It can be used to understand the user's problem on the Internet, and provide the necessary services to users according to the results of understanding;
You can also use voice conversations with users on a wireless internet or telephone network (combining D-EAR Keyword-Spotter and D-EAR Parser).
Compared with the specification language, the understanding of the natural language has a greater difficulty.
This is because natural language contains a lot of spoken language, such as omitting, referring to, correction, repetition, emphasis, reverse order, etc.
Speaking conversation systems involving voice will also include noise, unclear, speech, eating sound, sound, etc.
Compared to keyword-based technologies, the advantages of language understanding techniques are:
(1) Direct. When the information query, the user can go straight to the topic without the selection of multi-level menus.
____ (2) Flexible. User queries don't have to be strictly inquired in accordance with certain "keywords", as long as the user's narrative is consistent with the query on "Semantic".
D-EAR PARSER Features: (1) Support context-related understanding; (2) can freely transform topics; (3) hybrid. Dialog Manager within D-EAR Parser knows what problems have been to be answered by the user, which issues need to get the user's answer, and you can remind the system to actively ask the user to get enough information. Users can freely transform the topics when interacting with the system.
D-EAR PARSER technology can be used in places such as phones, mobile phones, wireless communications, etc., and intelligent queries, information acquisition, etc. According to the specific application field, such as flight inquiries and ticket, tour guides, weather inquiry, stock query and transactions, etc., customization.
The "Deliberal Dialogue System" development tool contains a set of customization tools to help implement a specific field of spoken language dialogue systems, embedding a privilege analyzer (a semantic analysis), a privileged dialog manager (manage the dialogue history and Context-related analysis and omitting analysis can be handled) and a proud text generator (to generate natural response text).
Application example - Speaking dialogue system:
Combine D-Ear Keyword-Spotter and D-EAR Parser, you can implement a language-based oral dialogue system (SDS, SPOKEN DIALOGUE SYSTEM), so that people can perform mutual conversations with the computer, so that the computer understands what people say, Clear people's needs and provide corresponding information services.
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