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- Johan Schalkwyk, Doug Beeferman, +5 authors Brian Strope
- 2010

Using our voice to access information has been part of science fiction ever since the days of Captain Kirk talking to the Star Trek computer. Today, with powerful smartphones and cloud based computing, science fiction is becoming reality. In this chapter we give an overview of Google Search by Voice and our efforts to make speech input on mobile devices… (More)

- M. Ostendorf, B. Byrne, +9 authors T. Zeppenfeld
- 1996

This paper describes the research efforts of the “Hidden Speaking Mode” group participating in the 1996 summer workshop on speech recognition. The goal of this project is to model pronunciation variations that occur in conversational speech in general and, more specifically, to investigate the use of a hidden speaking mode to represent systematic variations… (More)

- Laura Jehl, Adrià de Gispert, Mark Hopkins, Bill Byrne
- EACL
- 2014

We present a simple preordering approach for machine translation based on a featurerich logistic regression model to predict whether two children of the same node in the source-side parse tree should be swapped or not. Given the pair-wise children regression scores we conduct an efficient depth-first branch-and-bound search through the space of possible… (More)

- B. Byrne, M. Finke, S. Khudanpur
- 1997

Accurately modelling pronunciation variability in conversational speech is an important component for automatic speech recognition. We describe some of the projects undertaken in this direction at WS97, the Fifth LVCSR Summer Workshop, held at Johns Hopkins University, Baltimore, in July-August, 1997. We first illustrate a use of hand-labelled phonetic… (More)

- Adrià de Gispert, Gonzalo Iglesias, Bill Byrne
- HLT-NAACL
- 2015

We propose the use of neural networks to model source-side preordering for faster and better statistical machine translation. The neural network trains a logistic regression model to predict whether two sibling nodes of the source-side parse tree should be swapped in order to obtain a more monotonic parallel corpus, based on samples extracted from the… (More)

- M. Ostendorf, B. Byrne, +9 authors T. Zeppenfeld
- 1996

This paper describes the research efforts of the “Hidden Speaking Mode” group participating in the 1996 summer workshop on speech recognition. The goal of this project is to model pronunciation variations that occur in conversational speech in general and, more specifically, to investigate the use of a hidden speaking mode to represent systematic variations… (More)

- Adrià de Gispert, Marcus Tomalin, Bill Byrne
- EACL
- 2014

We describe an approach to word ordering using modelling techniques from statistical machine translation. The system incorporates a phrase-based model of string generation that aims to take unordered bags of words and produce fluent, grammatical sentences. We describe the generation grammars and introduce parsing procedures that address the computational… (More)

- Adrià de Gispert, Bill Byrne, Eva Hasler, Felix Stahlberg
- EACL
- 2017

We present a novel scheme to combine neural machine translation (NMT) with traditional statistical machine translation (SMT). Our approach borrows ideas from linearised lattice minimum Bayes-risk decoding for SMT. The NMT score is combined with the Bayes-risk of the translation according the SMT lattice. This makes our approach much more flexible than… (More)

- Matic Horvat, Ann A. Copestake, Bill Byrne
- IWCS
- 2015

We introduce a robust statistical approach to realization from Minimal Recursion Semantics representations. The approach treats realization as a translation problem, transforming the Dependency MRS graph representation to a surface string. Translation is based on a Synchronous Context-Free Grammar that is automatically extracted from a large corpus of… (More)

- Aurelien Waite, Bill Byrne
- HLT-NAACL
- 2015

Most modern statistical machine translation systems are based on the linear model. There are many reasons for the prevalence of the linear model: other component models can be incorporated as features, there are many methods for estimating their parameters, and the resulting model scores can be easily used in finite-state representations. One popular method… (More)