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Brain mechanisms of acoustic communication in humans and nonhuman primates: An evolutionary perspective
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In: Behavioral and Brain Sciences (2014)
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22 |
Writing: Movements of the self
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In: Theory & Psychology (2014)
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24 |
Language-independent grapheme-phoneme conversion and word stress assignment as a web service
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26 |
Phylogenetic reorganization of the basal ganglia: A necessary, but not the only, bridge over a primate Rubicon of acoustic communication
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In: Behavioral and Brain Sciences (2014)
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27 |
Parameterization and automatic labeling of Hungarian intonation
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28 |
An analysis of post-vocalic /s-∫/ neutralization in Augsburg German: evidence for a gradient sound change
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In: Frontiers in Psychology (2014)
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29 |
Predictability of the effects of phoneme merging on speech recognition performance by quantifying phoneme relations
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30 |
From segmentation bootstrapping to transcription-to-word conversion
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In: Proc. Interspeech (2013)
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31 |
Accentual phrase in languages with fixed word stress: a study on Hungarian and Slovak
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In: Workshop Advancing Prosodic Transcription for Spoken Language Science and Technology II, Phonetics and Phonology in Iberia 2013 (2013)
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Information theoretic syllable structure and its relation to the c-center effect
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34 |
A dialect distance metric based on string and temporal alignment
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In: Elektronische Sprachsignalverarbeitung (2013)
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35 |
Exploring the connection of acoustic and distinctive features
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In: Proc. Interspeech 2013 (2013)
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36 |
Parameterization of F0 register and discontinuity to predict prosodic boundary strength in Hungarian spontaneous speech
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Machine Learning of Probabilistic Phonological Pronunciation Rules from the Italian CLIPS Corpus
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In: Proc. Interspeech (2013)
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Abstract:
A blending of phonological concepts and technical analysis is proposed to yield a better modeling and understanding of phonological processes. Based on the manual segmentation and labeling of the Italian CLIPS corpus we automatically derive a probabilistic set of phonological pronunciation rules: a new alignment technique is used to map the phonological form of spontaneous sentences onto the phonetic surface form. A machine-learning algorithm then calculates a set of phonologi- cal replacement rules together with their conditional probabilities. A critical analysis of the resulting probabilistic rule set is presented and discussed with regard to regional Italian accents. The rule set presented here is also applied in the newly published web-service WebMAUS that allows a user to segment and phonetically label Italian speech via a simple web-interface.
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Keyword:
ddc:410; Phonetik und Sprachverarbeitung
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URL: https://epub.ub.uni-muenchen.de/18046/1/SchielIS2013.pdf https://epub.ub.uni-muenchen.de/18046/ http://nbn-resolving.de/urn:nbn:de:bvb:19-epub-18046-1 https://doi.org/10.5282/ubm/epub.18046
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38 |
Automatisation of intonation modelling and its linguistic anchoring
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39 |
Probabilistic induction of metrical trees for word stress assignment
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In: Proc. ESSV (2012)
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Informationstheorie in der Literaturwissenschaft
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In: CLARIN-D Newsletter (2012)
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