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» A Markov Random Field Model for Automatic Speech Recognition
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ACL
2004
13 years 7 months ago
Using Conditional Random Fields to Predict Pitch Accents in Conversational Speech
The detection of prosodic characteristics is an important aspect of both speech synthesis and speech recognition. Correct placement of pitch accents aids in more natural sounding ...
Michelle L. Gregory, Yasemin Altun
IPCV
2008
13 years 7 months ago
Speech Recognition System of Arabic Digits based on A Telephony Arabic Corpus
- Automatic recognition of spoken digits is one of the difficult tasks in the field of computer speech recognition. Spoken digits recognition process is required in many applicatio...
Yousef Alotaibi, Mansour Al-Ghamdi, Fahad Alotaiby
EMNLP
2008
13 years 7 months ago
Revealing the Structure of Medical Dictations with Conditional Random Fields
Automatic processing of medical dictations poses a significant challenge. We approach the problem by introducing a statistical framework capable of identifying types and boundarie...
Jeremy Jancsary, Johannes Matiasek, Harald Trost
KDD
2010
ACM
274views Data Mining» more  KDD 2010»
13 years 9 months ago
Grafting-light: fast, incremental feature selection and structure learning of Markov random fields
Feature selection is an important task in order to achieve better generalizability in high dimensional learning, and structure learning of Markov random fields (MRFs) can automat...
Jun Zhu, Ni Lao, Eric P. Xing
ACL
2004
13 years 7 months ago
Discriminative Language Modeling with Conditional Random Fields and the Perceptron Algorithm
This paper describes discriminative language modeling for a large vocabulary speech recognition task. We contrast two parameter estimation methods: the perceptron algorithm, and a...
Brian Roark, Murat Saraclar, Michael Collins, Mark...