefficient in terms of time, cost and effort for the provider if the goal of a portal is to provide a comprehensive indexing of all available data on a topic on the Internet.
  • Transcription device and a corresponding method for computer-aided transcription and / or transphrasing non-bijectively assignable elements of a first and second group which does not have the above-mentioned disadvantages of the prior art.
  • the invention is intended to make it possible to realize a transcription device which, without any further action, adapts itself dynamically to a new word usage, in particular newly appearing names, and automatically proposes the correct transcription.
  • the transcription device should do without elaborate coding of words, but be producible with minimal effort.
  • Transcriptional parameters are encoded according to their transcription site such that by means of a filter module based on the encoding of the first transcription and the corresponding transcription sites, a plurality of transcription variations are generated by variation with the combinations of indexed fill elements, each
  • Transskritpionsvariation is associated with an incremental stack, that for each transcription variation generates a corresponding search element and accessed by transcription device via a network on decentralized databases, the corresponding incremental stack is incremented by trigger module each time triggering a search element that generated based on the accumulated incremental stack probability parameter and by means of comparison module based on the probability parameters, a specific transcription is uniquely selected.
  • the filling elements may be e.g. include phonetically non-relevant phonograms in the target language.
  • the filling elements may be e.g. include meaningful, affirmative or attenuating filler words.
  • the invention has i.a.
  • the network may e.g. include the international backbone IP network.
  • transcriptions which can be processed only with great effort and time e.g. by means of lookup table, i. a one-to-one encoding of the elements to be assigned can be realized are directly detectable. New names and terms are also detected and used dynamically correctly by the transcription device according to the invention. This was not possible with any prior art.
  • the automated transcription device comprises a control and monitoring module for controlling Web engines and / or conversion devices, wherein inteis the transcription device additionally source databases are accessible.
  • This embodiment variant has the advantage, inter alia, that these systems can automatically access a previously definable entirety of source databases from a network, in particular from the Internet (eg web sites, chat rooms, e-mail forums, etc.), which also have a previously definable Search criteria are scanned, regardless of language, font and spelling.
  • the system not only enables the generation of a "hit list" of web sites with corresponding content found on the Internet, but the system allows the aforementioned screening of predefinable sources and their systematic and thus quantitatively relevant evaluation, according to the desired and defined content criteria independently of speech, writing and writing criteria.
  • the system can actually "monitor" the defined sources for the first time in the art independently and over a longer period of time, even if the language and writing usage change, such as when introducing new spellings such as the Duden or new appearing name.
  • the first group of the second group is assigned by means of the transcription device, wherein the assignment of the first group in the second group is not surjective, while by means of a coding module of the transcription device, the second group of the first group is assigned, the assignment of the second Group is surjective to the first group.
  • the second group may be based, for example, on the Cyrillic alphabet. This has the advantage that transcriptions in languages such as Bulgarian, Ardian, Russian, Serbian, Ukrainian, Belorussian can be easily grasped. Another advantage is that web engines based on the inventive transcription device Web Sides, especially New Groups, etc. can easily detect.
  • the filling elements and / or transcription variations may include not only Cyrillic but also, for example, Hebrew letters. This has the advantage that transcription terms are captured in the appropriate languages such as old / new Hebrew.
  • the scorecard with the found records and / or references to the found records is stored in a content module of a central unit accessible to a user.
  • This variant has u.a. the advantage that the system e.g. can be used as a monitoring, monitoring and / or warning system for the user.
  • a user profile is created on the basis of user information, wherein user-specific optimized data is generated based on the data records stored in the content module, found and / or references to data records found by means of a repackaging module taking into account the data of the user profile, which user-specifically optimized data the user stored in the content module of the central unit provides.
  • the user can be stored as a variant variant different user profiles for different communication devices of the user assigned. Further, e.g. Also, data on user behavior is automatically recorded by the central unit and stored in association with the user profile.
  • This variant has u.a. the advantage that different access options of the user can be considered user-specific and the system can be optimized user-specific.
  • Transcription device for carrying out this method relates. Furthermore, it is not limited to the said triggering device and a corresponding method, but also relates to a computer program product for implementing the method according to the invention.
  • a computer program product for implementing the method according to the invention.
  • FIG. 1 schematically shows the mode of operation of a transcription device 10 according to the invention for computer-aided transcription and / or transphrasing of non-bijectively assignable elements of a first 20 and second 50 groups by means of the automated transcription device 10.
  • FIG. 2 likewise schematically illustrates the mode of operation of a transcription device 10 according to the invention for computer-assisted transcription and / or transphrasing of non-bijectively assignable elements of a first 20 and second 50 groups by means of the automated transcription device 10. The method is shown schematically in more detail.
  • FIG. 3 likewise illustrates a schematic representation of a
  • Figure 1 schematically illustrates an architecture that may be used to implement the invention.
  • FIG. 1 for computer-aided transcription and / or transphrasing of non-bijectively assignable elements of a first 20 and second 50 groups by automated transcription device 10 with a Monte Carlo module 112 of the transcription device 10, different combinations of indexed fill elements are generated and stored in a database 115 based on the stored index parameter stored.
  • the filling elements may include, for example, phonetically irrelevant phonograms. However, the filling elements may also include, for example, meaningful, affirmative or attenuating filling words.
  • the Monte Carlo module 112 can probabilistically generate transcriptions (eg purely randomly or according to a probability distribution), which are then used for further processing / analysis.
  • Transcription device or the corresponding method is based as a whole on the probability distribution of all possible generated transcriptions and triggers accordingly.
  • the transcriptions themselves become i.N. concerning the filling elements is not probabilistically generated, since, as stated, the insertion of the filling elements can follow predefined rules, but only with respect to the application of a filling rule or the non-application.
  • a first transcription 40 is generated for a selected element of the first group 20, wherein the respective transcription parameters used are encoded according to their transcription site.
  • a filter module 113 based on the coding of the first transcription 40 and the corresponding transcription sites, a plurality of transcription variations are generated by variation with the combinations of indexed fill elements, each transskritization variation being associated with an increment stack 116.
  • a corresponding search element is generated and by means of transcription device 10 is accessed via a network 70 on decentralized databases 71, ..., 74, wherein the corresponding incrementation stack 117 by means of trigger module 111 on each triggering of a search element 1211, ..., 1212 is incremented.
  • the network 70 may include, for example, the international backbone IP network.
  • the network 70 can also include, for example, communication networks, such as a GSM or UMTS network, or a satellite-based mobile radio network, and / or one or more fixed networks, for example the public switched telephone network, the worldwide Internet or a suitable LAN (Local Area Network) or WAN (Wide Area Network). In particular, it also includes ISDN and XDSL connections.
  • a transcription device 10 thus accesses network nodes connected to source databases 71, ..., 74 via the network 70, and data of the source databases 71, ..., 74 are selected or triggered based on the transscripts variations.
  • the transcription device 10 is bidirectionally connected to the network nodes or source databases 71,..., 74 via the communication network 70.
  • the data to be triggered based on the search terms can, as shown, be stored at different locations in different networks or locally accessible to the transcription device 10.
  • the network nodes with the databases 71,..., 74 may include WWW (Hyper Text Transfer Protocol / WAP: Wireless Application Protocol etc.) servers, chat servers, email servers (MIME), news servers, E-journal servers, group servers or any other file servers, such as FTP (File Transfer Protocol) servers, ASD (Active Server Pages) based servers, or SQL-based servers (SQL: Structured Query Language), etc. include.
  • elements of the first group 20 can be assigned to elements of the second group 50, wherein the assignment of the first group 20 into the second group 50 is not surjective, while the second group is assigned to the first group by means of a coding module 11 of the transcription device , where the assignment of the second group to the first group is surjective.
  • the elements of the first group 20 and / or the second group 50 may include multimedia data such as digital data such as text, graphics, images, maps, animations, moving images, video, quicktime, sound recordings, programs (software), program accompanying data and hyperlinks or References to multimedia data. These include, for example, MPx (MP3) or MPEGx (MPEG4 or 7) standards, as defined by the Moving Picture Experts Group.
  • elements of the first 20 and / or second 50 groups may include data in HTML (Hyper Text Markup Language), HDML (Handheld Device Markup Language), WMD (Wireless Markup Language), VRML (Virtual Reality Modeling Language), or XML (Extensible Markup Language) format include.
  • the second group may for example be based on Cyrillic and / or Hebrew alphabet.
  • the filling elements and / or transcription variations may include, for example, Cyrillic or Hebrew letters.
  • the abovementioned standards (ALA-LC, BGN / PCGN, etc.) can be reversed by means of the transcription device 10 according to the invention, and finally the transliterated names can be reversed by means of databases 71,... 74, in particular Google, for example. checked for their correctness.
  • the transcription device may use one of the standard methods mentioned above.
  • the transcription device 10 makes a transliterating proposal based on the method according to the invention by means of the databases 71, ..., 74, this is certainly the right one.
  • the transcription device can use, for example, a combination of the two standards ALA-LC and BGN / PCGN. It is peculiar to both norms that the corresponding illustrations of the Cyrillic narrative are not injective in Latin. This means that two different Cyrillic characters can be mapped to the same Latin character. For the reversal of the figure, this means that a Latin character can produce two different cyrillic variants. Also exist in the Russian silent character (similar to the N r T in error), the cause consonants are pronounced softer or harder. The two silent characters V, the softer the previous constants, and "V, which makes the preceding consonant harder.
  • the text written in Latin can be translated character by character into Cyrillic characters. In doing so, a copy of the result is created for each possible branch. At the end of this process there is a notation for every theoretically possible variant due to the phonetic rules. An example can be found in FIG. 3.
  • the procedure for Cyrillic expressions is a procedure for a wider selection of BGN / PCGN procedures (currently 29 different languages are covered by BGN / PCGN).
  • the BGN / PCGN procedures were developed by the United States Board of Geographical Names and the Permanent Commitee on Geographical Names for British Official Use.
  • the procedures for supporting transliterations in Cyrillic letters, especially Russian expressions, were recorded in 1944 by BGN and in 1947 by PCGN.
  • the transliteration is based solely on the use of the capital letters and punctuation, which are on the English version of standard keyboards and keyboards.
  • BGN / PCGB does not require any special characters, although the use of the character ( ⁇ ) is permitted to avoid ambiguity.
  • BGN / PCGN Many publications use a simplified form of BGN / PCGN, for example, to translate English into Russian terms by typically converting e to yo, simplifying -y and -yy endings to -y, and avoiding apostrophes for t and b , Edward Allworth, for example, uses a BGN / PCGN based methodology in his book "Nationalities of the Soviet East - Publications and Writing Systems.” It always transfers e and e to e and e respectively and substitutes an i for y from M, K> and fi, making the procedure similar to a version of the ALA-LC system without diacritics.
  • the following table illustrates the BGN / PCGN method with example:
  • Taivi ⁇ oB Tambov
  • flyflMHKa Dudinka ⁇ ( ⁇ )
  • ⁇ ypMaH ⁇ B Furmanov
  • the ALA-LC comprises Slavonic alphabet tables and is a set of standards for transliterating text and terms in a variety of spellings and is used primarily in North American libraries and publications. The latest version was published by the American Library Association & Library of Congress in 1997. The non-ambiguous version of the method requires diacritical and connection characters between the individual letters, which are often omitted in practice. ALA-LC also publishes transliteration tables for a wide variety of languages.
  • Taivi ⁇ oB Tambov
  • the automated transcription device 10 may include a control and monitoring module for controlling web engines and / or conversion devices, wherein by means of the transcription device 10 in addition source databases 71, ..., 74 become accessible.
  • additionally accessible is meant that data or databases with data in other types of writing or writing can be captured by the web engines and interpreted uniformly.
  • the selected transcriptions in a content module of the transcription device 10 can be stored accessible to a user. In order to be able to access the content module, it can be useful (for example, to offset the claimed service) to identify a specific user from the transcription device 10 by means of a user database. For example, personal identification numbers (PIN) and / or so-called smart cards can be used for identification.
  • PIN personal identification numbers
  • smart cards can be used for identification.
  • Smart cards normally require a card reader in the communication device. In both cases, the name or other identification of the user as well as the PIN is transmitted to the transcription device 10 or a trusted remote server. An identification module or authentication module decrypts (if necessary) and checks the PIN via the user database. Credit cards can also be used as a variant for the identification of the user. If the user uses his credit card, he can also enter his PIN. Typically, the magnetic stripe of the credit card contains the Account number and the encrypted PIN of the authorized holder, ie in this case the user. The decryption can be done directly in the card reader itself, as is common in the art. Smart cards have the advantage that they allow greater security against fraud by an additional encryption of the PIN.
  • This encryption can be done either by a dynamic number key, which contains eg time, day or month or another algorithm.
  • the decryption and identification does not happen in the device itself, but externally via the identification module.
  • Another option is a smart card inserted directly into the user's communication device.
  • the chip card can be, for example, SIM cards (Subscriber Identification Module) or smart cards, with the chip cards each being assigned a telephone number.
  • the assignment can be made, for example via an HLR (Home Location Register) by the IRLS IMSI (International Mobile Subscriber Identification) of a phone number, for example, a MSISDN (Mobile Subscriber ISDN) is stored. This assignment then enables a unique identification of the user.
  • the user to start the transcription device 10 transmit a transcription request for the corresponding query from a communication device via the network 70 to the transcription device 10 via a front-end.
  • the transcription request data can be input via input elements of the communication device.
  • the input elements may include, for example, keyboards, graphical input means (mouse, trackball, eye tracker with Virtual Retinal Display (VRD) etc.), but also IVR (Interactive Voice Response) etc.
  • the user has the option of determining at least part of the transcription request data himself. This can happen, for example, when the user is requested by the communication device to fill out an appropriate front-end query via an interface.
  • the front-end query may in particular include additional authentication and / or fees for the query.
  • the transcription data request data can be checked and, if they satisfy determinable criteria, the transcription is carried out.
  • a user profile is created based on user information, for example, based on the stored in the content module transcriptions and / or references to performed transcriptions by means of a repackaging module, taking into account the data of the user profile user-optimized data are generated.
  • the user-specific optimized data can then be made available to the user in the content module of the transcription device 10, for example. It may be advantageous for a user to be assigned different user profiles allocated to different communication devices of this user.
  • data on user behavior can also be automatically acquired by the transcription device 10 and stored in association with the user profile.

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Abstract

L'invention concerne un dispositif de transcription. Elle concerne aussi un procédé correspondant pour la transcription et/ou le transphrasage assistés par ordinateur d'éléments - pouvant être associés de manière bijective - d'un premier (20) et d'un deuxième groupe (50) au moyen d'un dispositif de transcription automatisé (10). Selon ce procédé, au moyen d'un module de filtrage (113) et sur la base d'un codage d'une première transcription (40), on génère une pluralité de variantes de transcription en faisant varier des éléments de remplissage indexés, sachant que chaque variante de transcription est associée à une pile d'incrémentation (116). Pour chaque variante de transcription, on génère un élément de recherche correspondant et, au moyen du dispositif de transcription (10), on accède par l'intermédiaire d'un réseau (70) à des bases de données (71,...,74) disposées de manière décentralisée, sachant que la pile d'incrémentation correspondante (117) est, au moyen d'un module de déclenchement (111), incrémentée en conséquence à chaque déclenchement d'un élément de recherche (1211,...,1212). Sur la base des piles d'incrémentation cumulées (117), on génère des paramètres de vraisemblance et, au moyen d'un module de comparaison (114), on sélectionne de manière univoque une transcription donnée sur la base des paramètres de vraisemblance.
PCT/EP2007/050418 2007-01-16 2007-01-16 Dispositif de transcription pour la transcription et le transphrasage automatisés, et procédé correspondant WO2008086889A1 (fr)

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Citations (1)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
WO2003065248A2 (fr) * 2002-02-01 2003-08-07 International Business Machines Corporation Extraction de documents correspondant au moyen de demandes formulees dans toute langue nationale

Patent Citations (1)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
WO2003065248A2 (fr) * 2002-02-01 2003-08-07 International Business Machines Corporation Extraction de documents correspondant au moyen de demandes formulees dans toute langue nationale

Non-Patent Citations (1)

* Cited by examiner, † Cited by third party
Title
GREGORY GREFENSTETTE, YAN QU AND DAVID A. EVANS: "Mining the Web to Create a Language Model for Mapping between English names and phrases and Japanese", PROCEEDINGS OF THE IEEE/WIC/ACM INTERNATIONAL CONFERENCE ON WEB INTELLIGENCE (WI04)), 20 September 2004 (2004-09-20) - 24 September 2004 (2004-09-24), Beijing, China, XP002454892, Retrieved from the Internet <URL:http://ieeexplore.ieee.org/iel5/9689/30573/01410791.pdf?arnumber=1410791> [retrieved on 20071015] *

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