Real-Time Speech-to-Speech Translation for PDAs

Prasad, Rohit; Krstovski, Kriste; Choi, Fred; Saleem, Shirin; Natarajan, Prem; Decerbo, M.; Stallard, David

doi:10.1109/portable.2007.23

Cited by 4 publications

(2 citation statements)

References 12 publications

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“…Although entropy-pruned language models have been used to produce real-time translation systems (Prasad et al 2007), we believe our use of entropy-pruned language models in two-pass translation to be novel. This is an approach that is widely used in automatic speech recognition (Ljolje, Pereira, and Riley 1999) and we note that it relies on efficient representation of very large search spaces T for subsequent rescoring, as is possible with FSAs and PDAs.…”

Section: Related Workmentioning

confidence: 99%

Pushdown Automata in Statistical Machine Translation

Allauzen

Byrne

Gispert

et al. 2014

Computational Linguistics

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This article describes the use of pushdown automata (PDA) in the context of statistical machine translation and alignment under a synchronous context-free grammar. We use PDAs to compactly represent the space of candidate translations generated by the grammar when applied to an input sentence. General-purpose PDA algorithms for replacement, composition, shortest path, and expansion are presented. We describe HiPDT, a hierarchical phrase-based decoder using the PDA representation and these algorithms. We contrast the complexity of this decoder with a decoder based on a finite state automata representation, showing that PDAs provide a more suitable framework to achieve exact decoding for larger synchronous context-free grammars and smaller language models. We assess this experimentally on a large-scale Chinese-to-English alignment and translation task. In translation, we propose a two-pass decoding strategy involving a weaker language model in the first-pass to address the results of PDA complexity analysis. We study in depth the experimental conditions and tradeoffs in which HiPDT can achieve state-of-the-art performance for large-scale SMT.

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Section: Related Workmentioning

confidence: 99%

Pushdown Automata in Statistical Machine Translation

Allauzen

Byrne

Gispert

et al. 2014

Computational Linguistics

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“…For an example of a mobile application that could benefit from cyber foraging see e.g., [8], or consider the following use-case:…”

Section: Introductionmentioning

confidence: 99%

Developing cyber foraging applications for portable devices

Kristensen

Bouvin

2008

PORTABLE-POLYTRONIC 2008 - 2nd IEEE International Interdisciplinary Conference on Portable Information Devices and the 2008 7th

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This paper presents the Locusts cyber foraging framework. Cyber foraging is the opportunistic use of computing resources available in the nearby environment, and using such resources thus fall into the category of distributed computing. Furthermore, for the resources to be used efficiently, parallel computing techniques must also be employed. Distributed and parallel computing are two concepts that are both notoriously known for being very hard for developers to grasp. Because of this one might think that techniques such as cyber foraging would have a hard time surviving outside of research environments. In this paper a framework is presented that has special focus on making cyber foraging accessible for all developers.

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