Word frequency and text type: some observations based on the LOB corpus of British English texts
Computers and the Humanities
Text compression
A Cache-Based Natural Language Model for Speech Recognition
IEEE Transactions on Pattern Analysis and Machine Intelligence
Pattern Classification (2nd Edition)
Pattern Classification (2nd Edition)
Two-stage language models for information retrieval
SIGIR '02 Proceedings of the 25th annual international ACM SIGIR conference on Research and development in information retrieval
Stochastic k-testable Tree Languages and Applications
ICGI '02 Proceedings of the 6th International Colloquium on Grammatical Inference: Algorithms and Applications
Supertagging: an approach to almost parsing
Computational Linguistics
A study of smoothing methods for language models applied to information retrieval
ACM Transactions on Information Systems (TOIS)
Parsing with Probabilistic Strictly Locally Testable Tree Languages
IEEE Transactions on Pattern Analysis and Machine Intelligence
ConLL '00 Proceedings of the 2nd workshop on Learning language in logic and the 4th conference on Computational natural language learning - Volume 7
Information extraction from research papers using conditional random fields
Information Processing and Management: an International Journal
Joint-sequence models for grapheme-to-phoneme conversion
Speech Communication
Scaling high-order character language models to gigabytes
Software '05 Proceedings of the Workshop on Software
Smoothing and compression with stochastic k-testable tree languages
Pattern Recognition
Discrete visual features modeling via leave-one-out likelihood estimation and applications
Journal of Visual Communication and Image Representation
Classifying melodies using tree grammars
IbPRIA'11 Proceedings of the 5th Iberian conference on Pattern recognition and image analysis
On multimodal interactive machine translation using speech recognition
ICMI '11 Proceedings of the 13th international conference on multimodal interfaces
Statistical behavior analysis of smoothing methods for language models of mandarin data sets
AIRS'06 Proceedings of the Third Asia conference on Information Retrieval Technology
Improving on-line handwritten recognition in interactive machine translation
Pattern Recognition
Hi-index | 0.14 |
In this paper, we apply the leaving-one-out concept to the estimation of 驴small驴 probabilities, i.e., the case where the number of training samples is much smaller than the number of possible classes. After deriving the Turing-Good formula in this framework, we introduce several specific models in order to avoid the problems of the original Turing-Good formula. These models are the constrained model, the absolute discounting model and the linear discounting model. These models are then applied to the problem of bigram-based stochastic language modeling. Experimental results are presented for a German and an English corpus.