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» Canonical state models for automatic speech recognition
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ICASSP
2010
IEEE
14 years 4 months ago
Unsupervised knowledge acquisition for Extracting Named Entities from speech
This paper presents a Named Entity Recognition (NER) method dedicated to process speech transcriptions. The main principle behind this method is to collect in an unsupervised way ...
Frédéric Béchet, Eric Charton
ICASSP
2011
IEEE
14 years 1 months ago
A study of the effect of emotional state upon text-independent speaker identification
In this paper we evaluate the effect of the emotional state of a speaker when text-independent speaker identification is performed. The spectral features used for speaker recogni...
Marius Vasile Ghiurcau, Corneliu Rusu, Jaakko Asto...
ECML
2006
Springer
15 years 1 months ago
PAC-Learning of Markov Models with Hidden State
The standard approach for learning Markov Models with Hidden State uses the Expectation-Maximization framework. While this approach had a significant impact on several practical ap...
Ricard Gavaldà, Philipp W. Keller, Joelle P...
INTERSPEECH
2010
14 years 4 months ago
Audio-visual anticipatory coarticulation modeling by human and machine
The phenomenon of anticipatory coarticulation provides a basis for the observed asynchrony between the acoustic and visual onsets of phones in certain linguistic contexts. This ty...
Louis H. Terry, Karen Livescu, Janet B. Pierrehumb...
ICASSP
2008
IEEE
15 years 4 months ago
Unsupervised learning of auditory filter banks using non-negative matrix factorisation
Non-negative matrix factorisation (NMF) is an unsupervised learning technique that decomposes a non-negative data matrix into a product of two lower rank non-negative matrices. Th...
Alexander Bertrand, Kris Demuynck, Veronique Stout...