Corpora

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 | 1

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

TOSCA-MP SPEECH GROUND TRUTH

by Beatrice Savoldi | May 30, 2023 | Corpora | 0

This multilingual dataset was created within the TOSCA-MP project as ground truth data for the evaluation of automatic transcription and spoken language translation technologies.

MT Group at FBK Follow

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

Avatar MT Group at FBK @fbk_mt ·

19 Jun

Our pick of the week by @DennisFucci: "Speech Representation Analysis Based on Inter- and Intra-Model Similarities" by Yassine El Kheir, Ahmed Ali, and Shammur Absar Chowdhury (ICASSP Workshops 2024)

#speech #speechtech

Dennis Fucci @DennisFucci

Findings from https://ieeexplore.ieee.org/document/10669908 show that speech SSL models converge on similar embedding spaces, but via different routes. While overall representations align, individual neurons learn distinct localized concepts.
Interesting read! @fbk_mt

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Avatar Fondazione Bruno Kessler - FBK @fbk_research ·

10 Jun

Cosa chiedono davvero gli italiani all’intelligenza artificiale?
FBK in collaborazione con RiTA lancia un’indagine aperta a tutte/i per capire usi reali, abitudini e bisogni.

Bastano 10 minuti per partecipare, scopri di più: https://magazine.fbk.eu/it/news/italiani-e-ia-cosa-chiediamo-veramente-allintelligenza-artificiale/

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Avatar Marco Gaido @mgaido91 ·

11 Jun

🚀 Last call for the Model Compression for Machine Translation task at #WMT2025 (co-located with #EMNLP2025)!
Test data out on June 19 ➡️ 2 weeks for evaluation!
Can you shrink an LLM and keep translation quality high?
👉 https://www2.statmt.org/wmt25/model-compression.html #NLP #ML #LLM #ModelCompression

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11 Jun

Our pick of the week by @beomseok_lee_: "ALAS: Measuring Latent Speech-Text Alignment For Spoken Language Understanding In Multimodal LLMs" by Pooneh Mousavi, @yingzhi_wang, @mirco_ravanelli, and @CemSubakan (2025)

#SLU #speech #multimodal #LLM

Beomseok LEE @beomseok_lee_

Speech-language models show promise in multimodal tasks—but how well are speech & text actually aligned? 🤔

This paper https://arxiv.org/abs/2505.19937 proposes a new metric to measure layer-wise correlation between the two, with a focus on SLU tasks. 🔍🗣️📄

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