Language Technology
Language technology (LT) refers to the use of computational methods, artificial intelligence (AI), and linguistic knowledge to process, understand, and generate human language. It includes various tools and techniques that enable computers to analyze, translate, and interact with language in written and spoken forms.
Key Areas of Language Technology:
- Natural Language Processing (NLP) – Algorithms that analyze and generate human language, such as text summarization, named entity recognition, and sentiment analysis.
- Machine Translation (MT) – Automated translation systems like Google Translate and DeepL.
- Speech Processing – Speech-to-text (STT) and text-to-speech (TTS) technologies for voice recognition and synthesis.
- Information Retrieval & Semantic Search – Search engines that understand meaning and context rather than just keywords.
- Optical Character Recognition (OCR) – Extracting text from images or scanned documents.
- Text Mining & Information Extraction – Finding relevant patterns, keywords, or insights from large text datasets.
- Conversational AI & Chatbots – AI-driven virtual assistants like ChatGPT, Alexa, and Siri.
- Text Simplification & Summarization – Making complex content more understandable or generating concise summaries.
Applications of Language Technology:
- Multilingual communication (e.g., automatic translation tools)
- Accessibility (e.g., screen readers, speech synthesis for visually impaired users)
- Knowledge management (e.g., extracting insights from research articles)
- Smart search engines with contextual understanding
- Digital assistants and customer service automation
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