WO2000030070A2 - Method and apparatus for improved part-of-speech tagging - Google Patents

Method and apparatus for improved part-of-speech tagging Download PDF

Info

Publication number
WO2000030070A2
WO2000030070A2 PCT/US1999/027210 US9927210W WO0030070A2 WO 2000030070 A2 WO2000030070 A2 WO 2000030070A2 US 9927210 W US9927210 W US 9927210W WO 0030070 A2 WO0030070 A2 WO 0030070A2
Authority
WO
WIPO (PCT)
Prior art keywords
speech
part
set
taggers
specialized
Prior art date
Application number
PCT/US1999/027210
Other languages
French (fr)
Other versions
WO2000030070A3 (en
Inventor
Alwin B. Carus
Original Assignee
Lernout & Hauspie Speech Products N.V.
Priority date (The priority date is an assumption and is not a legal conclusion. Google has not performed a legal analysis and makes no representation as to the accuracy of the date listed.)
Filing date
Publication date
Priority to US10877898P priority Critical
Priority to US60/108,778 priority
Application filed by Lernout & Hauspie Speech Products N.V. filed Critical Lernout & Hauspie Speech Products N.V.
Publication of WO2000030070A2 publication Critical patent/WO2000030070A2/en
Publication of WO2000030070A3 publication Critical patent/WO2000030070A3/en

Links

Classifications

    • GPHYSICS
    • G06COMPUTING; CALCULATING; COUNTING
    • G06FELECTRIC DIGITAL DATA PROCESSING
    • G06F17/00Digital computing or data processing equipment or methods, specially adapted for specific functions
    • G06F17/20Handling natural language data
    • G06F17/27Automatic analysis, e.g. parsing
    • G06F17/2705Parsing
    • G06F17/271Syntactic parsing, e.g. based on context-free grammar [CFG], unification grammars

Abstract

A tagging device for identifying parts-of-speech of text includes a first part-of-speech tagger that provides, at a first output, a part-of-speech tag for each term in the text and a set of specialized part-of-speech taggers, having an output coupled to a device output and also having an input. The set of specialized part-of-speech taggers provide a set of candidate part-of-speech tags for each term provided at the input to the set of specialized part-of-speech taggers. An exception handler, coupled to the first output provides, in response to each term in the text, a part-of-speech tag from the first output to the device output, unless the term in the text is included in an exception list, in which case the term is provided to the input of the set of specialized part-of-speech taggers. A voting procedure may be used to select a part-of-speech tag from the set of candidate part-of-speech tags produced by the specialised part-of-speech-taggers for terms on the exception list.

Description

Method and Apparatus for Improved Part-of-Speech Tagging

Technical Field The present invention relates generally to part-of-speech tagging of text and more particularly to the contextual part-of-speech disambiguation of words and phrases in text.

Background Art The identification of the part-of-speech of words and phrases in text is useful in many different areas such as word and text processing (e.g. proofreading), information retrieval and natural-language database query, information and fact extractions, natural language understanding and machine translation. Many different methods exist by which the part-of-speech may be identified and tagged such as the Markov model, decision tree, connectionist, transformational, nearest neighbor, on-line learning, and maximum entropy. These methods are well described in the art. See, for example Weischedel, R., Meteer, M., Scwartz, R., Ramshaw, L., and Palmucci, J., "Coping with Ambiguity and Unknown Words Through Probabilistic Models", Computational Linguistics (1993); Black, E., Jelinek, F., Lafferty, J., Mercer, R., and Roukos, S., "Decision Tree Models Applied to the Labeling of Text with Parts-of -Speech", Darpa Workshop on Speech and Natural Language (Harriman, N.Y., 1992); Schmid, H., "Part of Speech Tagging with Neutral Networks," Proceedings of 15th International Conference on Computational Linguistics (COLING) (Yokohama, Japan 1994); Brill, E, "Transformation-Based Error-Driven Learning and Natural Language Processing: A Case Study in Part of Speech Tagging", Computational Linguistics 21(4) , pp. 543-565, Dec. 1995; Daelemans, W., Zavrel, P., Berck, P., Gillis, S., "MBT: A Memory-Based Part of Speech Tagger-Generator," Proceedings of the Fourth Workshop on Very Large Corpora, Copenhagen, Denmark, pp.14-27, (1996); Ratnaparkhi, A., "A Maximum Entropy Part-of-Speech Tagger," Proceedings of the First Empirical Methods in Natural Language Processing Conference, Mav 17-18 (University of Pennsylvania 1996). The foregoing references are herein incorporated by reference.

Even the most accurate part-of-speech taggers in the prior art result in some residual error. Improved performance and accuracy may be obtained by producing larger and slower part-of-speech taggers. Another method developed for improving the accuracy of part-of-speech taggers is described in Brill, E., Wu, J., "Classifier Combination for Improved Lexical Disambiguation," Proceedings of the 19th International Conference on Computational Linguistics and Association for Computational Linguistics (COLING-ACL)(Montreal, Canada, 1998) and van Halteren, H., Zavrel, J., Daelemans, W., "Improving Data Driven Wordclass Tagging by System Combination," Proceedings of 19th International Conference on Computational Linguistics and Association for Computational Lιnguιstιcs(COLTNG- ACL)(Montreal, Canada 1998), pp491-497. The foregoing references are herein incorporated by reference. The method described in the foregoing references involves processing the entire text with four different part-of-speech taggers. A part-of-speech tag is then selected from the results of the four part-of-speech taggers using a selection procedure. Although such a method improves accuracy, the improvement comes at a cost of computational speed and complexity.

Summary of the Invention In accordance with one aspect of the invention, a tagging device for identifying parts-of-speech of terms in a text comprises a first part-of-speech tagger, a set of specialized part-of-speech-taggers and an exception handler. As used in this description and the following claims, the word "set" refers to a set that includes at least one member. The first part-of-speech tagger provides, at a first output, a part-of-speech tag for each term in the text. As used in this description and the following claims, the word "term" refers to a word and optionally to a word or a phrase. In other words, the tagging device is operative on each word in the text, and optionally the tagger may be operative as well on phrases in the text. The set of specialized part-of-speech taggers has an output coupled to a device output and also has an input and provides a set of candidate part-of-speech tags for each term provided at the input to the set of specialized part-of-speech taggers. The exception handler, coupled to the first output, provides, in response to each term in the text, a part-of-speech tag from the first output to the device output, unless the term in the text is included in an exception list. If the term in the text is included in the exception list, the term is provided to the input of the set of specialized part-of-speech taggers.

In a further embodiment, the set of specialized part of speech taggers includes a plurality of specialized part-of-speech taggers and the tagging device further includes a selector, coupled to the output of the set of specialized part-of- speech taggers. The selector also has an output coupled to the device output. The selector selects a part-of-speech tag from the set of candidate part-of-speech tags using a voting procedure and provides the selected part-of-speech tag at the device output. In another further embodiment, at least one member of the set of specialized part-of-speech taggers is optimized for processing terms on the exception list. The exception list may include terms which account for a predetermined percentage of errors produced by the first part-of-speech tagger. In yet another embodiment, the voting procedure generates a score for each unique candidate part-of-speech tag from the set of candidate part-of- speech tags based on predetermined characteristics of each specialized part-of- speech tagger in the set of specialized part-of-speech taggers. The voting procedure may select the part-of-speech tag with the highest score. The tagging device may further include a tokenizer, coupled to the first part-of-speech tagger, for parsing the text into a set of word tokens.

In an alternative embodiment, a method for identifying parts-of-speech of terms in a text comprises: (a) using a first part-of-speech tagger to determine the part-of-speech of each term in the text; (b) identifying each term in the text which is included in an exception list; (c) providing the part-of-speech tag from step (a) as a device output for each term not included in the exception list; and (d) using a set of specialized part-of-speech taggers to determine a set of candidate part-of- speech tags for each term included in the exception list. In a further embodiment, the method, wherein the set of specialized part-of-speech taggers includes a plurality of taggers, further includes (e) selecting a part-of-speech tag from the set of candidate part-of-speech tags using a voting procedure and (f) providing the part of speech tag selected in step (e) as the device output for each term included in the exception list

In a further embodiment, at least one member of the set of specialized part-of-speech taggers is optimized for processing terms on the exception list The exception list may include terms which account for a predetermined percentage of errors produced by step (a) In the above embodiments, the vohng procedure generates a score for each unique candidate part-of-speech tag from the set of candidate part-of-speech tags, the score being based upon predetermined characteristics of each specialized part-of-speech tagger in the set of specialized part-of-speech taggers The voting procedure may select the candidate part-of-speech tag with the highest score The method may further include, before step (a), parsing the text into word tokens

In another alternative embodiment, a digital storage medium encoded with instructions which, when loaded into a computer, may establish any of the devices previously discussed

Brief Description of the Drawings

The present invention will be more readily understood by reference to the following detailed description taken with the accompanying drawings, in which

Fig 1 is a block diagram of a tagging device in accordance with an embodiment of the invention Fig 2 is a block diagram showing the voting procedure utilized by the tagging device of Fig 1 in accordance with a preferred embodiment of the invention

Fig 3 is a block diagram showing the flow of control for a method of part- of-speech tagging in accordance with an embodiment of the invention Detailed Description of Specific Embodiments Figure 1 shows a block diagram of a tagging device in accordance with an embodiment of the invention. Text is input at a text input 10 and then the text is parsed into word tokens using a tokenizer 11. The tokenizer 11 may be one of general use in the art (for example, U.S. Patent No. 5,721,939, "Method and Apparatus for Tokerύzing Text", or U.S. Patent No. 4,991,094, "Method for Language-Independent Text Tokenization using a Character Categorization", herein incorporated by reference). The tokenized text is then placed into a text buffer in order to be processed by the tagging device. A first part of speech tagger 12 processes the tokenized text. The first part-of-speech tagger 12 may be one of general use in the art such as Markov model, decision tree, connectionist, transformational, nearest neighbor, on-line learning, or maximum entropy. Preferably, the first part-of-speech tagger 12 is a fast and accurate part-of-speech tagger. In one embodiment of the invention, the first part-of-speech tagger 12 is a Brill transformational tagger implemented by an Abney-like finite-state automaton (FSA) (See Brill, E., "Transformation-Based Error-Driven Learning and Natural Language Processing: A Case Study in Part of Speech Tagging," Computational Linguistics 21 (4), Dec. 1995, pp. 543-565, herein incorporated by reference). Accordingly, the first part of speech tagger 12 is produced by generating Brill part-of-speech tagging transformational rules against a first part- of-speech tagged corpus of text.

An exception handler 13 is coupled to the first part-of-speech tagger 12. If the term being processed is not found on an exception list, the part-of-speech tag identified by the first part of speech tagger will be the output 19 of the tagging device. When the exception handler 13 encounters a term found on the exception list, the term is routed to a set of specialized part-of- speech taggers 14- 17 coupled to the exception handler 13 for further processing. The set of specialized part-of-speech taggers may include n members, where n can be a number greater than or equal to one. In the embodiment shown in Figure 1, the set of specialized part-of-speech taggers includes four specialized part-of-speech taggers 14-17. Preferably, the exception list includes terms which are known to have inaccurate tagging results using the first part-of-speech tagger 12. The terms included in the exception list are identified by running the first part-of-speech tagger 12 against a second part-of-speech tagged corpus of text to identify the residual error of the first part-of-speech tagger 12. The frequency distribution of the part-of-speech tagging errors by the term associated with the errors is generated in order to identify the terms which account for the most frequently occurring errors produced by the first part-of-speech tagger 12. Terms which account for a predetermined percentage of the errors produced by the first part- of-speech tagger 12 are included in the exception list. In one embodiment, the predetermined percentage is 90%.

Each specialized part-of-speech tagger is generated using the exception list described above. Each of the specialized part-of-speech taggers 14-17 may be one generally known in the art. As discussed above, some examples of part-of - speech taggers are the Markov model, decision tree, connectionist, transformational, nearest neighbor, on-line learning, and maximum entropy. The specialized part-of-speech taggers are produced by the methods appropriate to each style of tagger, however, each specialized part-of-speech tagger is trained specifically on the terms included in the exception list. Preferably, each specialized part-of-speech tagger is of a different type. In one embodiment, the specialized part-of-speech taggers 14-17 are trigram, Brill transformational, memory-based learning, and maximum entropy part-of-speech taggers. If there is only one specialized part-of-speech tagger in the set of specialized part-of-speech taggers, the output of the specialized part-of-speech tagger is the device output 19 for each term in the text that is included in the exception list. As discussed above, for each term not found on the exception list, the device output 19 will be the output of the first part-of-speech tagger 12.

If the set of part-of-speech taggers consists of a plurality of specialized part-of-speech taggers, as shown in Figure 1, each specialized part-of-speech tagger 14-17 will produce a candidate part-of-speech tag for the term being processed by the set of specialized part-of-speech taggers. Each candidate part- of-speech tag produced by the set of specialized part of speech taggers is provided to a selector 18. The selector 18 uses a voting procedure to select one of the candidate part-of-speech tags. Figure 2 is a block diagram showing the voting procedure according to an embodiment of the invention. At block 20, each specialized part-of-speech tagger processes the term and identifies a candidate part-of-speech tag. At block 21, the voting procedure creates a list of unique candidate part-of-speech tags identified by the specialized part-of-speech taggers. A score is then calculated for each unique candidate part-of-speech tag at block 22. In one embodiment, the voting procedure uses pre-computed values of precision and recall for each specialized part-of-speech tagger to calculate a score (block 22) for each unique candidate part-of-speech tag produced by the set of specialized part-of-speech taggers. Precision is defined as the percentage of tokens tagged X by the part-of-speech tagger that are also tagged X in the training corpus. Recall is defined as the percentage of tokens tagged X in a training corpus that are also tagged X by the part-of-speech tagger. For example, the word "that" has several possible parts of speech, such as coordinating conjunction (CS), determiner (DT), qualifier (QL) or WH-pronoun (WPR). If a specialized part-of-speech tagger produced the tag DT in fifty instances of the word "that" of which forty-five as identified by the training corpus are correct, then the precision is .90 (=45/50). If there were fifty instances of "that" tagged DT in the training corpus and the specialized tagger tagged forty-eight of them as DT, then the recall is .96 (=48/50).

As mentioned above, the values of precision and recall may be used to determine the score for each unique candidate part-of-speech tag at block 22. The score for a candidate part-of-speech tag may be calculated by adding the precision of each specialized part-of-speech tagger which produced a particular candidate part-of-speech tag to an amount equal to (1-recall) of each specialized part-of-speech tagger which produced the particular candidate part-of-speech tag. The candidate part-of-speech tag with the highest accumulated score is selected at block 23 as the part-of-speech tag for the term being processed by the set of specialized part-of-speech taggers.

Table 1 shows example results for the word "that" using a set of specialized part-of-speech taggers consisting of trigram, Brill transformational, memory-based learning, and maximum entropy part-of-speech taggers. The candidate part-of-speech tags are defined as determiner (DT) and coordinating conjunction(CS).

Figure imgf000010_0001

Table 1. Example results from specialized taggers for the term "that" in a given instance

The calculation of the scores for the candidate part-of-speech tags "DT" and "CS" would be as follows:

ScoreDT=.83 + .88 + (1-.93) + (1-.89) = 1.89 Score^ =.87 + .91 + (1-.87) + (1-.93) = 1.98 In this example, the candidate part-of-speech tag CS has the higher score and would be selected as the part-of-speech tag for the word "that".

Returning to Figure 1, the output 19 of the tagging device will be the output of selector 18 for each term in the text that is found on the exception list. Otherwise, the output 19 of the tagging device will be the output of the first part- of-speech tagger 12. The use of the specialized part-of-speech taggers 14-17 in combination with the first part-of-speech tagger 12 improves the performance and accuracy of the first part-of-speech tagger 12. This is accomplished by training each specialized part of speech tagger 14-17 to improve the accuracy of those terms which produce the largest error rates for the first part-of-speech tagger 12.

Figure 3 illustrates the flow of control for a method of identifying the parts-of-speech of terms in a text in accordance with an embodiment of the invention. The text input at block 30 is parsed into word tokens at block 31. The tokenized text is then placed in a text buffer at block 32 and processed at block 33 by a first part-of-speech tagger. At block 34, if the term being processed is not found on an exception list, the output at block 37 will be the part-of-speech tag produced by the first part-of-speech tagger. The exception list is described above with respect to Figure 1. If the term being processed is found on the exception list, the term will be processed by a set specialized part-of-speech taggers at block 35. The set of specialized part-of-speech taggers produce a set of candidate part-of-speech tags. If the set of specialized part of speech taggers includes only one specialized part-of-speech tagger, the output at block 37 will be the output of the specialized part-of-speech tagger as determined at block 35. If the set of specialized part-of-speech taggers includes a plurality of specialized part-of-speech taggers, a voting procedure is used at block 36 to select a part-of- speech tag from the set of candidate part-of-speech tags. The voting procedure for an embodiment of the invention is described above with respect to Figure 2. At block 37 the output for a term in the text that is found on the exception list will be the part-of-speech tag selected in step 36.

Although various exemplary embodiments of the invention have been disclosed, it should be apparent to those skilled in the art that various changes and modifications can be made which will achieve some of the advantages of the invention without departing from the true scope of the invention. These and other obvious modifications are intended to be covered by the appended claims.

Claims

What is claimed is:
1. A tagging device for identifying parts-of-speech of text, the device comprising: a first part-of-speech tagger that provides, at a first output, a part- of-speech tag for each term in the text; a set of specialized part-of-speech-taggers, having an output coupled to a device output and also having an input, the set of specialized part- of-speech taggers providing a set of candidate part-of-speech tags for each term provided at the input to the set of specialized part-of-speech taggers; and an exception handler, coupled to the first output, to provide, in response to each term in the text, a part-of-speech tag from the first output to the device output, unless the term in the text is included in an exception list, in which case the term is provided to the input of the set of specialized part-of - speech taggers.
2. A tagging device according to claim 1, wherein the set of specialized part of speech taggers includes a plurality of specialized part-of- speech taggers, the device further comprising: a selector, coupled to the output of the set of specialized part-of- speech taggers, the selector having an output coupled to the device output, for selecting a part-of-speech tag from the set of candidate part-of-speech tags using a voting procedure and providing the selected part-of-speech tag at the device output.
3. A tagging device according to claim 1, wherein at least one member of the set of specialized part-of-speech taggers is optimized for processing terms on the exception list.
4. A tagging device according to claim 1, wherein the exception list includes terms which account for a predetermined percentage of errors produced by the first part-of-speech tagger.
5 A tagging device according to claim 2, wherein the voting procedure generates a score for each unique part-of-speech tag rrom the set of candidate part-of-speech tags based on predetermined characteristics of each specialized part-of-speech tagger in the set of specialized part-of-speech taggers
6 A tagging device according to claim 5, wherein the voting procedure selects the candidate part-of-speech tag with the highest score
7 A tagging device according to claim 1, further including a tokenizer, coupled to the first part-of-speech tagger, for parsing the text into a set of word tokens
8 A method for identifying parts-of-speech ot text, the method comprising, (a) using a first part-of-speech tagger, to determine the part-of- speech of each term in the text,
(b) identifying each term in the text which is included in an exception list,
(c)provιdιng the part-of-speech tag from step (a) as a device output for each term not included in the exception list, and
(d) using a set of specialized part-of-speech taggers to determine a set of candidate part-of-speech tags for each term in the text that is included in the exception list
9 A method according to claim 8, wherein the set of specialized part- of-speech taggers includes a plurality of taggers, the method further including
(e) using a vohng procedure to select a part-of-speech tag from the set of candidate part-of-speech tags, and
(f) providing the part of speech tag selected in step (e) as the device output for each term in the text that is included in the exception list
10. A method according to claim 8, wherein at least one member of the set of specialized part-of-speech taggers is optimized for processing terms on the exception list.
11. A method according to claim 8, wherein the exception list includes terms which account for a predetermined percentage of errors produced by step (a).
12. A method according to claim 9, wherein the voting procedure generates a score for each unique candidate part-of-speech tag from the set of candidate part-of-speech tags, the score being based upon predetermined characteristics of each specialized part-of-speech tagger in the set of specialized part-of-speech taggers.
13. A method according to claim 12, wherein the voting procedure selects the part-of-speech tag with the highest score.
14. A method according to claim 8, further including, before step (a), parsing the text into word tokens.
15. A digital storage medium encoded with instructions which, when loaded into a computer, establishes a device for identifying the parts-of-speech of text, the device including: a first part-of-speech tagger that provides, at a first output, a part- of-speech tag for each term in the text; a set of specialized part-of-speech-taggers, having an output coupled to a device output and also having an input, the set of specialized part- of-speech taggers providing a set of candidate part-of-speech tags for each term provided at the input to the set of specialized part-of-speech taggers; and an exception handler, coupled to the first output, to provide, in response to each term in the text, a part-of-speech tag from the first output to the device output, unless the term in the text is included in an exception list, in which case the term is provided to the input of the set of specialized part-of- speech taggers.
16. A storage medium according to claim 15, wherein the set of specialized part of speech taggers includes a plurality of specialized part-of- speech taggers, the device further comprising: a selector, coupled to the output of the set of specialized part-of- speech taggers, the selector having an output coupled to the device output, for selecting a part-of-speech tag from the set of candidate part-of-speech tags using a voting procedure and providing the selected part-of-speech tag at the device output.
17. A storage medium according to claim 15, wherein at least one of the set of specialized part-of-speech taggers is optimized for processing terms on the exception list.
18. A storage medium according to claim 15, wherein the exception list includes terms which account for a predetermined percentage of errors produced by the first part-of-speech tagger.
19. A storage medium according to claim 16, wherein the voting procedure generates a score for each unique part-of-speech tag from the set of candidate part-of-speech tags, the score being based upon predetermined characteristics of each specialized part-of-speech tagger in the set of specialized part-of-speech taggers.
20. A storage medium according to claim 19 wherein the voting procedure selects the part-of-speech tag with the highest score.
21. A storage medium according to claim 15 , the device further including a tokenizer, coupled to the first part-of-speech tagger, for parsing the text into a set of word tokens.
PCT/US1999/027210 1998-11-17 1999-11-17 Method and apparatus for improved part-of-speech tagging WO2000030070A2 (en)

Priority Applications (2)

Application Number Priority Date Filing Date Title
US10877898P true 1998-11-17 1998-11-17
US60/108,778 1998-11-17

Applications Claiming Priority (4)

Application Number Priority Date Filing Date Title
JP2000582999A JP2002530761A (en) 1998-11-17 1999-11-17 Improved part-of-speech tagging method and apparatus
EP19990972347 EP1131812A2 (en) 1998-11-17 1999-11-17 Method and apparatus for improved part-of-speech tagging
CA 2351404 CA2351404A1 (en) 1998-11-17 1999-11-17 Method and apparatus for improved part-of-speech tagging
AU37899/00A AU3789900A (en) 1998-11-17 1999-11-17 Method and apparatus for improved part-of-speech tagging

Publications (2)

Publication Number Publication Date
WO2000030070A2 true WO2000030070A2 (en) 2000-05-25
WO2000030070A3 WO2000030070A3 (en) 2000-09-08

Family

ID=22323993

Family Applications (1)

Application Number Title Priority Date Filing Date
PCT/US1999/027210 WO2000030070A2 (en) 1998-11-17 1999-11-17 Method and apparatus for improved part-of-speech tagging

Country Status (5)

Country Link
EP (1) EP1131812A2 (en)
JP (1) JP2002530761A (en)
AU (1) AU3789900A (en)
CA (1) CA2351404A1 (en)
WO (1) WO2000030070A2 (en)

Cited By (91)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
WO2001082127A1 (en) * 2000-04-25 2001-11-01 Microsoft Corporation Language model sharing
GB2401972A (en) * 2003-05-20 2004-11-24 Hewlett Packard Development Co Identifying special word usage in a document
US6910004B2 (en) 2000-12-19 2005-06-21 Xerox Corporation Method and computer system for part-of-speech tagging of incomplete sentences
US8892446B2 (en) 2010-01-18 2014-11-18 Apple Inc. Service orchestration for intelligent automated assistant
US9152623B2 (en) 2012-11-02 2015-10-06 Fido Labs, Inc. Natural language processing system and method
US9201955B1 (en) 2010-04-15 2015-12-01 Google Inc. Unambiguous noun identification
US9262612B2 (en) 2011-03-21 2016-02-16 Apple Inc. Device access using voice authentication
US9300784B2 (en) 2013-06-13 2016-03-29 Apple Inc. System and method for emergency calls initiated by voice command
US9330720B2 (en) 2008-01-03 2016-05-03 Apple Inc. Methods and apparatus for altering audio output signals
US9338493B2 (en) 2014-06-30 2016-05-10 Apple Inc. Intelligent automated assistant for TV user interactions
US9368114B2 (en) 2013-03-14 2016-06-14 Apple Inc. Context-sensitive handling of interruptions
US9430463B2 (en) 2014-05-30 2016-08-30 Apple Inc. Exemplar-based natural language processing
US9483461B2 (en) 2012-03-06 2016-11-01 Apple Inc. Handling speech synthesis of content for multiple languages
US9495129B2 (en) 2012-06-29 2016-11-15 Apple Inc. Device, method, and user interface for voice-activated navigation and browsing of a document
US9502031B2 (en) 2014-05-27 2016-11-22 Apple Inc. Method for supporting dynamic grammars in WFST-based ASR
US9535906B2 (en) 2008-07-31 2017-01-03 Apple Inc. Mobile device having human language translation capability with positional feedback
US9576574B2 (en) 2012-09-10 2017-02-21 Apple Inc. Context-sensitive handling of interruptions by intelligent digital assistant
US9582608B2 (en) 2013-06-07 2017-02-28 Apple Inc. Unified ranking with entropy-weighted information for phrase-based semantic auto-completion
US9620104B2 (en) 2013-06-07 2017-04-11 Apple Inc. System and method for user-specified pronunciation of words for speech synthesis and recognition
US9620105B2 (en) 2014-05-15 2017-04-11 Apple Inc. Analyzing audio input for efficient speech and music recognition
US9626955B2 (en) 2008-04-05 2017-04-18 Apple Inc. Intelligent text-to-speech conversion
US9633004B2 (en) 2014-05-30 2017-04-25 Apple Inc. Better resolution when referencing to concepts
US9633660B2 (en) 2010-02-25 2017-04-25 Apple Inc. User profiling for voice input processing
US9633674B2 (en) 2013-06-07 2017-04-25 Apple Inc. System and method for detecting errors in interactions with a voice-based digital assistant
US9646614B2 (en) 2000-03-16 2017-05-09 Apple Inc. Fast, language-independent method for user authentication by voice
US9646609B2 (en) 2014-09-30 2017-05-09 Apple Inc. Caching apparatus for serving phonetic pronunciations
US9668121B2 (en) 2014-09-30 2017-05-30 Apple Inc. Social reminders
US9697822B1 (en) 2013-03-15 2017-07-04 Apple Inc. System and method for updating an adaptive speech recognition model
US9697820B2 (en) 2015-09-24 2017-07-04 Apple Inc. Unit-selection text-to-speech synthesis using concatenation-sensitive neural networks
US9711141B2 (en) 2014-12-09 2017-07-18 Apple Inc. Disambiguating heteronyms in speech synthesis
US9715875B2 (en) 2014-05-30 2017-07-25 Apple Inc. Reducing the need for manual start/end-pointing and trigger phrases
US9721566B2 (en) 2015-03-08 2017-08-01 Apple Inc. Competing devices responding to voice triggers
US9734193B2 (en) 2014-05-30 2017-08-15 Apple Inc. Determining domain salience ranking from ambiguous words in natural speech
US9760559B2 (en) 2014-05-30 2017-09-12 Apple Inc. Predictive text input
US9785630B2 (en) 2014-05-30 2017-10-10 Apple Inc. Text prediction using combined word N-gram and unigram language models
US9798393B2 (en) 2011-08-29 2017-10-24 Apple Inc. Text correction processing
US9818400B2 (en) 2014-09-11 2017-11-14 Apple Inc. Method and apparatus for discovering trending terms in speech requests
US9842101B2 (en) 2014-05-30 2017-12-12 Apple Inc. Predictive conversion of language input
US9842105B2 (en) 2015-04-16 2017-12-12 Apple Inc. Parsimonious continuous-space phrase representations for natural language processing
US9858925B2 (en) 2009-06-05 2018-01-02 Apple Inc. Using context information to facilitate processing of commands in a virtual assistant
US9865280B2 (en) 2015-03-06 2018-01-09 Apple Inc. Structured dictation using intelligent automated assistants
US9886953B2 (en) 2015-03-08 2018-02-06 Apple Inc. Virtual assistant activation
US9886432B2 (en) 2014-09-30 2018-02-06 Apple Inc. Parsimonious handling of word inflection via categorical stem + suffix N-gram language models
US9899019B2 (en) 2015-03-18 2018-02-20 Apple Inc. Systems and methods for structured stem and suffix language models
US9922642B2 (en) 2013-03-15 2018-03-20 Apple Inc. Training an at least partial voice command system
US9934775B2 (en) 2016-05-26 2018-04-03 Apple Inc. Unit-selection text-to-speech synthesis based on predicted concatenation parameters
US9953088B2 (en) 2012-05-14 2018-04-24 Apple Inc. Crowd sourcing information to fulfill user requests
US9959870B2 (en) 2008-12-11 2018-05-01 Apple Inc. Speech recognition involving a mobile device
US9966068B2 (en) 2013-06-08 2018-05-08 Apple Inc. Interpreting and acting upon commands that involve sharing information with remote devices
US9966065B2 (en) 2014-05-30 2018-05-08 Apple Inc. Multi-command single utterance input method
US9972304B2 (en) 2016-06-03 2018-05-15 Apple Inc. Privacy preserving distributed evaluation framework for embedded personalized systems
US9971774B2 (en) 2012-09-19 2018-05-15 Apple Inc. Voice-based media searching
US10043516B2 (en) 2016-09-23 2018-08-07 Apple Inc. Intelligent automated assistant
US10049668B2 (en) 2015-12-02 2018-08-14 Apple Inc. Applying neural network language models to weighted finite state transducers for automatic speech recognition
US10049663B2 (en) 2016-06-08 2018-08-14 Apple, Inc. Intelligent automated assistant for media exploration
US10057736B2 (en) 2011-06-03 2018-08-21 Apple Inc. Active transport based notifications
US10067938B2 (en) 2016-06-10 2018-09-04 Apple Inc. Multilingual word prediction
US10074360B2 (en) 2014-09-30 2018-09-11 Apple Inc. Providing an indication of the suitability of speech recognition
US10079014B2 (en) 2012-06-08 2018-09-18 Apple Inc. Name recognition system
US10078631B2 (en) 2014-05-30 2018-09-18 Apple Inc. Entropy-guided text prediction using combined word and character n-gram language models
US10083688B2 (en) 2015-05-27 2018-09-25 Apple Inc. Device voice control for selecting a displayed affordance
US10089072B2 (en) 2016-06-11 2018-10-02 Apple Inc. Intelligent device arbitration and control
US10101822B2 (en) 2015-06-05 2018-10-16 Apple Inc. Language input correction
US10127220B2 (en) 2015-06-04 2018-11-13 Apple Inc. Language identification from short strings
US10127911B2 (en) 2014-09-30 2018-11-13 Apple Inc. Speaker identification and unsupervised speaker adaptation techniques
US10134385B2 (en) 2012-03-02 2018-11-20 Apple Inc. Systems and methods for name pronunciation
US10170123B2 (en) 2014-05-30 2019-01-01 Apple Inc. Intelligent assistant for home automation
US10176167B2 (en) 2013-06-09 2019-01-08 Apple Inc. System and method for inferring user intent from speech inputs
US10185542B2 (en) 2013-06-09 2019-01-22 Apple Inc. Device, method, and graphical user interface for enabling conversation persistence across two or more instances of a digital assistant
US10186254B2 (en) 2015-06-07 2019-01-22 Apple Inc. Context-based endpoint detection
US10192552B2 (en) 2016-06-10 2019-01-29 Apple Inc. Digital assistant providing whispered speech
US10199051B2 (en) 2013-02-07 2019-02-05 Apple Inc. Voice trigger for a digital assistant
US10223066B2 (en) 2015-12-23 2019-03-05 Apple Inc. Proactive assistance based on dialog communication between devices
US10241644B2 (en) 2011-06-03 2019-03-26 Apple Inc. Actionable reminder entries
US10241752B2 (en) 2011-09-30 2019-03-26 Apple Inc. Interface for a virtual digital assistant
US10249300B2 (en) 2016-06-06 2019-04-02 Apple Inc. Intelligent list reading
US10255907B2 (en) 2015-06-07 2019-04-09 Apple Inc. Automatic accent detection using acoustic models
US10269345B2 (en) 2016-06-11 2019-04-23 Apple Inc. Intelligent task discovery
US10276170B2 (en) 2010-01-18 2019-04-30 Apple Inc. Intelligent automated assistant
US10283110B2 (en) 2009-07-02 2019-05-07 Apple Inc. Methods and apparatuses for automatic speech recognition
US10289433B2 (en) 2014-05-30 2019-05-14 Apple Inc. Domain specific language for encoding assistant dialog
US10297253B2 (en) 2016-06-11 2019-05-21 Apple Inc. Application integration with a digital assistant
US10318871B2 (en) 2005-09-08 2019-06-11 Apple Inc. Method and apparatus for building an intelligent automated assistant
US10356243B2 (en) 2015-06-05 2019-07-16 Apple Inc. Virtual assistant aided communication with 3rd party service in a communication session
US10354011B2 (en) 2016-06-09 2019-07-16 Apple Inc. Intelligent automated assistant in a home environment
US10366158B2 (en) 2015-09-29 2019-07-30 Apple Inc. Efficient word encoding for recurrent neural network language models
US10410637B2 (en) 2017-05-12 2019-09-10 Apple Inc. User-specific acoustic models
US10446143B2 (en) 2016-03-14 2019-10-15 Apple Inc. Identification of voice inputs providing credentials
US10446141B2 (en) 2014-08-28 2019-10-15 Apple Inc. Automatic speech recognition based on user feedback
US10482874B2 (en) 2017-05-15 2019-11-19 Apple Inc. Hierarchical belief states for digital assistants
US10490187B2 (en) 2016-09-15 2019-11-26 Apple Inc. Digital assistant providing automated status report

Citations (2)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
US4661924A (en) * 1984-07-31 1987-04-28 Hitachi, Ltd. Multiple-parts-of-speech disambiguating method and apparatus for machine translation system
US5680628A (en) * 1995-07-19 1997-10-21 Inso Corporation Method and apparatus for automated search and retrieval process

Patent Citations (2)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
US4661924A (en) * 1984-07-31 1987-04-28 Hitachi, Ltd. Multiple-parts-of-speech disambiguating method and apparatus for machine translation system
US5680628A (en) * 1995-07-19 1997-10-21 Inso Corporation Method and apparatus for automated search and retrieval process

Cited By (112)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
US9646614B2 (en) 2000-03-16 2017-05-09 Apple Inc. Fast, language-independent method for user authentication by voice
WO2001082127A1 (en) * 2000-04-25 2001-11-01 Microsoft Corporation Language model sharing
US7895031B2 (en) 2000-04-25 2011-02-22 Microsoft Corporation Language model sharing
US6910004B2 (en) 2000-12-19 2005-06-21 Xerox Corporation Method and computer system for part-of-speech tagging of incomplete sentences
US7269544B2 (en) 2003-05-20 2007-09-11 Hewlett-Packard Development Company, L.P. System and method for identifying special word usage in a document
GB2401972A (en) * 2003-05-20 2004-11-24 Hewlett Packard Development Co Identifying special word usage in a document
US10318871B2 (en) 2005-09-08 2019-06-11 Apple Inc. Method and apparatus for building an intelligent automated assistant
US9117447B2 (en) 2006-09-08 2015-08-25 Apple Inc. Using event alert text as input to an automated assistant
US8942986B2 (en) 2006-09-08 2015-01-27 Apple Inc. Determining user intent based on ontologies of domains
US8930191B2 (en) 2006-09-08 2015-01-06 Apple Inc. Paraphrasing of user requests and results by automated digital assistant
US10381016B2 (en) 2008-01-03 2019-08-13 Apple Inc. Methods and apparatus for altering audio output signals
US9330720B2 (en) 2008-01-03 2016-05-03 Apple Inc. Methods and apparatus for altering audio output signals
US9865248B2 (en) 2008-04-05 2018-01-09 Apple Inc. Intelligent text-to-speech conversion
US9626955B2 (en) 2008-04-05 2017-04-18 Apple Inc. Intelligent text-to-speech conversion
US9535906B2 (en) 2008-07-31 2017-01-03 Apple Inc. Mobile device having human language translation capability with positional feedback
US10108612B2 (en) 2008-07-31 2018-10-23 Apple Inc. Mobile device having human language translation capability with positional feedback
US9959870B2 (en) 2008-12-11 2018-05-01 Apple Inc. Speech recognition involving a mobile device
US9858925B2 (en) 2009-06-05 2018-01-02 Apple Inc. Using context information to facilitate processing of commands in a virtual assistant
US10475446B2 (en) 2009-06-05 2019-11-12 Apple Inc. Using context information to facilitate processing of commands in a virtual assistant
US10283110B2 (en) 2009-07-02 2019-05-07 Apple Inc. Methods and apparatuses for automatic speech recognition
US10276170B2 (en) 2010-01-18 2019-04-30 Apple Inc. Intelligent automated assistant
US8903716B2 (en) 2010-01-18 2014-12-02 Apple Inc. Personalized vocabulary for digital assistant
US8892446B2 (en) 2010-01-18 2014-11-18 Apple Inc. Service orchestration for intelligent automated assistant
US9548050B2 (en) 2010-01-18 2017-01-17 Apple Inc. Intelligent automated assistant
US9318108B2 (en) 2010-01-18 2016-04-19 Apple Inc. Intelligent automated assistant
US9633660B2 (en) 2010-02-25 2017-04-25 Apple Inc. User profiling for voice input processing
US10049675B2 (en) 2010-02-25 2018-08-14 Apple Inc. User profiling for voice input processing
US9201955B1 (en) 2010-04-15 2015-12-01 Google Inc. Unambiguous noun identification
US10102359B2 (en) 2011-03-21 2018-10-16 Apple Inc. Device access using voice authentication
US9262612B2 (en) 2011-03-21 2016-02-16 Apple Inc. Device access using voice authentication
US10241644B2 (en) 2011-06-03 2019-03-26 Apple Inc. Actionable reminder entries
US10057736B2 (en) 2011-06-03 2018-08-21 Apple Inc. Active transport based notifications
US9798393B2 (en) 2011-08-29 2017-10-24 Apple Inc. Text correction processing
US10241752B2 (en) 2011-09-30 2019-03-26 Apple Inc. Interface for a virtual digital assistant
US10134385B2 (en) 2012-03-02 2018-11-20 Apple Inc. Systems and methods for name pronunciation
US9483461B2 (en) 2012-03-06 2016-11-01 Apple Inc. Handling speech synthesis of content for multiple languages
US9953088B2 (en) 2012-05-14 2018-04-24 Apple Inc. Crowd sourcing information to fulfill user requests
US10079014B2 (en) 2012-06-08 2018-09-18 Apple Inc. Name recognition system
US9495129B2 (en) 2012-06-29 2016-11-15 Apple Inc. Device, method, and user interface for voice-activated navigation and browsing of a document
US9576574B2 (en) 2012-09-10 2017-02-21 Apple Inc. Context-sensitive handling of interruptions by intelligent digital assistant
US9971774B2 (en) 2012-09-19 2018-05-15 Apple Inc. Voice-based media searching
US9152623B2 (en) 2012-11-02 2015-10-06 Fido Labs, Inc. Natural language processing system and method
US10199051B2 (en) 2013-02-07 2019-02-05 Apple Inc. Voice trigger for a digital assistant
US9368114B2 (en) 2013-03-14 2016-06-14 Apple Inc. Context-sensitive handling of interruptions
US9922642B2 (en) 2013-03-15 2018-03-20 Apple Inc. Training an at least partial voice command system
US9697822B1 (en) 2013-03-15 2017-07-04 Apple Inc. System and method for updating an adaptive speech recognition model
US9966060B2 (en) 2013-06-07 2018-05-08 Apple Inc. System and method for user-specified pronunciation of words for speech synthesis and recognition
US9620104B2 (en) 2013-06-07 2017-04-11 Apple Inc. System and method for user-specified pronunciation of words for speech synthesis and recognition
US9633674B2 (en) 2013-06-07 2017-04-25 Apple Inc. System and method for detecting errors in interactions with a voice-based digital assistant
US9582608B2 (en) 2013-06-07 2017-02-28 Apple Inc. Unified ranking with entropy-weighted information for phrase-based semantic auto-completion
US9966068B2 (en) 2013-06-08 2018-05-08 Apple Inc. Interpreting and acting upon commands that involve sharing information with remote devices
US10176167B2 (en) 2013-06-09 2019-01-08 Apple Inc. System and method for inferring user intent from speech inputs
US10185542B2 (en) 2013-06-09 2019-01-22 Apple Inc. Device, method, and graphical user interface for enabling conversation persistence across two or more instances of a digital assistant
US9300784B2 (en) 2013-06-13 2016-03-29 Apple Inc. System and method for emergency calls initiated by voice command
US9620105B2 (en) 2014-05-15 2017-04-11 Apple Inc. Analyzing audio input for efficient speech and music recognition
US9502031B2 (en) 2014-05-27 2016-11-22 Apple Inc. Method for supporting dynamic grammars in WFST-based ASR
US9842101B2 (en) 2014-05-30 2017-12-12 Apple Inc. Predictive conversion of language input
US9734193B2 (en) 2014-05-30 2017-08-15 Apple Inc. Determining domain salience ranking from ambiguous words in natural speech
US10169329B2 (en) 2014-05-30 2019-01-01 Apple Inc. Exemplar-based natural language processing
US9430463B2 (en) 2014-05-30 2016-08-30 Apple Inc. Exemplar-based natural language processing
US9966065B2 (en) 2014-05-30 2018-05-08 Apple Inc. Multi-command single utterance input method
US10289433B2 (en) 2014-05-30 2019-05-14 Apple Inc. Domain specific language for encoding assistant dialog
US9785630B2 (en) 2014-05-30 2017-10-10 Apple Inc. Text prediction using combined word N-gram and unigram language models
US10083690B2 (en) 2014-05-30 2018-09-25 Apple Inc. Better resolution when referencing to concepts
US10078631B2 (en) 2014-05-30 2018-09-18 Apple Inc. Entropy-guided text prediction using combined word and character n-gram language models
US9633004B2 (en) 2014-05-30 2017-04-25 Apple Inc. Better resolution when referencing to concepts
US9715875B2 (en) 2014-05-30 2017-07-25 Apple Inc. Reducing the need for manual start/end-pointing and trigger phrases
US9760559B2 (en) 2014-05-30 2017-09-12 Apple Inc. Predictive text input
US10170123B2 (en) 2014-05-30 2019-01-01 Apple Inc. Intelligent assistant for home automation
US9338493B2 (en) 2014-06-30 2016-05-10 Apple Inc. Intelligent automated assistant for TV user interactions
US9668024B2 (en) 2014-06-30 2017-05-30 Apple Inc. Intelligent automated assistant for TV user interactions
US10446141B2 (en) 2014-08-28 2019-10-15 Apple Inc. Automatic speech recognition based on user feedback
US10431204B2 (en) 2014-09-11 2019-10-01 Apple Inc. Method and apparatus for discovering trending terms in speech requests
US9818400B2 (en) 2014-09-11 2017-11-14 Apple Inc. Method and apparatus for discovering trending terms in speech requests
US10127911B2 (en) 2014-09-30 2018-11-13 Apple Inc. Speaker identification and unsupervised speaker adaptation techniques
US9646609B2 (en) 2014-09-30 2017-05-09 Apple Inc. Caching apparatus for serving phonetic pronunciations
US9986419B2 (en) 2014-09-30 2018-05-29 Apple Inc. Social reminders
US9668121B2 (en) 2014-09-30 2017-05-30 Apple Inc. Social reminders
US10074360B2 (en) 2014-09-30 2018-09-11 Apple Inc. Providing an indication of the suitability of speech recognition
US9886432B2 (en) 2014-09-30 2018-02-06 Apple Inc. Parsimonious handling of word inflection via categorical stem + suffix N-gram language models
US9711141B2 (en) 2014-12-09 2017-07-18 Apple Inc. Disambiguating heteronyms in speech synthesis
US9865280B2 (en) 2015-03-06 2018-01-09 Apple Inc. Structured dictation using intelligent automated assistants
US10311871B2 (en) 2015-03-08 2019-06-04 Apple Inc. Competing devices responding to voice triggers
US9886953B2 (en) 2015-03-08 2018-02-06 Apple Inc. Virtual assistant activation
US9721566B2 (en) 2015-03-08 2017-08-01 Apple Inc. Competing devices responding to voice triggers
US9899019B2 (en) 2015-03-18 2018-02-20 Apple Inc. Systems and methods for structured stem and suffix language models
US9842105B2 (en) 2015-04-16 2017-12-12 Apple Inc. Parsimonious continuous-space phrase representations for natural language processing
US10083688B2 (en) 2015-05-27 2018-09-25 Apple Inc. Device voice control for selecting a displayed affordance
US10127220B2 (en) 2015-06-04 2018-11-13 Apple Inc. Language identification from short strings
US10101822B2 (en) 2015-06-05 2018-10-16 Apple Inc. Language input correction
US10356243B2 (en) 2015-06-05 2019-07-16 Apple Inc. Virtual assistant aided communication with 3rd party service in a communication session
US10255907B2 (en) 2015-06-07 2019-04-09 Apple Inc. Automatic accent detection using acoustic models
US10186254B2 (en) 2015-06-07 2019-01-22 Apple Inc. Context-based endpoint detection
US9697820B2 (en) 2015-09-24 2017-07-04 Apple Inc. Unit-selection text-to-speech synthesis using concatenation-sensitive neural networks
US10366158B2 (en) 2015-09-29 2019-07-30 Apple Inc. Efficient word encoding for recurrent neural network language models
US10049668B2 (en) 2015-12-02 2018-08-14 Apple Inc. Applying neural network language models to weighted finite state transducers for automatic speech recognition
US10223066B2 (en) 2015-12-23 2019-03-05 Apple Inc. Proactive assistance based on dialog communication between devices
US10446143B2 (en) 2016-03-14 2019-10-15 Apple Inc. Identification of voice inputs providing credentials
US9934775B2 (en) 2016-05-26 2018-04-03 Apple Inc. Unit-selection text-to-speech synthesis based on predicted concatenation parameters
US9972304B2 (en) 2016-06-03 2018-05-15 Apple Inc. Privacy preserving distributed evaluation framework for embedded personalized systems
US10249300B2 (en) 2016-06-06 2019-04-02 Apple Inc. Intelligent list reading
US10049663B2 (en) 2016-06-08 2018-08-14 Apple, Inc. Intelligent automated assistant for media exploration
US10354011B2 (en) 2016-06-09 2019-07-16 Apple Inc. Intelligent automated assistant in a home environment
US10192552B2 (en) 2016-06-10 2019-01-29 Apple Inc. Digital assistant providing whispered speech
US10067938B2 (en) 2016-06-10 2018-09-04 Apple Inc. Multilingual word prediction
US10269345B2 (en) 2016-06-11 2019-04-23 Apple Inc. Intelligent task discovery
US10297253B2 (en) 2016-06-11 2019-05-21 Apple Inc. Application integration with a digital assistant
US10089072B2 (en) 2016-06-11 2018-10-02 Apple Inc. Intelligent device arbitration and control
US10490187B2 (en) 2016-09-15 2019-11-26 Apple Inc. Digital assistant providing automated status report
US10043516B2 (en) 2016-09-23 2018-08-07 Apple Inc. Intelligent automated assistant
US10410637B2 (en) 2017-05-12 2019-09-10 Apple Inc. User-specific acoustic models
US10482874B2 (en) 2017-05-15 2019-11-19 Apple Inc. Hierarchical belief states for digital assistants

Also Published As

Publication number Publication date
AU3789900A (en) 2000-06-05
EP1131812A2 (en) 2001-09-12
JP2002530761A (en) 2002-09-17
WO2000030070A3 (en) 2000-09-08
CA2351404A1 (en) 2000-05-25

Similar Documents

Publication Publication Date Title
Bobrow Syntactic analysis of English by computer: a survey
Daelemans et al. Language-independent data-oriented grapheme-to-phoneme conversion
Derouault et al. Natural language modeling for phoneme-to-text transcription
Yarowsky Decision lists for lexical ambiguity resolution: Application to accent restoration in Spanish and French
Tan et al. Lstm-based deep learning models for non-factoid answer selection
Collins et al. Prepositional phrase attachment through a backed-off model
US6055528A (en) Method for cross-linguistic document retrieval
US5987404A (en) Statistical natural language understanding using hidden clumpings
Brants TnT: a statistical part-of-speech tagger
EP0583083B1 (en) Finite-state transduction of related word forms for text indexing and retrieval
Poibeau et al. Proper name extraction from non-journalistic texts
US7143036B2 (en) Ranking parser for a natural language processing system
Briscoe et al. Robust Accurate Statistical Annotation of General Text.
US8543565B2 (en) System and method using a discriminative learning approach for question answering
EP0907923B1 (en) Method and system for computing semantic logical forms from syntax trees
Rigau et al. Combining unsupervised lexical knowledge methods for word sense disambiguation
EP0953192B1 (en) Natural language parser with dictionary-based part-of-speech probabilities
US6473729B1 (en) Word phrase translation using a phrase index
US5835888A (en) Statistical language model for inflected languages
EP0415000B1 (en) Method and apparatus for spelling error detection and correction
Van den Bosch et al. Memory-based morphological analysis
Jelinek Up from trigrams!-the struggle for improved language models
US5510981A (en) Language translation apparatus and method using context-based translation models
US6490549B1 (en) Automatic orthographic transformation of a text stream
US6304841B1 (en) Automatic construction of conditional exponential models from elementary features

Legal Events

Date Code Title Description
AK Designated states

Kind code of ref document: A2

Designated state(s): AU CA JP

AL Designated countries for regional patents

Kind code of ref document: A2

Designated state(s): AT BE CH CY DE DK ES FI FR GB GR IE IT LU MC NL PT SE

121 Ep: the epo has been informed by wipo that ep was designated in this application
AL Designated countries for regional patents

Kind code of ref document: A3

Designated state(s): AT BE CH CY DE DK ES FI FR GB GR IE IT LU MC NL PT SE

AK Designated states

Kind code of ref document: A3

Designated state(s): AU CA JP

DFPE Request for preliminary examination filed prior to expiration of 19th month from priority date (pct application filed before 20040101)
ENP Entry into the national phase in:

Ref country code: CA

Ref document number: 2351404

Kind code of ref document: A

Format of ref document f/p: F

Ref country code: JP

Ref document number: 2000 582999

Kind code of ref document: A

Format of ref document f/p: F

Ref document number: 2351404

Country of ref document: CA

WWE Wipo information: entry into national phase

Ref document number: 37899/00

Country of ref document: AU

WWE Wipo information: entry into national phase

Ref document number: 1999972347

Country of ref document: EP

WWP Wipo information: published in national office

Ref document number: 1999972347

Country of ref document: EP

WWW Wipo information: withdrawn in national office

Ref document number: 1999972347

Country of ref document: EP