553 research outputs found
Asymptotic Capacity of Large Relay Networks with Conferencing Links
In this correspondence, we consider a half-duplex large relay network, which
consists of one source-destination pair and relay nodes, each of which is
connected with a subset of the other relays via signal-to-noise ratio
(SNR)-limited out-of-band conferencing links. The asymptotic achievable rates
of two basic relaying schemes with the "-portion" conferencing strategy are
studied: For the decode-and-forward (DF) scheme, we prove that the DF rate
scales as ; for the amplify-and-forward (AF) scheme, we
prove that it asymptotically achieves the capacity upper bound in some
interesting scenarios as goes to infinity.Comment: submitted to IEEE Transactions on Communication
Incorporating source-language paraphrases into phrase-based SMT with confusion networks
To increase the model coverage, sourcelanguage paraphrases have been utilized to boost SMT system performance. Previous
work showed that word lattices constructed from paraphrases are able to reduce out-ofvocabulary words and to express inputs in different ways for better translation quality.
However, such a word-lattice-based method suffers from two problems: 1) path duplications in word lattices decrease the capacities for potential paraphrases; 2) lattice decoding in SMT dramatically increases the search space and results in poor time efļ¬ciency. Therefore, in this paper, we adopt word confusion networks as the input structure to carry source-language paraphrase information. Similar to previous work, we use word lattices to build word confusion networks for merging of duplicated paths and faster decoding. Experiments are carried out on small-, medium- and large-scale Englishā
Chinese translation tasks, and we show that compared with the word-lattice-based method, the decoding time on three tasks is reduced signiļ¬cantly (up to 79%) while comparable
translation quality is obtained on the largescale task
Asymptotic Capacity of Large Fading Relay Networks with Random Node Failures
To understand the network response to large-scale physical attacks, we
investigate the asymptotic capacity of a half-duplex fading relay network with
random node failures when the number of relays is infinitely large. In this
paper, a simplified independent attack model is assumed where each relay node
fails with a certain probability. The noncoherent relaying scheme is
considered, which corresponds to the case of zero forward-link channel state
information (CSI) at the relays. Accordingly, the whole relay network can be
shown equivalent to a Rayleigh fading channel, where we derive the
-outage capacity upper bound according to the multiple access (MAC)
cut-set, and the -outage achievable rates for both the
amplify-and-forward (AF) and decode-and-forward (DF) strategies. Furthermore,
we show that the DF strategy is asymptotically optimal as the outage
probability goes to zero, with the AF strategy strictly suboptimal
over all signal to noise ratio (SNR) regimes. Regarding the rate loss due to
random attacks, the AF strategy suffers a less portion of rate loss than the DF
strategy in the high SNR regime, while the DF strategy demonstrates more robust
performance in the low SNR regime.Comment: 24 pages, 5 figures, submitted to IEEE Transactions on Communication
Facilitating translation using source language paraphrase lattices
For resource-limited language pairs, coverage of the test set by the parallel corpus is an important factor that affects translation quality in two respects: 1) out of vocabulary words; 2) the same information in an input
sentence can be expressed in different ways, while current phrase-based SMT systems cannot automatically select an alternative way to transfer the same information. Therefore,
given limited data, in order to facilitate translation
from the input side, this paper proposes a novel method to reduce the translation difficulty using source-side lattice-based paraphrases. We utilise the original phrases from the input sentence and the corresponding paraphrases to build a lattice with estimated weights for each edge to improve translation quality. Compared to the baseline system, our method achieves relative improvements of 7.07%, 6.78% and 3.63% in terms of BLEU score on small, medium and largescale
English-to-Chinese translation tasks respectively. The results show that the proposed method is effective not only for resourcelimited language pairs, but also for resource sufficient pairs to some extent
Improved phrase-based SMT with syntactic reordering patterns learned from lattice scoring
In this paper, we present a novel approach to incorporate source-side syntactic reordering patterns into phrase-based SMT. The main contribution of this work is to use the lattice scoring approach to exploit and utilize reordering
information that is favoured by the baseline PBSMT system. By referring to the parse trees of the training corpus, we represent the observed reorderings with source-side
syntactic patterns. The extracted patterns are then used to convert the parsed inputs into word lattices, which contain both the original source sentences and their potential reorderings. Weights of the word lattices are estimated from the observations of the syntactic reordering patterns in the training corpus. Finally, the PBSMT system is tuned
and tested on the generated word lattices to show the benefits of adding potential sourceside reorderings in the inputs. We confirmed the effectiveness of our proposed method on a medium-sized corpus for Chinese-English
machine translation task. Our method outperformed the baseline system by 1.67% relative on a randomly selected testset and 8.56% relative on the NIST 2008 testset in terms of BLEU score
Source-side syntactic reordering patterns with functional words for improved phrase-based SMT
Inspired by previous source-side syntactic reordering methods for SMT, this paper focuses on using automatically learned syntactic reordering patterns with functional words which indicate structural reorderings between the source and target language. This approach takes advantage of phrase alignments and source-side parse trees for pattern extraction, and then filters out those patterns without functional words. Word lattices transformed by the generated patterns are fed into PBSMT systems to incorporate potential reorderings from the inputs. Experiments are carried out on a medium-sized corpus for a ChineseāEnglish SMT task. The proposed method outperforms the baseline system by 1.38% relative on a randomly selected testset and 10.45% relative on the NIST 2008 testset in terms of BLEU score. Furthermore, a system with just 61.88% of the patterns filtered by functional words obtains a comparable performance with the unfiltered one on the randomly selected testset, and achieves 1.74% relative improvements on the NIST 2008 testset
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