
Statistical Language and Speech Processing
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The 9 full papers presented in this volume were carefully reviewed and selected from 21 submissions. The papers present topics of either theoretical or applied interest discussing the employment of statistical models (including machine learning) within language and speech processing.
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Content
Transfer Learning.- Automatic News Article Generation from Legislative Proceedings: A Phenom-based Approach.- Comparison of Czech Transformers on Text Classification Tasks.- Constructing Sentiment Lexicon with Game for Annotation Collection.- Robustness of Named Entity Recognition: Case of Latvian.- Speech.- Use of Speaker Metadata for Improving Automatic Pronunciation Assessment.- Augmenting ASR for user-generated videos with semi-supervised training and acoustic model adaptation for Spoken Content Retrieval.- Various DNN-HMM Architectures Used in Acoustic Modeling with
Single-Speaker and Single-Channel Invariant Representation Learning for Robust Far-Field Speaker Recognition.
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