Corpora

MCIF

by Sara Papi | Apr 17, 2026 | Corpora | 0

MCIF (Multimodal Crosslingual Instruction Following) is a multilingual human-annotated benchmark based on scientific talks that is designed to evaluate instruction-following in crosslingual, multimodal settings over both short-...

mGeNTE

by Beatrice Savoldi | Jan 13, 2025 | Corpora | 0

mGeNTE (Multilingual Gender-Neutral Translation Evaluation) is a natural, multilingual corpus designed to benchmark gender-neutral language and automatic translation.mGente is built upon European Parliament speech data extracted...

MOSEL

by Sara Papi | Oct 31, 2024 | Corpora | 0

The MOSEL corpus is a multilingual dataset collection including up to 950K hours of open-source speech recordings covering the 24 official languages of the European Union. We collect data by surveying labeled and unlabeled...

Speech-MASSIVE

by Beomseok Lee | Aug 21, 2024 | Corpora | 0

Spoken Language Understanding (SLU) involves interpreting spoken input using Natural Language Processing (NLP). Voice assistants like Alexa and Siri are real-world examples of SLU applications. The core tasks in SLU include...

WAGS

by Mauro Cettolo | Apr 30, 2024 | Corpora | 0

Ready-to-use version for MT research purposes of the multilingual transcriptions of TED talks

GenderCrawl

by Dennis Fucci | Oct 20, 2023 | Corpora | 0

Text corpora for Spanish, French, and Italian containing gendered words referring to the first-person speaker

INES

by Beatrice Savoldi | Oct 19, 2023 | Corpora | 0

The INclusive Evaluation Suite (INES) is a test set designed to assess MT systems ability to produce gender-inclusive translations for the German→English language pair. By design, each German source sentence in INES includes an...

GeNTE

by Beatrice Savoldi | Oct 9, 2023 | Corpora | 0

GeNTE (Gender-Neutral Translation Evaluation) is a natural, bilingual corpus designed to benchmark the ability of machine translation systems to generate gender-neutral translations. Built from European Parliament speeches,...

EC Short Clips

by Marco Gaido | Jul 7, 2023 | Corpora | 0

EC Short Clips is a test set dedicated to evaluate automatic subtitling systems.

EuroParl Interviews

by Marco Gaido | Jul 7, 2023 | Corpora | 0

EuroParl Interviews is a test set dedicated to evaluate automatic subtitling systems.

NEuRoparl-ST

by Matteo Negri | Jun 1, 2023 | Corpora | 0

Multilingual benchmark built from European Parliament speeches and annotated with Named Entities and Terminology

Heroes-ON-OFF

by Mauro Cettolo | May 30, 2023 | Corpora | 0

Annotation of dubbing segments based on the Heroes corpus

MT Group at FBK Follow

#MachineTranslation Research Unit @FBK_research. #nlproc #deeplearning #ai

Avatar MT Group at FBK @fbk_mt ·

15 May

🏝️ Yesterday at #LREC2026, Palma de Mallorca!
@lina_conti presented "Voice, Bias, and Coreference: An Interpretability Study of Gender in Speech Translation" at the poster session.
📄Paper:
💻Code: https://github.com/lina-conti/voice-bias-coreference
#SpeechTranslation #NLProc

Reply on Twitter 2055326042957713546 Retweet on Twitter 2055326042957713546 Like on Twitter 2055326042957713546 5 Twitter 2055326042957713546

Avatar MT Group at FBK @fbk_mt ·

13 May

How does the granularity of speech-text pairs impact SpeechLLM performance, and what is the optimal way to interleave tokens? Furthermore, what are the best practices for generating synthetic data to boost training?🧐

Reply on Twitter 2054503147721097286 Retweet on Twitter 2054503147721097286 Like on Twitter 2054503147721097286 3 Twitter 2054503147721097286

Retweet on Twitter MT Group at FBK Retweeted

Avatar fbk_stek @fbk_stek ·

8 May

Reply on Twitter 2052822167511826811 Retweet on Twitter 2052822167511826811 2 Like on Twitter 2052822167511826811 3 Twitter 2052822167511826811

Retweet on Twitter MT Group at FBK Retweeted

Avatar Meetween @meetweeneu ·

26 Mar

🎙️ Our paper on connecting Speech Foundation Models with LLMs is featured in the SpeechLMM Training Journal on Weights & Biases.

Read it 👉 https://bit.ly/4svG7ll

SpeechLMM 2.0 coming this summer. 👀

#Meetween #SpeechLMM #AI #NLP

Reply on Twitter 2037102183120879826 Retweet on Twitter 2037102183120879826 1 Like on Twitter 2037102183120879826 3 Twitter 2037102183120879826