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    computational linguistics

    Explore "computational linguistics" with insightful episodes like "Introduction to Computational Linguistics (CL)", "Modelling semantic change from Ancient Greek to emoji", "Barbara McGillivray", "Language change as a (random?) walk in entropy space" and "Computational Literary Studies and Mental Health" from podcasts like """The AI Chronicles" Podcast", "Cambridge Language Sciences", "Cambridge Language Sciences", "Cambridge Language Sciences" and "Textual Therapies"" and more!

    Episodes (8)

    Introduction to Computational Linguistics (CL)

    Introduction to Computational Linguistics (CL)

    Computational Linguistics is an interdisciplinary field that combines principles from linguistics, computer science, and artificial intelligence to study language and develop algorithms and computational models to process, understand, and generate human language. It seeks to bridge the gap between human language and computers, enabling machines to comprehend and communicate with humans more effectively.

    Key areas of study in Computational Linguistics include:

    1. Natural Language Processing (NLP): NLP focuses on developing algorithms and techniques to enable computers to understand, interpret, and generate human language. Applications of NLP include machine translation, sentiment analysis, speech recognition, and text summarization.
    2. Speech Processing: This area deals specifically with speech-related tasks, such as speech recognition, speech synthesis, and speaker identification. It involves converting spoken language into text or vice versa.
    3. Machine Translation: Machine translation aims to develop automated systems that can translate text or speech from one language to another. It is a crucial application in today's globalized world.
    4. Information Retrieval: Information retrieval focuses on developing algorithms to retrieve relevant information from large collections of text or multimedia data, commonly used in search engines.
    5. Text Mining: Text mining involves extracting useful patterns and information from large volumes of unstructured text data, which can be useful in various domains such as sentiment analysis, market research, and opinion mining.
    6. Syntax and Semantics: Computational Linguistics also delves into the study of sentence structure (syntax) and meaning representation (semantics) to enable computers to understand the intricacies of human language.
    7. Language Generation: This area involves developing algorithms that can generate human-like language, used in chatbots, language modeling, and creative writing applications.
    8. Corpus Linguistics: Corpus Linguistics is the study of large collections of text (corpora) to gain insights into linguistic patterns and properties, which is essential for building robust NLP systems.

    Computational Linguistics has applications in various industries, including artificial intelligence, robotics, virtual assistants, customer support, healthcare, finance, and education, to name a few.

    Researchers and practitioners in Computational Linguistics employ various machine learning techniques, statistical models, and linguistic theories to develop sophisticated language processing systems. As technology advances, the capabilities of CL continue to grow, making natural language interactions with computers more seamless and human-like.

    Kind regards by Schneppat AI & GPT-5

    Computational Literary Studies and Mental Health

    Computational Literary Studies and Mental Health
    A project combining English literature, experimental psychology, and computational linguistics, with a focus on entropy, abstraction, and mental health. James Carney's current research investigates how mental illness interacts with textual structures – specifically, using machine learning to investigate the potential therapeutic qualities of literature with different levels of entropy (unpredictability) and abstraction, for anxiety disorders versus depression. We also touch on wider questions of motivation in the health humanities and literary studies, the appeal of belief in the transformative power of literature, and the expansion of textual/computational inquiry out into structural anthropology.