9789999340397 - A Computational Acoustic Analysis Of Prosodic Features In English Speech Insights From LLM-DL Model: Pakistani English Speech di Abbasi, Abdul Malik; Husain, Imtiaz... (12 risultati)

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Paperback. Condizione: Brand New. 108 pages. 6.00x0.25x9.00 inches. In Stock.

Condizione: New.

Condizione: New.

Condizione: New.

Paperback. Condizione: new. Paperback. This volume, 'A Computational Acoustic Analysis of Prosodic Features in Pakistani English Speech: Insights from Large Language and Deep Learning Models', represents a timely and innovative contribution to the field. By integrating computational acoustic methods with large language and deep learning models, the research advances both linguistic theory and applied technology. It demonstrates how machine learning can illuminate subtle prosodic distinctions, while also underscore the importance of documenting and analyze local varieties of English within global frameworks. This study seeks to advance our understanding of Pakistani English prosody by employing computational acoustic techniques integrated with large language models (LLMs) and deep learning (DL) frameworks. The methodological orientation reflects a commitment to both empirical rigor and technological innovation. By analyzing speech data through advanced computational models, the research provides insights into the distinctive prosodic contours of Pakistani English, while also demonstrating the applicability of machine learning approaches to linguistic inquiry. This item is printed on demand. Shipping may be from multiple locations in the US or from the UK, depending on stock availability.

PAP. Condizione: New. New Book. Shipped from UK. THIS BOOK IS PRINTED ON DEMAND. Established seller since 2000.

PAP. Condizione: New. New Book. Delivered from our UK warehouse in 4 to 14 business days. THIS BOOK IS PRINTED ON DEMAND. Established seller since 2000.

Paperback. Condizione: new. Paperback. This volume, 'A Computational Acoustic Analysis of Prosodic Features in Pakistani English Speech: Insights from Large Language and Deep Learning Models', represents a timely and innovative contribution to the field. By integrating computational acoustic methods with large language and deep learning models, the research advances both linguistic theory and applied technology. It demonstrates how machine learning can illuminate subtle prosodic distinctions, while also underscore the importance of documenting and analyze local varieties of English within global frameworks. This study seeks to advance our understanding of Pakistani English prosody by employing computational acoustic techniques integrated with large language models (LLMs) and deep learning (DL) frameworks. The methodological orientation reflects a commitment to both empirical rigor and technological innovation. By analyzing speech data through advanced computational models, the research provides insights into the distinctive prosodic contours of Pakistani English, while also demonstrating the applicability of machine learning approaches to linguistic inquiry. This item is printed on demand. Shipping may be from our Sydney, NSW warehouse or from our UK or US warehouse, depending on stock availability.

Paperback. Condizione: new. Paperback. This volume, 'A Computational Acoustic Analysis of Prosodic Features in Pakistani English Speech: Insights from Large Language and Deep Learning Models', represents a timely and innovative contribution to the field. By integrating computational acoustic methods with large language and deep learning models, the research advances both linguistic theory and applied technology. It demonstrates how machine learning can illuminate subtle prosodic distinctions, while also underscore the importance of documenting and analyze local varieties of English within global frameworks. This study seeks to advance our understanding of Pakistani English prosody by employing computational acoustic techniques integrated with large language models (LLMs) and deep learning (DL) frameworks. The methodological orientation reflects a commitment to both empirical rigor and technological innovation. By analyzing speech data through advanced computational models, the research provides insights into the distinctive prosodic contours of Pakistani English, while also demonstrating the applicability of machine learning approaches to linguistic inquiry. This item is printed on demand. Shipping may be from our UK warehouse or from our Australian or US warehouses, depending on stock availability.

Taschenbuch. Condizione: Neu. nach der Bestellung gedruckt Neuware - Printed after ordering - This volume, 'A Computational Acoustic Analysis of Prosodic Features in Pakistani English Speech: Insights from Large Language and Deep Learning Models', represents a timely and innovative contribution to the field. By integrating computational acoustic methods with large language and deep learning models, the research advances both linguistic theory and applied technology. It demonstrates how machine learning can illuminate subtle prosodic distinctions, while also underscore the importance of documenting and analyze local varieties of English within global frameworks. This study seeks to advance our understanding of Pakistani English prosody by employing computational acoustic techniques integrated with large language models (LLMs) and deep learning (DL) frameworks. The methodological orientation reflects a commitment to both empirical rigor and technological innovation. By analyzing speech data through advanced computational models, the research provides insights into the distinctive prosodic contours of Pakistani English, while also demonstrating the applicability of machine learning approaches to linguistic inquiry.

Taschenbuch. Condizione: Neu. A Computational Acoustic Analysis Of Prosodic Features In English Speech Insights From LLM-DL Model | Pakistani English Speech | Abdul Malik Abbasi | Taschenbuch | Englisch | 2026 | Eliva Press | EAN 9789999340397 | Verantwortliche Person für die EU: Libri GmbH, Europaallee 1, 36244 Bad Hersfeld, gpsr[at]libri[dot]de | Anbieter: preigu Print on Demand.