papers

Publications (30)

cs.CL2019

Tagged Back-Translation

Isaac Caswell, Ciprian Chelba, David Grangier

Recent work in Neural Machine Translation (NMT) has shown significant quality gains from noised-beam decoding during back-translation, a method to generate synthetic parallel data.…

cs.CL2001

Portability of Syntactic Structure for Language Modeling

Ciprian Chelba

The paper presents a study on the portability of statistical syntactic knowledge in the framework of the structured language model (SLM). We investigate the impact of porting SLM s…

cs.CL2012

Large Scale Language Modeling in Automatic Speech Recognition

Ciprian Chelba, Dan Bikel, Maria Shugrina +2

Large language models have been proven quite beneficial for a variety of automatic speech recognition tasks in Google. We summarize results on Voice Search and a few YouTube speech…

cs.CL2016

Multinomial Loss on Held-out Data for the Sparse Non-negative Matrix Language Model

Ciprian Chelba, Fernando Pereira

We describe Sparse Non-negative Matrix (SNM) language model estimation using multinomial loss on held-out data. Being able to train on held-out data is important in practical situa…

cs.CL2014

One Billion Word Benchmark for Measuring Progress in Statistical Language Modeling

Ciprian Chelba, Tomas Mikolov, Mike Schuster +4

We propose a new benchmark corpus to be used for measuring progress in statistical language modeling. With almost one billion words of training data, we hope this benchmark will be…

cs.CL2000

Exploiting Syntactic Structure for Natural Language Modeling

Ciprian Chelba

The thesis presents an attempt at using the syntactic structure in natural language for improved language models for speech recognition. The structured language model merges techni…