1. A method comprising:
extracting, by a computer processor of a computing system from a plurality of documents, content, wherein said extracting said content comprises:
performing, by said computer processor, a text analytics process with respect to said plurality of documents;
presenting, by said computer processor, a first screen interface comprising a metrics search menu, wherein said first screen interface presents a menu indicating a hierarchal order for various metrics;
enabling, by said first screen interface, a metrics search;
identifying, by said computer processor based on results of said text analytics process and said metrics search, extraction patterns associated with said content, wherein said extraction patterns comprise metrics and business rules comprising key content types that require sharing among peers;
presenting, by said computer processor, a second screen interface comprising a concept search menu, wherein said second screen interface presents a menu indicating a hierarchal order for business processes, concepts, metrics, and rules;
identifying, by said computer processor based on results of said text analytics process and a concept search enabled by said second screen interface, concepts from glossaries;
extracting, by said computer processor, said concepts from said content in accordance with said extraction patterns; and
determining, by said computer processor based on results of comparing said concepts to a plurality of specified concepts, new concepts of said concepts;
presenting, by said computer processor, a third screen interface enabling a process for exporting, importing, and merging metrics, wherein said third screen interface presents a menu indicating identified content sources and content details associated with said content;
enabling, by said third screen interface, said process for exporting, importing, and merging metrics;
publishing, by said computer processor based on said enabling said process for exporting, importing, and merging metrics, said content in external glossaries;
publishing, by said computer processor, said content arranged in a business content hierarchy in a specified format;
enabling, by said computer processor, said business content hierarchy in a plurality of business related projects; and
arranging, by said computer processor, updated content associated with said content and said business content hierarchy in said updated business content hierarchy.
2. The method of claim 1, wherein said publishing said business content hierarchy comprises:
translating, by said computer processor, an XML version of said business content hierarchy into a DHTML format using an XSL process; and
displaying, by said computer processor, said content as a tree structure or an alphabetical structure.
3. The method of claim 1, wherein said publishing said business content hierarchy comprises:
translating, by said computer processor, an XML version of said business content hierarchy into a DHTML format using an XSL process; and
generating, by said computer processor, a document comprising said content presented as a tree structure or an alphabetical structure.
4. The method of claim 1, wherein said publishing said enabling said business content hierarchy in said plurality of projects comprises:
performing a read only operation, by said computer processor, associated with an XML version of said business content hierarchy; and
retrieving, by said computer processor, details associated with said content.
5. The method of claim 4, wherein said read only operation comprises an operation selected from the group consisting of searching, zooming, and highlighting.
6. The method of claim 1, wherein said updating said content and said business content hierarchy comprises:
loading, by said computer processor, a selected file associated with said content;
translating, by said computer processor, an XML version of said selected file into a DHTML format using an XSL process; and
importing, by said computer processor, additional content associated with said selected file.
7. The method of claim 1, wherein said updating said content and said business content hierarchy comprises:
loading, by said computer processor, selected node content associated with said content;
applying, by said computer processor, pagination to said selected node content;
presenting, by said computer processor via an explorer export window, business content of said selected node content;
receiving, by said computer processor from a user, a selection for specific content of said business content;
exporting, by said computer processor to an external location, said specific content.
8. The method of claim 1, wherein said updating said content and said business content hierarchy comprises:
loading, by said computer processor, a selected file associated with said content;
translating, by said computer processor, an XML version of said selected file into a DHTML format using an XSL process; and
adding, by said computer processor, additional content associated with said selected file.
9. The method of claim 1, further comprising:
providing a process for supporting a computer infrastructure, said process comprising providing at least one support service for at least one of creating, integrating, hosting, maintaining, and deploying computer-readable code in the computing system, wherein the code in combination with the computing system performs the method of claim 1.
10. A computing system comprising a computer processor coupled to a computer-readable memory unit, said memory unit comprising instructions that when executed by the computer processor implements a method comprising:
extracting, by said computer processor from a plurality of documents, content, wherein said extracting said content comprises:
performing, by said computer processor, a text analytics process with respect to said plurality of documents;
presenting, by said computer processor, a first screen interface comprising a metrics search menu, wherein said first screen interface presents a menu indicating a hierarchal order for various metrics;
enabling, by said first screen interface, a metrics search;
identifying, by said computer processor based on results of said text analytics process and said metrics search, extraction patterns associated with said content, wherein said extraction patterns comprise metrics and business rules comprising key content types that require sharing among peers;
presenting, by said computer processor, a second screen interface comprising a concept search menu, wherein said second screen interface presents a menu indicating a hierarchal order for business processes, concepts, metrics, and rules;
identifying, by said computer processor based on results of said text analytics process and a concept search enabled by said second screen interface, concepts from glossaries;
extracting, by said computer processor, said concepts from said content in accordance with said extraction patterns; and
determining, by said computer processor based on results of comparing said concepts to a plurality of specified concepts, new concepts of said concepts;
presenting, by said computer processor, a third screen interface enabling a process for exporting, importing, and merging metrics, wherein said third screen interface presents a menu indicating identified content sources and content details associated with said content;
enabling, by said third screen interface, said process for exporting, importing, and merging metrics;
publishing, by said computer processor based on said enabling said process for exporting, importing, and merging metrics, said content in external glossaries;
publishing, by said computer processor, said content arranged in a business content hierarchy in a specified format;
enabling, by said computer processor, said business content hierarchy in a plurality of business related projects; and
arranging, by said computer processor, updated content associated with said content and said business content hierarchy in said updated business content hierarchy.
11. The computing system of claim 10, wherein said publishing said business content hierarchy comprises:
translating, by said computer processor, an XML version of said business content hierarchy into a DHTML format using an XSL process; and
displaying, by said computer processor, said content as a tree structure or an alphabetical structure.
12. The computing system of claim 10, wherein said publishing said business content hierarchy comprises:
translating, by said computer processor, an XML version of said business content hierarchy into a DHTML format using an XSL process; and
generating, by said computer processor, a document comprising said content presented as a tree structure or an alphabetical structure.
13. The computing system of claim 10, wherein said publishing said enabling said business content hierarchy in said plurality of projects comprises:
performing a read only operation, by said computer processor, associated with an XML version of said business content hierarchy; and
retrieving, by said computer processor, details associated with said content.
14. The computing system of claim 13, wherein said read only operation comprises an operation selected from the group consisting of searching, zooming, and highlighting.
15. The computing system of claim 10, wherein said updating said content and said business content hierarchy comprises:
loading, by said computer processor, a selected file associated with said content;
translating, by said computer processor, an XML version of said selected file into a DHTML format using an XSL process; and
importing, by said computer processor, additional content associated with said selected file.
16. The computing system of claim 10, wherein said updating said content and said business content hierarchy comprises:
loading, by said computer processor, selected node content associated with said content;
applying, by said computer processor, pagination to said selected node content;
presenting, by said computer processor via an explorer export window, business content of said selected node content;
receiving, by said computer processor from a user, a selection for specific content of said business content;
exporting, by said computer processor to an external location, said specific content.
17. The computing system of claim 10, wherein said updating said content and said business content hierarchy comprises:
loading, by said computer processor, a selected file associated with said content;
translating, by said computer processor, an XML version of said selected file into a DHTML format using an XSL process; and
adding, by said computer processor, additional content associated with said selected file.
18. A computer program product, comprising a computer readable hardware storage device storing a computer readable program code, said computer readable program code comprising an algorithm that when executed by a computer processor of a computing system implements a method, said method comprising:
extracting, by said computer processor from a plurality of documents, content, wherein said extracting said content comprises:
performing, by said computer processor, a text analytics process with respect to said plurality of documents;
presenting, by said computer processor, a first screen interface comprising a metrics search menu, wherein said first screen interface presents a menu indicating a hierarchal order for various metrics;
enabling, by said first screen interface, a metrics search;
identifying, by said computer processor based on results of said text analytics process and said metrics search, extraction patterns associated with said content, wherein said extraction patterns comprise metrics and business rules comprising key content types that require sharing among peers;
presenting, by said computer processor, a second screen interface comprising a concept search menu, wherein said second screen interface presents a menu indicating a hierarchal order for business processes, concepts, metrics, and rules;
identifying, by said computer processor based on results of said text analytics process and a concept search enabled by said second screen interface, concepts from glossaries;
extracting, by said computer processor, said concepts from said content in accordance with said extraction patterns; and
determining, by said computer processor based on results of comparing said concepts to a plurality of specified concepts, new concepts of said concepts;
presenting, by said computer processor, a third screen interface enabling a process for exporting, importing, and merging metrics, wherein said third screen interface presents a menu indicating identified content sources and content details associated with said content;
enabling, by said third screen interface, said process for exporting, importing, and merging metrics;
publishing, by said computer processor based on said enabling said process for exporting, importing, and merging metrics, said content in external glossaries;
publishing, by said computer processor, said content arranged in a business content hierarchy in a specified format;
enabling, by said computer processor, said business content hierarchy in a plurality of business related projects; and
arranging, by said computer processor, updated content associated with said content and said business content hierarchy in said updated business content hierarchy.
19. The computer program product of claim 18, wherein said publishing said business content hierarchy comprises:
translating, by said computer processor, an XML version of said business content hierarchy into a DHTML format using an XSL process; and
displaying, by said computer processor, said content as a tree structure or an alphabetical structure.
20. The computer program product of claim 18, wherein said publishing said business content hierarchy comprises:
translating, by said computer processor, an XML version of said business content hierarchy into a DHTML format using an XSL process; and
generating, by said computer processor, a document comprising said content presented as a tree structure or an alphabetical structure.
The claims below are in addition to those above.
All refrences to claim(s) which appear below refer to the numbering after this setence.
1. A method comprising:
starting an automatic speech recognition session for a phone call initiated from a communication device;
determining that the communication device is associated with a plurality of users;
identifying a group of selected speech recognition models comprising a speaker independent model and a plurality of speaker dependent models;
recognizing an utterance received from a particular user in the plurality of users using each model in the group of selected speech recognition models in parallel, to yield a group of recognition results;
selecting a dominant speech model from the group of selected speech recognition models using a heuristic search algorithm, to yield a selected dominant speech model, wherein the dominant speech model is an efficient model in the group of selected speech recognition models; and
continuously using the selected dominant speech model to recognize speech received from the particular user for a remainder of the automatic speech recognition session.
2. The method of claim 1, further comprising dropping a speech model from the group of selected speech recognition models when recognition accuracy is below a threshold.
3. The method of claim 1, further comprising selecting the plurality of speaker dependent models based on the communication device.
4. The method of claim 3, further comprising selecting the plurality of speaker dependent models based on the plurality of users associated with the communication device.
5. The method of claim 3, further comprising receiving additional utterances from the communication device and clustering the additional utterances to generate a new speaker dependent model.
6. The method of claim 1, further comprising iteratively generating the group of selected models, recognizing the utterance, and selecting the dominant speech model, each time a new automatic speech recognition session is initiated.
7. A system comprising:
a processor;
a computer-readable storage medium having instructions stored which, when executed by the processor, cause the processor to perform operations comprising:
starting an automatic speech recognition session for a phone call initiated from a communication device;
determining that the communication device is associated with a plurality of users;
identifying a group of selected speech recognition models comprising a speaker independent model and a plurality of speaker dependent models;
recognizing an utterance received from a particular user in the plurality of users using each model in the group of selected speech recognition models in parallel, to yield a group of recognition results;
selecting a dominant speech model from the group of selected speech recognition models using a heuristic search algorithm, to yield a selected dominant speech model, wherein the dominant speech model is an efficient model in the group of selected speech recognition models; and
continuously using the selected dominant speech model to recognize speech received from the particular user for a remainder of the automatic speech recognition session.
8. The system of claim 7, the computer-readable storage medium having additional instructions stored which, when executed by the processor, result in operations comprising dropping a speech model from the group of selected speech recognition models when recognition accuracy is below a threshold.
9. The system of claim 7, the computer-readable storage medium having additional instructions which, when executed by the processor, result in operations comprising selecting the plurality of speaker dependent models based on the communication device.
10. The system of claim 9, the computer-readable storage medium having additional instructions which, when executed by the processor, result in operations comprising selecting the plurality of speaker dependent models based on the plurality of users associated with the communication device.
11. The system of claim 9, the computer-readable storage medium having additional instructions which, when executed by the processor, result in operations comprising:
receiving utterances from the communication device; and
clustering the utterances to generate a new speaker dependent model.
12. The system of claim 7, the computer-readable storage medium storing additional instructions which, when executed by the processor, result in operations comprising iteratively generating the group of selected speech recognition models, recognizing the utterance, and selecting the dominant speech model, each time a new automatic speech recognition session is initiated.
13. A computer-readable storage device having instructions stored which, when executed by a computing device, cause the computing device to perform operations comprising:
starting an automatic speech recognition session for a phone call initiated from a communication device;
determining that the communication device is associated with a plurality of users;
identifying a group of selected speech recognition models comprising a speaker independent model and a plurality of speaker dependent models;
recognizing an utterance received from a particular user in the plurality of users using each model in the group of selected speech recognition models in parallel, to yield a group of recognition results;
selecting a dominant speech model from the group of selected speech recognition models using a heuristic search algorithm, to yield a selected dominant speech model, wherein the dominant speech model is an efficient model in the group of selected speech recognition models; and
continuously using the selected dominant speech model to recognize speech received from the particular user for a remainder of the automatic speech recognition session.
14. The computer-readable storage device of claim 13, having additional instructions stored which, when executed by the computing device, result in operations comprising dropping a speech model from the group of selected speech recognition models when recognition accuracy is below a threshold.
15. The computer-readable storage device of claim 13, having additional instructions stored which, when executed by the computing device, result in operations comprising:
selecting the plurality of speaker dependent models based on the plurality of users associated with the communication device.