92 citations · 301 across the 26 of their papers we have counts for
8 papers · 1 filter
Adapting Multilingual Neural Machine Translation to Unseen Languages
Surafel M. Lakew, Alina Karakanta, Marcello Federico +2
Multilingual Neural Machine Translation (MNMT) for low-resource languages (LRL) can be enhanced by the presence of related high-resource languages (HRL), but the relatedness of HRL…
Controlling the Output Length of Neural Machine Translation
Surafel Melaku Lakew, Mattia Di Gangi, Marcello Federico
The recent advances introduced by neural machine translation (NMT) are rapidly expanding the application fields of machine translation, as well as reshaping the quality level to be…
Robust Neural Machine Translation for Clean and Noisy Speech Transcripts
Mattia Antonino Di Gangi, Robert Enyedi, Alessandra Brusadin +1
Neural machine translation models have shown to achieve high quality when trained and fed with well structured and punctuated input texts. Unfortunately, the latter condition is no…
On the Importance of Word Boundaries in Character-level Neural Machine Translation
Duygu Ataman, Orhan Firat, Mattia A. Di Gangi +2
Neural Machine Translation (NMT) models generally perform translation using a fixed-size lexical vocabulary, which is an important bottleneck on their generalization capability and…
Multilingual Neural Machine Translation for Zero-Resource Languages
Surafel M. Lakew, Marcello Federico, Matteo Negri +1
In recent years, Neural Machine Translation (NMT) has been shown to be more effective than phrase-based statistical methods, thus quickly becoming the state of the art in machine t…
Training Neural Machine Translation To Apply Terminology Constraints
Georgiana Dinu, Prashant Mathur, Marcello Federico +1
This paper proposes a novel method to inject custom terminology into neural machine translation at run time. Previous works have mainly proposed modifications to the decoding algor…
Phonetically-Oriented Word Error Alignment for Speech Recognition Error Analysis in Speech Translation
Nicholas Ruiz, Marcello Federico
We propose a variation to the commonly used Word Error Rate (WER) metric for speech recognition evaluation which incorporates the alignment of phonemes, in the absence of time boun…
Assessing the Tolerance of Neural Machine Translation Systems Against Speech Recognition Errors
Nicholas Ruiz, Mattia Antonino Di Gangi, Nicola Bertoldi +1
Machine translation systems are conventionally trained on textual resources that do not model phenomena that occur in spoken language. While the evaluation of neural machine transl…