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» Language model adaptation using Random Forests
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SIGGRAPH
1998
ACM
13 years 11 months ago
Progressive Forest Split Compression
In this paper we introduce the Progressive Forest Split (PFS) representation, a new adaptive refinement scheme for storing and transmitting manifold triangular meshes in progress...
Gabriel Taubin, André Guéziec, Willi...
IJCNLP
2005
Springer
14 years 1 months ago
An Empirical Study on Language Model Adaptation Using a Metric of Domain Similarity
Abstract. This paper presents an empirical study on four techniques of language model adaptation, including a maximum a posteriori (MAP) method and three discriminative training mo...
Wei Yuan, Jianfeng Gao, Hisami Suzuki
ICASSP
2010
IEEE
13 years 7 months ago
Language recognition using deep-structured conditional random fields
We present a novel language identification technique using our recently developed deep-structured conditional random fields (CRFs). The deep-structured CRF is a multi-layer CRF mo...
Dong Yu, Shizhen Wang, Zahi Karam, Li Deng
INTERSPEECH
2010
13 years 2 months ago
Rapid bootstrapping of five eastern european languages using the rapid language adaptation toolkit
This paper presents our latest efforts toward LVCSR systems for five Eastern European languages such as Bulgarian, Croatian, Czech, Polish, and Russian using our Rapid Language Ad...
Ngoc Thang Vu, Tim Schlippe, Franziska Kraus, Tanj...
ICASSP
2008
IEEE
14 years 1 months ago
Unsupervised language model adaptation via topic modeling based on named entity hypotheses
Language model (LM) adaptation is often achieved by combining a generic LM with a topic-specific model that is more relevant to the target document. Unlike previous work on unsup...
Yang Liu, Feifan Liu