Meteo Trentino and FBK started a collaboration in 2009 with the goal of developing a translation system for weather forecast bulletins. On a daily basis, Meteo Trentino compiles and makes available through the WEB site a weather bulletin related to the Trentino area written in Italian. An equivalent or shortened version of that bulletin is also published in English and German after a manual translation made by forecasters. FBK has been asked to provide forecasters with a system for the automatic translation of Italian bulletins into those two languages. In the course of 2009, FBK has developed the translation system and a simple interface (shown in the figure below) which have been delivered to Meteo Trentino, whose forecasters are currently using. The project has been extended to 2010 with the goal of improving the quality of the automatic translation by exploiting feedback from real users.
Our pick of the week by
@mgaido91
: "FlexiSLM: A Dynamic and Controllable Frame Rate Spoken Language Model" by Jiaqi Li, Chaoren Wang, Xiaohai Tian, Mingjie Chen, Xinyu Liang, Xu Li, Yufan Lin, Junwen Qiu, Jun Zhang, Lu Lu, Haizhou Li and @drwuz
#SLM #EfficientInference
Cool to see a work that adaptively chooses at inference how much to compress the input speech sequence, to control inference costs and quality based on the input, without enforcing a global trade-off to each segment: https://arxiv.org/pdf/2606.31247
@fbk_mt
Our pick of the week by
@FBKZhihangXie : "Speech-XL: Towards Long-Form Speech Understanding in Large Speech Language Models" by Haoqin Sun, @Chenyang_Lyu, Shiwan Zhao, Xuanfan Ni, Xiangyu Kong, @wangly0229, Weihua Luo and Yong Qin
#SpeechLLM #LongFormSpeech #SLU
🚀 New paper: Speech-XL for long-form SpeechLLMs
📄 https://arxiv.org/abs/2602.05373
🧩 Uses Speech Summarization Tokens to compress local speech intervals into compact KV states efficiently.
✨ Improves long-form speech understanding while reducing memory and FLOPs on 10-minute audio.
Our pick of the week by
@BeatriceSavoldi
: "Accuracy: Community Perspectives on Machine Translation" by Yujun Wang,
@EhudReiter
, Shimei Pan,
@egere14
and Wei Zhao #MachineTranslation #TranslationQuality #Evaluation
📖 #PickoftheWeek @fbk_mt "Accuracy: Community Perspectives on Machine Translation"
A cool analysis of the conflicting interests of different communities around MT(AI developers, LSPs, and users)
https://arxiv.org/pdf/2606.09655
#NLP #MachineTranslation #DiverseStakeholders