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Found 36 papers, 4 papers with code
KIT’s Multilingual Neural Machine Translation systems for IWSLT 2017
For the SLT track, in addition to a monolingual neural translation system used to generate correct punctuations and true cases of the data prior to training our multilingual system, we introduced a noise model in order to make our system more robust.
Adaptation and Combination of NMT Systems: The KIT Translation Systems for IWSLT 2016
In addition, we investigated methods to combine NMT systems that encode the input as well as the output differently.
Multilingual Disfluency Removal using NMT
In this paper, we investigate a multilingual approach for speech disfluency removal.
KIT’s IWSLT 2018 SLT Translation System
The baseline system is a cascade of an ASR system, a system to segment the ASR output and a neural machine translation system.
The IWSLT 2019 KIT Speech Translation System
This paper describes KIT’s submission to the IWSLT 2019 Speech Translation task on two sub-tasks corresponding to two different datasets.
The IWSLT 2019 Evaluation Campaign
The IWSLT 2019 evaluation campaign featured three tasks: speech translation of (i) TED talks and (ii) How2 instructional videos from English into German and Portuguese, and (iii) text translation of TED talks from English into Czech.
Multilingual Speech Translation KIT @ IWSLT2021
This paper contains the description for the submission of Karlsruhe Institute of Technology (KIT) for the multilingual TEDx translation task in the IWSLT 2021 evaluation campaign.
KIT’s IWSLT 2021 Offline Speech Translation System
We describe a system in both cascaded condition and end-to-end condition.
Incorporating External Annotation to improve Named Entity Translation in NMT
The correct translation of named entities (NEs) still poses a challenge for conventional neural machine translation (NMT) systems.
Improving Multilingual Neural Machine Translation For Low-Resource Languages: French, English - Vietnamese
Prior works have demonstrated that a low-resource language pair can benefit from multilingual machine translation (MT) systems, which rely on many language pairs’ joint training.
Improving Multilingual Neural Machine Translation For Low-Resource Languages: French,English - Vietnamese
Prior works have demonstrated that a low-resource language pair can benefit from multilingual machine translation (MT) systems, which rely on many language pairs' joint training.
KIT's IWSLT 2020 SLT Translation System
This paper describes KIT{'}s submissions to the IWSLT2020 Speech Translation evaluation campaign.
Relative Positional Encoding for Speech Recognition and Direct Translation
We also show that this model is able to better utilize synthetic data than the Transformer, and adapts better to variable sentence segmentation quality for speech translation.
Removing European Language Barriers with Innovative Machine Translation Technology
This paper presents our progress towards deploying a versatile communication platform in the task of highly multilingual live speech translation for conferences and remote meetings live subtitling.
Low Latency ASR for Simultaneous Speech Translation
User studies have shown that reducing the latency of our simultaneous lecture translation system should be the most important goal.
Automatic Speech Recognition
Automatic Speech Recognition (ASR)
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Overcoming the Rare Word Problem for Low-Resource Language Pairs in Neural Machine Translation
Among the six challenges of neural machine translation (NMT) coined by (Koehn and Knowles, 2017), rare-word problem is considered the most severe one, especially in translation of low-resource languages.
How Transformer Revitalizes Character-based Neural Machine Translation: An Investigation on Japanese-Vietnamese Translation Systems
While translating between East Asian languages, many works have discovered clear advantages of using characters as the translation unit.
Improving Zero-shot Translation with Language-Independent Constraints
We investigated the behaviour of such models on the standard IWSLT 2017 multilingual dataset.
KIT Lecture Translator: Multilingual Speech Translation with One-Shot Learning
{\%} Combining these techniques, we are able to provide an adapted speech translation system for several European languages.
Low-Latency Neural Speech Translation
After adaptation, we are able to reduce the number of corrections displayed during incremental output construction by 45%, without a decrease in translation quality.
Combining Advanced Methods in Japanese-Vietnamese Neural Machine Translation
Neural machine translation (NMT) systems have recently obtained state-of-the art in many machine translation systems between popular language pairs because of the availability of data.
Effective Strategies in Zero-Shot Neural Machine Translation
In this paper, we proposed two strategies which can be applied to a multilingual neural machine translation system in order to better tackle zero-shot scenarios despite not having any parallel corpus.
Analyzing Neural MT Search and Model Performance
By separating the search space and the modeling using $n$-best list reranking, we analyze the influence of both parts of an NMT system independently.
Toward Multilingual Neural Machine Translation with Universal Encoder and Decoder
In this paper, we present our first attempts in building a multilingual Neural Machine Translation framework under a unified approach.
Pre-Translation for Neural Machine Translation
We analyzed the influence of the quality of the initial system on the final result.
Lexical Translation Model Using a Deep Neural Network Architecture
In this paper we combine the advantages of a model using global source sentence contexts, the Discriminative Word Lexicon, and neural networks.
