Statistical Language and Speech Processing

This book consitutes the refereed proceedings of the First International Conference on Statistical Language and Speech Processing, SLSP 2013, held in Tarragona, Spain, in July 2013. The 24 full papers presented together with two invited talks were carefully reviewed and selected from 61 submissions. The papers cover a wide range of topics in the fields of computational language and speech processing and the statistical methods that are currently in use.

Inhalt

Deep Learning of Representations: Looking Forward.- Challenges and Opportunities of Multilingual Information.- Unsupervised Rhyme Scheme Identification in Hip Hop Lyrics Using Hidden Markov Models.- Complementarity of Lexical Cohesion and Speaker Role Information for Story Segmentation of French TV Broadcast News.- An Investigation of Single-Pass ASR System Combination for Spoken Language Understanding.- Predicting Part-of-Speech Tags and Morpho-Syntactic Relations Using
Similarity-Based Technique.- Statistical Error Correction Methods for Domain-Specific ASR Systems.- Reward Shaping for Statistical Optimisation of Dialogue Management.- Discriminative Framework for Spoken Tunisian Dialect Understanding.- Histogram Equalization Using Centroids of Fuzzy C-Means of Background Speakers' Utterances for Speaker Identification.- Cross-Lingual Random Indexing for Information Retrieval.- Rational Kernels for Arabic Text Classification.- MDL-Based Models for Transliteration Generation.- Using Regression for Spectral Estimation of HMMs.- Iterative Rule Segmentation under Minimum Description Length for Unsupervised Transduction Grammar Induction.- Comparing Resources for Spanish Lexical Simplification.- Context-Aware Correction of Spelling Errors in Hungarian Medical Documents.- Pronunciation Extraction from Phoneme Sequences through Cross-Lingual Word-to-Phoneme Alignment.- Can Statistical Tests Be Used for Feature Selection in Diachronic Text Classification?.- Factored Semantic Sequence Kernel for Sentiment Polarity Classification.- An Investigation of Code-Switching Attitude Dependent Language Modeling.