Low Resource Neural Machine Translation: A Benchmark for Five African Languages

MT Group at FBK Follow

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

13h

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 1 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

Retweet on Twitter MT Group at FBK Retweeted

Avatar Meetween @meetweeneu ·

1 Apr

Meetween is part of the organising committee of #IWSLT2026 — the premier conference on spoken language translation. The Shared Task Evaluation Period is open. Working on #speechtranslation, instruction following, or #modelcompression?
Get involved now! 🔗 http://iwslt.org/2026

Reply on Twitter 2039350814884422112 Retweet on Twitter 2039350814884422112 3 Like on Twitter 2039350814884422112 3 Twitter 2039350814884422112