Statistical Language And Speech Processing
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Statistical Methods for Speech Recognition
This book reflects decades of important research on the mathematical foundations of speech recognition. It focuses on underlying statistical techniques such as hidden Markov models, decision trees, the expectation-maximization algorithm, information theoretic goodness criteria, maximum entropy probability estimation, parameter and data clustering, and smoothing of probability distributions. The author's goal is to present these principles clearly in the simplest setting, to show the advantages of self-organization from real data, and to enable the reader to apply the techniques. Bradford Books imprint
Speech and Language Processing
This book takes an empirical approach to language processing, based on applying statistical and other machine-learning algorithms to large corpora.Methodology boxes are included in each chapter. Each chapter is built around one or more worked examples to demonstrate the main idea of the chapter. Covers the fundamental algorithms of various fields, whether originally proposed for spoken or written language to demonstrate how the same algorithm can be used for speech recognition and word-sense disambiguation. Emphasis on web and other practical applications. Emphasis on scientific evaluation. Useful as a reference for professionals in any of the areas of speech and language processing.
Statistical Language and Speech Processing
This book constitutes the refereed proceedings of the Third International Conference on Statistical Language and Speech Processing, SLSP 2015, held in Budapest, Hungary, in November 2015. The 26 full papers presented together with two invited talks were carefully reviewed and selected from 71 submissions. The papers cover topics such as: anaphora and coreference resolution; authorship identification, plagiarism and spam filtering; computer-aided translation; corpora and language resources; data mining and semantic Web; information extraction; information retrieval; knowledge representation and ontologies; lexicons and dictionaries; machine translation; multimodal technologies; natural language understanding; neural representation of speech and language; opinion mining and sentiment analysis; parsing; part-of-speech tagging; question-answering systems; semantic role labelling; speaker identification and verification; speech and language generation; speech recognition; speech synthesis; speech transcription; spelling correction; spoken dialogue systems; term extraction; text categorisation; text summarisation; and user modeling.