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Statistical Language and Speech Processing

Overview of attention for book
Cover of 'Statistical Language and Speech Processing'

Table of Contents

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    Book Overview
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    Chapter 1 Continuous-Space Language Processing: Beyond Word Embeddings
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    Chapter 2 Testing the Robustness of Laws of Polysemy and Brevity Versus Frequency
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    Chapter 3 Delexicalized and Minimally Supervised Parsing on Universal Dependencies
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    Chapter 4 Unsupervised Morphological Segmentation Using Neural Word Embeddings
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    Chapter 5 Statistical Analysis of the Prosodic Parameters of a Spontaneous Arabic Speech Corpus for Speech Synthesis
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    Chapter 6 Combining Syntactic and Acoustic Features for Prosodic Boundary Detection in Russian
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    Chapter 7 Articulatory Gesture Rich Representation Learning of Phonological Units in Low Resource Settings
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    Chapter 8 Estimating the Severity of Parkinson’s Disease Using Voiced Ratio and Nonlinear Parameters
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    Chapter 9 Optimal Feature Set and Minimal Training Size for Pronunciation Adaptation in TTS
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    Chapter 10 A New Perspective on Combining GMM and DNN Frameworks for Speaker Adaptation
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    Chapter 11 Class n-Gram Models for Very Large Vocabulary Speech Recognition of Finnish and Estonian
Attention for Chapter 11: Class n-Gram Models for Very Large Vocabulary Speech Recognition of Finnish and Estonian
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3 Mendeley
Summary
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Chapter title
Class n-Gram Models for Very Large Vocabulary Speech Recognition of Finnish and Estonian
Chapter number 11
Book title
Statistical Language and Speech Processing
Published by
Springer, Cham, October 2016
DOI 10.1007/978-3-319-45925-7_11
Book ISBNs
978-3-31-945924-0, 978-3-31-945925-7
Authors

Matti Varjokallio, Mikko Kurimo, Sami Virpioja, Varjokallio, Matti, Kurimo, Mikko, Virpioja, Sami

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Mendeley readers

Mendeley readers

The data shown below were compiled from readership statistics for 3 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Unknown 3 100%

Demographic breakdown

Readers by professional status Count As %
Student > Ph. D. Student 1 33%
Student > Bachelor 1 33%
Other 1 33%
Readers by discipline Count As %
Nursing and Health Professions 1 33%
Computer Science 1 33%
Engineering 1 33%

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