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dc.contributorJames H. Martin-
dc.contributor.authorDaniel Jurafsky-
dc.date.accessioned2026-04-23T07:10:19Z-
dc.date.available2026-04-23T07:10:19Z-
dc.date.issued2025-
dc.identifier.urihttp://thuvienso.thanglong.edu.vn//handle/TLU/13686-
dc.description.abstractIn the first part of the book we introduce the fundamental suite of algorithmic and linguistic tools that make up the modern neural large language model. We begin with tokenization and preprocessing, including Unicode, and then proceed to intro- duce many basic language modeling ideas using simple n-gram language models, we then introduce the algorithms which are the components of large language models logistic regression, embeddings, and feedforward networks. Next we are ready to introduce the principles of large language modeling, encoder, decoders and pretrain- ing, then the fundamental transformer architecture, then masked language model and other architectures like RNNs and LSTMs, information retrieval and retrieval- based algorithms like RAG, machine translation and the encoder-decoder model, and finally spoken language modeling including both ASR and TTS.vi
dc.language.isoenvi
dc.publisherPearson Educationvi
dc.subjectNatural language processing | Computational linguistics | Speech processing systems | Deep learning | Xử lý ngôn ngữ tự nhiên | Ngôn ngữ học tính toán | Nhận dạng tiếng nóivi
dc.titleSpeech and language processing : An introduction to natural language processing, computational linguistics, and speech recognitionvi
dc.typeSách/Bookvi
Appears in CollectionsKhoa học máy tính - Toán

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