2025年英語ai面試題庫及答案

一、單項選擇題（總共10題，每題2分）1.WhichofthefollowingisNOTacomponentofnaturallanguageprocessing(NLP)?A.TokenizationB.SentimentanalysisC.ImagerecognitionD.Part-of-speechtagging2.Theprocessofconvertingspokenlanguageintotextisknownas:A.TranscriptionB.TranslationC.SummarizationD.Parsing3.WhichAImodelisprimarilyusedforgeneratinghuman-liketext?A.ConvolutionalNeuralNetwork(CNN)B.RecurrentNeuralNetwork(RNN)C.GenerativeAdversarialNetwork(GAN)D.Transformer4.WhatisthemainpurposeofalanguagemodelinAI?A.ToidentifyobjectsinimagesB.TopredictthenextwordinasentenceC.TotranslatetextfromonelanguagetoanotherD.Torecognizespeechpatterns5.Whichofthefollowingtechniquesiscommonlyusedfortextsummarization?A.SentimentanalysisB.NamedentityrecognitionC.KeywordextractionD.Speechrecognition6.Theterm"BERT"standsfor:A.BidirectionalEncoderRepresentationsfromTransformersB.BasicEncodingandRepresentationTechniqueC.BigEnglishTextRepresentationD.BinaryEncodingandTextRecognition7.Whichofthefollowingisanexampleofasequence-to-sequencemodel?A.LSTMB.CNNC.GAND.BERT8.Theprocessofidentifyingandclassifyingtheemotionaltoneofatextisknownas:A.NamedentityrecognitionB.Part-of-speechtaggingC.SentimentanalysisD.Textgeneration9.WhichofthefollowingisNOTacommontaskinmachinetranslation?A.TranslationmemoryB.NeuralmachinetranslationC.Rule-basedtranslationD.Speech-to-textconversion10.Thetechniqueofusingpre-trainedmodelsandfine-tuningthemforspecifictasksisknownas:A.TransferlearningB.OverfittingC.UnderfittingD.Regularization二、填空題（總共10題，每題2分）1.Theprocessofbreakingdowntextintosmallerunitsiscalled________.2.Atechniqueusedtoidentifytheentities(likenames,dates,etc.)intextiscalled________.3.Theprocessofconvertingtextintoanumericalformatthatmachinescanunderstandiscalled________.4.ThetermusedtodescribetheabilityofanAImodeltounderstandandgeneratehuman-liketextis________.5.Amodelthatusesboththepastandfuturecontexttounderstandawordiscalleda________.6.Theprocessofgeneratingaconcisesummaryofalongertextiscalled________.7.Thetechniqueoftrainingamodelononetaskandthenapplyingittoadifferentbutrelatedtaskiscalled________.8.Theprocessofidentifyingthepartsofspeech(likenoun,verb,adjective)inasentenceiscalled________.9.Theprocessofconvertingspokenlanguageintotextiscalled________.10.Thetechniqueofusingmultiplemodelstoimprovetheoverallperformanceiscalled________.三、判斷題（總共10題，每題2分）1.Naturallanguageprocessing(NLP)isasubfieldofartificialintelligencethatfocusesontheinteractionbetweencomputersandhumanlanguage.2.Tokenizationistheprocessofconvertingatextintoasequenceofwordsorphrases.3.Sentimentanalysisisusedtoidentifythesentimentoremotionaltoneofatext.4.Imagerecognitionisapartofnaturallanguageprocessing.5.BERTisatransformer-basedmodelusedforvariousNLPtasks.6.Sequence-to-sequencemodelsareusedfortaskslikemachinetranslation.7.Namedentityrecognitionisusedtoidentifyandclassifytheemotionaltoneofatext.8.Transferlearningistheprocessofusingpre-trainedmodelsandfine-tuningthemforspecifictasks.9.Part-of-speechtaggingisusedtoidentifytheentitiesintext.10.Speechrecognitionistheprocessofconvertingtextintoanumericalformat.四、簡答題（總共4題，每題5分）1.Explaintheconceptoftokenizationinnaturallanguageprocessing.2.DescribethemaincomponentsofatransformermodelusedinNLP.3.DiscusstheimportanceofsentimentanalysisinAIapplications.4.ExplainhowtransferlearningcanbebeneficialinNLPtasks.五、討論題（總共4題，每題5分）1.DiscussthechallengesindevelopingAImodelsformachinetranslation.2.Explainhowpre-trainedmodelslikeBERThaverevolutionizedNLP.3.DiscusstheethicalimplicationsofusingAIinnaturallanguageprocessing.4.DiscussthefuturetrendsinnaturallanguageprocessingandAI.答案和解析一、單項選擇題答案1.C2.A3.D4.B5.C6.A7.D8.C9.D10.A二、填空題答案1.Tokenization2.Namedentityrecognition3.Textrepresentation4.Naturallanguageunderstanding5.Bidirectionalmodel6.Textsummarization7.Transferlearning8.Part-of-speechtagging9.Speechrecognition10.Ensemblelearning三、判斷題答案1.True2.True3.True4.False5.True6.True7.False8.True9.False10.False四、簡答題答案1.Tokenizationistheprocessofbreakingdowntextintosmallerunitscalledtokens.Thesetokenscanbewords,phrases,orevencharacters.TokenizationisessentialinNLPasithelpsinconvertinghuman-readabletextintoaformatthatmachinescanprocess.2.Atransformermodelconsistsofanencoderandadecoder.Theencoderprocessestheinputsequenceandgeneratesacontext-richrepresentation,whilethedecodergeneratestheoutputsequencebasedontheencoder'soutput.Themodelusesself-attentionmechanismstocapturetherelationshipsbetweendifferentpartsoftheinputsequence.3.SentimentanalysisiscrucialinAIapplicationsasithelpsinunderstandingtheemotionaltoneofatext.Thiscanbeusedincustomerfeedbackanalysis,socialmediamonitoring,andmarketresearch.Byanalyzingsentiment,businessescanmakeinformeddecisionsandimprovecustomersatisfaction.4.Transferlearninginvolvesusingpre-trainedmodelsonlargedatasetsandfine-tuningthemforspecifictasks.ThisapproachisbeneficialinNLPbecauseitreducestheamountofdataandcomputationalresourcesrequired,acceleratestraining,andimprovesmodelperformance.Pre-trainedmodelsalreadyhavearichunderstandingoflanguage,whichcanbeleveragedforvarioustasks.五、討論題答案1.DevelopingAImodelsformachinetranslationfacesseveralchallenges,includinghandlingthevastdiversityoflanguages,maintainingcontextacrosslongsentences,andensuringtheaccuracyoftranslations.Additionally,culturalnuancesandidiomaticexpressionscanbedifficulttocaptureaccurately.2.Pre-trainedmodelslikeBERThaverevolutionizedNLPbyprovidingarobustfoundationforvarioustasks.Thesemodelsaretrainedonlargedatasetsandcanbefine-tunedforspecificapplications,significantlyimprovingperformanc