Neural Lattice Language Models
@article{Buckman2018NeuralLL, title={Neural Lattice Language Models}, author={J. Buckman and Graham Neubig}, journal={Transactions of the Association for Computational Linguistics}, year={2018}, volume={6}, pages={529-541} }
In this work, we propose a new language modeling paradigm that has the ability to perform both prediction and moderation of information flow at multiple granularities: neural lattice language models. These models construct a lattice of possible paths through a sentence and marginalize across this lattice to calculate sequence probabilities or optimize parameters. This approach allows us to seamlessly incorporate linguistic intuitions — including polysemy and the existence of multiword lexical… CONTINUE READING
Topics from this paper
14 Citations
Learning Spoken Language Representations with Neural Lattice Language Modeling
- Computer Science
- ACL
- 2020
- 1
- PDF
Lattice LSTM for Chinese Sentence Representation
- Computer Science
- IEEE/ACM Transactions on Audio, Speech, and Language Processing
- 2020
- PDF
Neural Lattice Search for Speech Recognition
- Computer Science
- ICASSP 2020 - 2020 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP)
- 2020
- 1
Incorporating Task-specific Features into Deep Models to Classify Argument Components
- Computer Science
- EDM
- 2020
- PDF
ELMoLex: Connecting ELMo and Lexicon Features for Dependency Parsing
- Computer Science
- CoNLL Shared Task
- 2018
- 6
- PDF
References
SHOWING 1-10 OF 42 REFERENCES
Tying Word Vectors and Word Classifiers: A Loss Framework for Language Modeling
- Computer Science, Mathematics
- ICLR
- 2017
- 281
- Highly Influential
- PDF
One billion word benchmark for measuring progress in statistical language modeling
- Computer Science
- INTERSPEECH
- 2014
- 735
- PDF
Improved Semantic Representations From Tree-Structured Long Short-Term Memory Networks
- Computer Science
- ACL
- 2015
- 2,024
- PDF