SA: Sentiment Analysis
Sentiment analysis (SA) is a subfield of artificial intelligence and natural language processing that seeks to interpret and extract emotions and opinions from unstructured text. The main goal of SA is to automate the detection and classification of positive, negative, or neutral sentiments in a given text source, such as […]
NER: Named Entity Recognition
Named Entity Recognition (NER), also known as named entity recognition, is a key technique in the field of Natural Language Processing (NLP) that aims to identify and extract specific entities within a text. These entities can include names of people, organizations, places, dates, numbers, among others. NER works through algorithms that analyze […]
POS: Part of Speech
Part of Speech (POS) Tagging is a fundamental technique in natural language processing (NLP) that consists of identifying and classifying words in a text according to their grammatical categories, such as nouns, verbs, adjectives, adverbs, articles, prepositions, interjections, conjunctions and numerals. The process involves the morphosyntactic analysis of each word to determine its role […]
WSD: Word Sense Disambiguation
Word Sense Disambiguation (WSD) is a task in Natural Language Processing (NLP) that aims to identify the correct meaning of a polysemous word (with multiple meanings) in a specific context. The WSD process involves analyzing the lexical and syntactic context of the words surrounding the ambiguous term to determine the most appropriate meaning.
SS: Speech Synthesis
Speech Synthesis, also known as SS, is a technology that allows the conversion of text into speech. This process involves transforming a sequence of characters into an audio wave that imitates the human voice. Speech synthesis uses advanced natural language processing (NLP) techniques and […]
SR: Speech Recognition
Speech Recognition (SR) is a technology that allows the conversion of human speech into digital text. This process involves several technical steps, including audio capture, signal pre-processing, extraction of acoustic features, and subsequent classification of phonetic units into words and phrases. The accuracy of the […]
MT: Machine Translation
Machine Translation (MT) is a sub-field of Artificial Intelligence (AI) dedicated to developing systems capable of translating text from one language to another without human intervention. These systems use complex algorithms, often based on neural networks, to analyze, interpret and generate content in different languages. MT can […]
QA: Question Answering
QA, or Question Answering, is a subfield of Artificial Intelligence (AI) that focuses on developing systems capable of answering questions formulated in natural language accurately and efficiently. These systems employ Natural Language Processing (NLP) and Machine Learning techniques to understand context, interpret the intent of the question, and provide […]
IR: Information Retrieval
Information Retrieval (IR) is the field of computer science that focuses on developing methods and techniques for searching, retrieving, and presenting relevant information in large volumes of data. IR uses mathematical models and algorithms to process user queries, retrieve documents or content that meet information needs, and […]
IE: Information Extraction
Information Extraction (IE) is an area of artificial intelligence and natural language processing that focuses on identifying, extracting, and structuring unstructured or semi-structured text data. The goal of IE is to convert unstructured data into structured information that can be easily stored, queried, and analyzed. The […]
