Download presentation
Presentation is loading. Please wait.
Published byMagnus Marshall Modified over 9 years ago
1
speech in, speech out
2
24 listopad 2006WS0607 – elevator2/15 Nuance server compiled recognition grammar, master language package, licence manager Nuance client speech-in components
3
24 listopad 2006WS0607 – elevator3/15 anticipate user’s responses what pieces of information are needed to complete the dialog? in what order will they be requested? one piece of information at a time in particular order (directed dialog), several pieces at once, in any order, and prompt for missing items (mixed initiative)? recognition grammar
4
24 listopad 2006WS0607 – elevator4/15 syntax Nuance: Grammar Specification Language (GSL) Diamant: Speech Recognition Grammar Format (SRGF) recognition grammar
5
24 listopad 2006WS0607 – elevator5/15 GSL grammar: doc in a file with.grammar extension; e.g. mygram.grammar (mygram will be the resulting package name) contents:GrammarRuleName GrammarDescription GrammarRuleName: at least one uppercase character GrammarDescription: sequence of words, grammar names, and operators that define a set of recognizable word sequences words (terminals) in lower-case operators: recognition grammar () concat(A B C... Y)A and B and... [ ] disjunction[A B C... Y ]either A or B or... ? optional?YY is optional + positive closure+Yat least one Y * Kleene star*Yzero or more Y
6
24 listopad 2006WS0607 – elevator6/15 GSL grammar: example expressions [morning afternoon evening] “morning”, “afternoon”, “evening” (good [morning afternoon evening]) “good morning”, “good afternoon”, “good evening” (?good [morning afternoon evening]) “good morning”, “good afternoon”, “good evening”, “morning”, “afternoon”, “evening” (thanks +very much) “thanks very much”, “thanks very very much”,... (thanks *very much) “thanks much”, “thanks very much”, “thanks very very much”,... recognition grammar
7
24 listopad 2006WS0607 – elevator7/15 example GSL grammar.grammar file.slot_definitions file.GO_FLOOR [ FLOOR:f (?the FLOOR:f floor) (?the FLOOR:f please) (?Filler ?the FLOOR:f floor ?please) ] { } Filler [ (i would like to go to) (i want to go to) (uh) ] FLOOR [ first{return("1")} second{return("2")} third{return("3")} fourth{return("4")} ] recognition grammar floor
8
24 listopad 2006WS0607 – elevator8/15 another option: SRGF and export as Nuance GSL GrammarTest.bat recognition grammar
9
24 listopad 2006WS0607 – elevator9/15 compiling the package (compile-package.bat) set PKGHOME = path to your gsl file (w/o extension) nuance-compile %PKGHOME% English.America.1.3.0 recognition grammar master recognition package
10
24 listopad 2006WS0607 – elevator10/15 testing the grammar (text) parse-tool -package path_to_your_model nl-tool –package path_to_your_model –grammar grammar_in_your_model recognition grammar
11
24 listopad 2006WS0607 – elevator11/15 running Nuance: licence manager: lm.bat recognition server: rs.bat set PKGHOME = path to your compiled model recserver -package %PKGHOME% lm.Addresses=localhost config.... testing the grammar (speech) xapp -package path to your compiled model lm.Addresses=localhost speech recognition
12
24 listopad 2006WS0607 – elevator12/15 running nuance client edit Diamant config file: Clients.ini NuanceClient.bat (btw, have the licence manager and the server running too... duh!...) Diamant with speech-in
13
24 listopad 2006WS0607 – elevator13/15 adding speech-in add device as usual activate recognition: output „start” (start command) to nuance client read (speech) input from nuance client into variable as usual access recognition confidence (of type Real) like this: var#confidence Diamant with speech-in
14
24 listopad 2006WS0607 – elevator14/15 Mary server online at DFKI... Mary client MaryClient.bat speech-out components
15
24 listopad 2006WS0607 – elevator15/15 Diamant with speech-out adding speech-out add device as usual optionally, set format: {format = } (default plain text) and voice {voice = } in output node, output to Mary client as usual
16
24 listopad 2006WS0607 – elevator16/15 speech-enabled dialogs recognition tends to be imperfect... if recognition confidence low, then, for example (btw, think: grounding): repeat question ask for confirmation („did you say blah?”) inform user what they can say („you can say blah, bloo, and blee, please try again”) but... don’t let user get stuck in endless clarification dialog either!
Similar presentations
© 2025 SlidePlayer.com. Inc.
All rights reserved.