NLP concepts Flashcards
What is natural language processing (NLP)?
NLP enables computers to understand, interpret, and generate human language.
What principles does NLP apply?
NLP applies principles from linguistics and computational linguistics.
What are the main functions of NLP?
Understanding, interpreting, and generating human language.
What techniques are used in NLP?
Statistical models, machine learning, and deep learning.
What do statistical NLP models rely on?
Probabilistic models and mathematical algorithms.
What are examples of statistical NLP techniques?
N-grams, hidden Markov models, and conditional random fields.
How do machine learning-based NLP models work?
They learn patterns and relationships from labeled data.
What tasks do machine learning NLP models perform?
Text classification, sentiment analysis, and named entity recognition.
What does deep learning contribute to NLP?
It enables complex representations of language data using neural networks.
What are key applications of NLP?
Text processing, speech processing, morphological analysis, syntactical analysis, and semantic understanding.
What does text and speech processing include?
Speech recognition, language understanding, and text-to-speech synthesis.
What is morphological analysis?
Understanding word structure and form, including stemming and lemmatization.
What is syntactical analysis?
Analyzing grammatical structure using parsing and part-of-speech tagging.
What is lexical semantics?
Understanding word meanings and relationships, such as synonym detection.
What is relational semantics?
Understanding sentence meanings and logical relationships.
What is discourse analysis?
Understanding larger text structures, including coreference resolution.
Why is NLP useful?
For text analysis, speech interpretation, language translation, and command processing.
What is speech recognition?
Converting spoken language into text.
What is speech tagging?
Assigning linguistic tags to words in spoken sentences.
What is meaning disambiguation?
Resolving ambiguities in spoken language to determine intended meaning.
What are the types of NLP approaches?
Symbolic, statistical, and neural NLP models.
What is symbolic NLP?
Using predefined rules and linguistic knowledge bases.
What is statistical NLP?
Using probabilistic models to learn language patterns.
What is neural NLP?
Using artificial neural networks for language processing.
What NLP services does Microsoft Azure provide?
Text analysis, speech interpretation, translation, and command processing.
How does Azure NLP analyze text?
By extracting entities, relationships, and insights.
What does Azure NLP enable for spoken language?
Understanding spoken queries and synthesizing responses.
How does Azure NLP help with language translation?
It translates text between languages in real time.
How does Azure NLP support command processing?
By understanding user intents and executing tasks.
