Search Results for author:
Found 39 papers, 9 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.
Findings of the IWSLT 2022 Evaluation Campaign
The evaluation campaign of the 19th International Conference on Spoken Language Translation featured eight shared tasks: (i) Simultaneous speech translation, (ii) Offline speech translation, (iii) Speech to speech translation, (iv) Low-resource speech translation, (v) Multilingual speech translation, (vi) Dialect speech translation, (vii) Formality control for speech translation, (viii) Isometric speech translation.
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.
FINDINGS OF THE IWSLT 2021 EVALUATION CAMPAIGN
The evaluation campaign of the International Conference on Spoken Language Translation (IWSLT 2021) featured this year four shared tasks: (i) Simultaneous speech translation, (ii) Offline speech translation, (iii) Multilingual speech translation, (iv) Low-resource speech translation.
The MITLL-AFRL IWSLT 2016 Systems
This report summarizes the MITLL-AFRL MT and ASR systems and the experiments run during the 2016 IWSLT evaluation campaign.
A surprisal–duration trade-off across and within the world’s languages
We thus conclude that there is strong evidence of a surprisal–duration trade-off in operation, both across and within the world’s languages.
Text Rendering Strategies for Pixel Language Models
Pixel-based language models process text rendered as images, which allows them to handle any script, making them a promising approach to open vocabulary language modelling.
Multilingual Pixel Representations for Translation and Effective Cross-lingual Transfer
We introduce and demonstrate how to effectively train multilingual machine translation models with pixel representations.
A Holistic Cascade System, benchmark, and Human Evaluation Protocol for Expressive Speech-to-Speech Translation
Expressive speech-to-speech translation (S2ST) aims to transfer prosodic attributes of source speech to target speech while maintaining translation accuracy.
BLOOM: A 176B-Parameter Open-Access Multilingual Language Model
Large language models (LLMs) have been shown to be able to perform new tasks based on a few demonstrations or natural language instructions.
Language Modelling with Pixels
We pretrain the 86M parameter PIXEL model on the same English data as BERT and evaluate on syntactic and semantic tasks in typologically diverse languages, including various non-Latin scripts.
Ranked #1 on
Named Entity Recognition (NER)
on MasakhaNER
BibleTTS: a large, high-fidelity, multilingual, and uniquely African speech corpus
BibleTTS is a large, high-quality, open speech dataset for ten languages spoken in Sub-Saharan Africa.
UniMorph 4.0: Universal Morphology
The project comprises two major thrusts: a language-independent feature schema for rich morphological annotation and a type-level resource of annotated data in diverse languages realizing that schema.
Between words and characters: A Brief History of Open-Vocabulary Modeling and Tokenization in NLP
What are the units of text that we want to model?
Assessing Evaluation Metrics for Speech-to-Speech Translation
Speech-to-speech translation combines machine translation with speech synthesis, introducing evaluation challenges not present in either task alone.
A surprisal--duration trade-off across and within the world's languages
We thus conclude that there is strong evidence of a surprisal--duration trade-off in operation, both across and within the world's languages.
SIGTYP 2021 Shared Task: Robust Spoken Language Identification
While language identification is a fundamental speech and language processing task, for many languages and language families it remains a challenging task.
Robust Open-Vocabulary Translation from Visual Text Representations
Machine translation models have discrete vocabularies and commonly use subword segmentation techniques to achieve an 'open vocabulary.'
Tutorial Proposal: End-to-End Speech Translation
Speech translation is the translation of speech in one language typically to text in another, traditionally accomplished through a combination of automatic speech recognition and machine translation.
Automatic Speech Recognition
Automatic Speech Recognition (ASR)
+3
The Multilingual TEDx Corpus for Speech Recognition and Translation
We present the Multilingual TEDx corpus, built to support speech recognition (ASR) and speech translation (ST) research across many non-English source languages.
SIGTYP 2020 Shared Task: Prediction of Typological Features
Typological knowledge bases (KBs) such as WALS (Dryer and Haspelmath, 2013) contain information about linguistic properties of the world's languages.
FINDINGS OF THE IWSLT 2020 EVALUATION CAMPAIGN
The evaluation campaign of the International Conference on Spoken Language Translation (IWSLT 2020) featured this year six challenge tracks: (i) Simultaneous speech translation, (ii) Video speech translation, (iii) Offline speech translation, (iv) Conversational speech translation, (v) Open domain translation, and (vi) Non-native speech translation.
SIGMORPHON 2020 Shared Task 0: Typologically Diverse Morphological Inflection
Systems were developed using data from 45 languages and just 5 language families, fine-tuned with data from an additional 45 languages and 10 language families (13 in total), and evaluated on all 90 languages.
A Corpus for Large-Scale Phonetic Typology
A major hurdle in data-driven research on typology is having sufficient data in many languages to draw meaningful conclusions.
Phone Features Improve Speech Translation
End-to-end models for speech translation (ST) more tightly couple speech recognition (ASR) and machine translation (MT) than a traditional cascade of separate ASR and MT models, with simpler model architectures and the potential for reduced error propagation.
Generalized Entropy Regularization or: There's Nothing Special about Label Smoothing
Prior work has explored directly regularizing the output distributions of probabilistic models to alleviate peaky (i. e. over-confident) predictions, a common sign of overfitting.
CMU-01 at the SIGMORPHON 2019 Shared Task on Crosslinguality and Context in Morphology
This paper presents the submission by the CMU-01 team to the SIGMORPHON 2019 task 2 of Morphological Analysis and Lemmatization in Context.
Exploring Phoneme-Level Speech Representations for End-to-End Speech Translation
Previous work on end-to-end translation from speech has primarily used frame-level features as speech representations, which creates longer, sparser sequences than text.
Fluent Translations from Disfluent Speech in End-to-End Speech Translation
Spoken language translation applications for speech suffer due to conversational speech phenomena, particularly the presence of disfluencies.
Towards Fluent Translations from Disfluent Speech
We introduce a corpus of cleaned target data for the Fisher Spanish-English dataset for this task.
Optimizing Segmentation Granularity for Neural Machine Translation
However, the granularity of these subword units is a hyperparameter to be tuned for each language and task, using methods such as grid search.
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.
Operational Assessment of Keyword Search on Oral History
This project assesses the resources necessary to make oral history searchable by means of automatic speech recognition (ASR).
Automatic Speech Recognition
Automatic Speech Recognition (ASR)
+3
