Titlebook: Statistical Language and Speech Processing; First International Adrian-Horia Dediu,Carlos Martín-Vide,Bianca Truth Conference proceedings

Lyme-disease

Unsupervised Rhyme Scheme Identification in Hip Hop Lyrics Using Hidden Markov Modelsentifica-tion of rhyme schemes in hip hop lyrics, which to the best of our knowledge, is the first such effort. Unlike previous approaches that use supervised or semi-supervised approaches for the task of rhyme scheme identification, our model does not assume any prior phonetic or labeling informati

Tonometry

Complementarity of Lexical Cohesion and Speaker Role Information for Story Segmentation of French TVon and speaker role analysis. We propose an improved selection strategy from the classical lexical cohesion curve as well as an integrated supervised classification approach that jointly exploits the two views. The combination of these methods leads to significant improvements on a rich French datab

Medley

FAZE

Predicting Part-of-Speech Tags and Morpho-Syntactic Relations Using Similarity-Based Techniquee compound words before they are fed into a tagger. The technique relies on a set of features from Chinese morphemes as well as a set of collocation markers which provide hints on the syntactic categories of the compound words. The technique is trained with a compound words database with more than 5

格子架

欢乐东方

Reward Shaping for Statistical Optimisation of Dialogue Managementves a reward after each transition between two dialogue states. A sparse function only gives a reward at the end of the dialogue. Reward shaping consists of learning a diffuse function without modifying the optimal policy compared to a sparse one..Two reward shaping methods are applied to a corpus o

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该得

Finding the Most Likely Upper Level State Sequence for Hierarchical HMMsm, a direct extension of the Viterbi algorithm for hidden Markov models (HMMs), has been used to find the most likely state sequence for hierarchical HMMs. However, the generalized Viterbi algorithm finds the most likely whole level state sequence rather than the most likely upper level state sequen

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BUST

Speech/Music Discrimination via Energy Density Analysis method is based on the analysis of local energy for 1 or 2.5 seconds audio signals. An elementary analysis of the probability for the power distribution is an effective tool supporting the decision making system. We compare our feature with Percentage of Low Energy Frames (LEF), Modified Low Energy