A virtual assistant (VA) is a software agent that can perform various tasks or services for users based on their input, including commands or questions. These assistants often use chatbot technology to simulate human conversation, allowing users to interact with them through online chat or voice. Virtual assistants can interpret user speech and respond using synthesized voices.
Users can ask virtual assistants questions, control smart home devices, manage tasks like email and calendars,[1] and perform other basic functions through verbal commands. Popular virtual assistants for consumers include Amazon's Alexa, Apple's Siri, Microsoft's Cortana, and Google Assistant.[2] Many companies also use virtual assistant technology to enhance customer service or support.[3]
The advancement of artificial intelligence, particularly in chatbot technology like ChatGPT, has expanded the capabilities and interest in virtual assistant products and services.[4][5]
References
- ↑ Hoy, Matthew B. (2018). "Alexa, Siri, Cortana, and More: An Introduction to Voice Assistants". Medical Reference Services Quarterly. 37 (1): 81–88. doi:10.1080/02763869.2018.1404391. PMID 29327988. S2CID 30809087.
- ↑ "AI Faceoff: Siri vs. Cortana vs. Google Assistant vs. Alexa - businessnewsdaily.com". Business News Daily.
- ↑ "The Magic of Virtual Assistants and Their Impact on Customer Service".
- ↑ "The One Thing You Should Definitely be Using AI Chatbot for". 7 April 2023.
- ↑ "A.I. Means everyone gets a 'white-collar' personal assistant, Bill Gates says".
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| General terms | |
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| Text analysis |
- Argument mining
- Collocation extraction
- Concept mining
- Coreference resolution
- Deep linguistic processing
- Distant reading
- Information extraction
- Named-entity recognition
- Ontology learning
- Parsing
- Semantic parsing
- Syntactic parsing
- Part-of-speech tagging
- Semantic analysis
- Semantic role labeling
- Semantic decomposition
- Semantic similarity
- Sentiment analysis
- Terminology extraction
- Text mining
- Textual entailment
- Truecasing
- Word-sense disambiguation
- Word-sense induction
| Text segmentation |
- Compound-term processing
- Lemmatisation
- Lexical analysis
- Text chunking
- Stemming
- Sentence segmentation
- Word segmentation
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| Automatic summarization |
- Multi-document summarization
- Sentence extraction
- Text simplification
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| Machine translation |
- Computer-assisted
- Example-based
- Rule-based
- Statistical
- Transfer-based
- Neural
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| Distributional semantics models |
- BERT
- Document-term matrix
- Explicit semantic analysis
- fastText
- GloVe
- Language model (large)
- Latent semantic analysis
- Seq2seq
- Word embedding
- Word2vec
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Language resources, datasets and corpora | Types and standards |
- Corpus linguistics
- Lexical resource
- Linguistic Linked Open Data
- Machine-readable dictionary
- Parallel text
- PropBank
- Semantic network
- Simple Knowledge Organization System
- Speech corpus
- Text corpus
- Thesaurus (information retrieval)
- Treebank
- Universal Dependencies
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| Data |
- BabelNet
- Bank of English
- DBpedia
- FrameNet
- Google Ngram Viewer
- UBY
- WordNet
- Wikidata
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Automatic identification and data capture | |
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| Topic model |
- Document classification
- Latent Dirichlet allocation
- Pachinko allocation
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Computer-assisted reviewing |
- Automated essay scoring
- Concordancer
- Grammar checker
- Predictive text
- Pronunciation assessment
- Spell checker
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Natural language user interface | |
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| Related |
- Formal semantics
- Hallucination
- Natural Language Toolkit
- spaCy
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