FBK-Fairseq
Open source repository with the code and models used in recent papers
Read Moreby Marco Gaido | May 17, 2024 | Software | 0
Open source repository with the code and models used in recent papers
Read Moreby Marco Gaido | May 17, 2024 | Software | 0
SubSONAR evaluates the quality of SRT files using the multilingual multimodal SONAR model. The evaluation accounts for the semantic similarity (computed as a cosine similarity) between each subtitle block and the corresponding...
Read Moreby Marco Gaido | May 17, 2024 | Software | 0
pangolinn is a Python library for neural network developers that contains test suites aimed at...
Read Moreby Matteo Negri | May 30, 2023 | Software | 0
A neural adaptive machine translation system that adapts to context and learns from corrections
Read Moreby Dennis Fucci | May 30, 2023 | Software | 0
AQET (Adaptive Quality Estimation Tool) is an open-source package for performing Quality Estimation for Machine Translation able to continuously learn from post-edited sentences.
Read Moreby Andrea Piergentili | May 30, 2023 | Software | 0
An extension of MGIZA++, which allows to align sentence pair in an online mode.
Read Moreby Dennis Fucci | May 30, 2023 | Software | 0
The IRST Language Modeling (IRSTLM) Toolkit features algorithms and data structures suitable to estimate, store, and access very large n-gram language models.
Read Moreby Dennis Fucci | May 30, 2023 | Software | 0
Moses is a statistical machine translation system that allows you to automatically train translation models for any language pair.
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Our pick of the week by @FBKZhihangXie: "When End-to-End is Overkill: Rethinking Cascaded Speech-to-Text Translation" by Anna Min, et al, 2025.
Today's task: model compression!!
🎯 Goal: Compress a large, general-purpose multimodal model, making speech translation more efficient ⚡️, deployable 📲, and sustainable ♻️, while preserving translation quality ⭐️
#AI #SpeechTech #ModelCompression #LLMcompression
First up, a new task for 2025:
*Instruction-following for speech processing!*
Explore instruction-following for speech ⇨
Integrate speech foundation models with LLMs across tasks such as speech translation, recognition, summarization, and QA.
🔗:
📢Workshop gratuito 05/02: “Lo stato dell'arte nelle tecnologie per il riconoscimento del parlato.”
Diretta YouTube: https://www.youtube.com/live/i4x7w8fIIXo?si=wYvvrO3-MSh7Yik4
Registrazione: https://www.eventbrite.com/e/biglietti-lo-stato-dellarte-nelle-tecnologie-per-il-riconoscimento-del-parlato-1109098797359?aff=oddtdtcreator