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1、CHAPTER3CONFIDENCEMEASURES,DIALOGMODELINGANDUSERINTERFACESUMMARYTheprevioustwochaptersreviewed,respectively,themainsourcesofvariability/distortionandthecurrentstateoftheartofenvironment-independent/adaptivespeechrecognitiontechnology.Inthischapterwediscusswhatarethecriticaltechnologies
2、/componentsthatmakespeechrecognitionusable.Whendesigninganapplication,issuessuchashowtoassignaconfidencescoretoanhypothesis,howtodealwithextraneousspeechandout-ofvocabularywords,andhowtoprovideuserfeedbackanddesignefficienterrorcorrectiontechnologyisofprimeimportance.Moreover,manyappli
3、cationsnecessitatethedevelopmentofadialogmodulewhichmodelswhatisgoingonintheinteraction,capturesthecontextofthecommunication(whathasbeensaidbefore)andhelpstheusercompletehisrequest(ifneeded)andtoperformactions.Thischapteremphasizesthesetechnologiesandprovidessomedesignrecommendationson
4、howtodesignprompts,generateuserfeedbackanddevelopspeechuserinterfaces.75Chapter3ConfidenceMeasures,DialogModelingandUserInterface3.1.INTRODUCTIONInthelastdecade,theperformanceofspeechrecognitionsystemshasreachedanacceptablerange,makingpossiblemanyapplicationssuchasvoicedialing,informat
5、ionretrievaloverthephoneanddictation.Thesesystemsperformreasonablywellwhentheuseriscooperativeandcarefullyusesthesystem’svocabulary.However,whentheuser’sspeechcontainsoutofvocabularywordsordeviatesfromthetaskgrammaracceptedbythesystem,recognitionaccuracydegradessharply.Inparticular,whe
6、nspeakersarenoviceusersofthesystem,hesitations,Out-Of-Vocabulary(OOV)wordsandfillersoundsarebecomingaproblemforspeechrecognition.Inpracticalapplications,itiscommonthatabout20to30%oftheuserutterancesareoutofthegrammarspecifications.Ausablesystemshouldbeabletoignoreextraneousspeechandnoi
7、seandtodeterminehowconfidentitisinthespeechthathasbeenrecognized.Toextractpartialinformationfromaninpututteranceword-spottingalgorithmshavebeendeveloped.Thesealgorithmshavebeenappliedtoanumberofproblemsthatcansufferfromunexpectedspeechinput.Afterpartialinformationhasbeenextracted,iti
