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Found 31 papers, 10 papers with code
Overview of the IWSLT 2017 Evaluation Campaign
The IWSLT 2017 evaluation campaign has organised three tasks.
The IWSLT 2016 Evaluation Campaign
The IWSLT 2016 Evaluation Campaign featured two tasks: the translation of talks and the translation of video conference conversations.
Automatic Speech Recognition
Automatic Speech Recognition (ASR)
+3
Post-editing in Automatic Subtitling: A Subtitlers’ perspective
Subtitling tools are recently being adapted for post-editing by providing automatically generated subtitles, and featuring not only machine translation, but also automatic segmentation and synchronisation.
The IWSLT 2018 Evaluation Campaign
The International Workshop of Spoken Language Translation (IWSLT) 2018 Evaluation Campaign featured two tasks: low-resource machine translation and speech translation.
Extending the MuST-C Corpus for a Comparative Evaluation of Speech Translation Technology
This project aimed at extending the test sets of the MuST-C speech translation (ST) corpus with new reference translations.
Towards a methodology for evaluating automatic subtitling
In response to the increasing interest towards automatic subtitling, this EAMT-funded project aimed at collecting subtitle post-editing data in a real use case scenario where professional subtitlers edit automatically generated subtitles.
Machine Translation Human Evaluation: an investigation of evaluation based on Post-Editing and its relation with Direct Assessment
In this paper we present an analysis of the two most prominent methodologies used for the human evaluation of MT quality, namely evaluation based on Post-Editing (PE) and evaluation based on Direct Assessment (DA).
Findings of the IWSLT 2024 Evaluation Campaign
This paper reports on the shared tasks organized by the 21st IWSLT Conference.
SPES: Spectrogram Perturbation for Explainable Speech-to-Text Generation
Spurred by the demand for interpretable models, research on eXplainable AI for language technologies has experienced significant growth, with feature attribution methods emerging as a cornerstone of this progress.
MOSEL: 950,000 Hours of Speech Data for Open-Source Speech Foundation Model Training on EU Languages
The rise of foundation models (FMs), coupled with regulatory efforts addressing their risks and impacts, has sparked significant interest in open-source models.
SBAAM! Eliminating Transcript Dependency in Automatic Subtitling
Subtitling plays a crucial role in enhancing the accessibility of audiovisual content and encompasses three primary subtasks: translating spoken dialogue, segmenting translations into concise textual units, and estimating timestamps that govern their on-screen duration.
Integrating Language Models into Direct Speech Translation: An Inference-Time Solution to Control Gender Inflection
When translating words referring to the speaker, speech translation (ST) systems should not resort to default masculine generics nor rely on potentially misleading vocal traits.
No Pitch Left Behind: Addressing Gender Unbalance in Automatic Speech Recognition through Pitch Manipulation
Automatic speech recognition (ASR) systems are known to be sensitive to the sociolinguistic variability of speech data, in which gender plays a crucial role.
Automatic Speech Recognition
Automatic Speech Recognition (ASR)
+2
Direct Speech Translation for Automatic Subtitling
Automatic subtitling is the task of automatically translating the speech of audiovisual content into short pieces of timed text, i. e. subtitles and their corresponding timestamps.
Evaluating Subtitle Segmentation for End-to-end Generation Systems
Subtitle segmentation can be evaluated with sequence segmentation metrics against a human reference.
Cascade versus Direct Speech Translation: Do the Differences Still Make a Difference?
Five years after the first published proofs of concept, direct approaches to speech translation (ST) are now competing with traditional cascade solutions.
Beyond Voice Activity Detection: Hybrid Audio Segmentation for Direct Speech Translation
The audio segmentation mismatch between training data and those seen at run-time is a major problem in direct speech translation.
CTC-based Compression for Direct Speech Translation
Previous studies demonstrated that a dynamic phone-informed compression of the input audio is beneficial for speech translation (ST).
Contextualized Translation of Automatically Segmented Speech
We show that our context-aware solution is more robust to VAD-segmented input, outperforming a strong base model and the fine-tuning on different VAD segmentations of an English-German test set by up to 4. 25 BLEU points.
Findings of the 2016 WMT Shared Task on Cross-lingual Pronoun Prediction
We describe the design, the evaluation setup, and the results of the 2016 WMT shared task on cross-lingual pronoun prediction.
A Comparison of Transformer and Recurrent Neural Networks on Multilingual Neural Machine Translation
Motivated by this, our work (i) provides a quantitative and comparative analysis of the translations produced by bilingual, multilingual and zero-shot systems; (ii) investigates the translation quality of two of the currently dominant neural architectures in MT, which are the Recurrent and the Transformer ones; and (iii) quantitatively explores how the closeness between languages influences the zero-shot translation.
Findings of the 2017 DiscoMT Shared Task on Cross-lingual Pronoun Prediction
We describe the design, the setup, and the evaluation results of the DiscoMT 2017 shared task on cross-lingual pronoun prediction.
Unsupervised Clustering of Commercial Domains for Adaptive Machine Translation
In this paper, we report on domain clustering in the ambit of an adaptive MT architecture.
An Arabic-Hebrew parallel corpus of TED talks
We describe an Arabic-Hebrew parallel corpus of TED talks built upon WIT3, the Web inventory that repurposes the original content of the TED website in a way which is more convenient for MT researchers.
Neural versus Phrase-Based Machine Translation Quality: a Case Study
Within the field of Statistical Machine Translation (SMT), the neural approach (NMT) has recently emerged as the first technology able to challenge the long-standing dominance of phrase-based approaches (PBMT).
WAGS: A Beautiful English-Italian Benchmark Supporting Word Alignment Evaluation on Rare Words
This paper presents WAGS (Word Alignment Gold Standard), a novel benchmark which allows extensive evaluation of WA tools on out-of-vocabulary (OOV) and rare words.
The IWSLT 2011 Evaluation Campaign on Automatic Talk Translation
We report here on the eighth evaluation campaign organized in 2011 by the IWSLT workshop series.
