- Matteo Amodio, degree obtained: Laura Magistrale, University of Udine. “Evaluating Language Models for Football Possession Analytics: Team Assignment from Transcripts”, 2025.
- Eleonora Cupin, degree obtained: Laura Magistrale, University of Bologna, Forlì Campus. “Breaking gender bias in Machine Translation: Expanding the GeNTE corpus and exploring LLMs (inclusive) capabilities”, 2025.
- Manjinde Thind, degree obtained: Laura Magistrale, University of Bologna, Forlì Campus. “mGeNTE: A Multilingual Resource for Gender-Neutral Language and Translation”, 2025.
- Silvia Alma Piazzolla. degree obtained: Laura Magistrale – LM, Università di Trento (Italy). Dissertation: “Gender bias in commercial MT systems: a comparative evaluation on the MuST-SHE benchmark”, 2022
- Andrea Piergentili , degree obtained: Laurea Magistrale – LM, Lingue e Culture per la Comunicazione e Cooperazione Internazionale, Università dell’Aquila (Italy). Dissertation: “Creation of a multilingual benchmark for the evaluation of gender neutral automatic translation”, 2022
- Francesca Onorato, degree obtained: Laurea in Computer Science, University of Trento (Italy), Dissertation “Segmentation Strategies for End-to-End Simultaneous Speech Translation”, 2021
- Antonio Vespoli, degree obtained: Laurea in Computer Science, University of Trento (Italy), Dissertation: “Data-to-Text: Generating Forecast Bulletins from Raw Data”, 2020
- Andrea Alfieri, degree obtained: Master of Arts – MA, Specialized Translation, U. Bologna-Forlì, 2020
- Nicholas Ruiz, degree obtained: European Master Erasmus Mundus Language & Communication Technologies, Free University of Bozen-Bolzano, 2011.
- Diego Pineda, degree obtained: European Master in Language and Speech, Universitat Politècnica de Catalunya, 2006. Dissertation: “A Punctuation Detector in Speech Recognition”. Now with SOGETI, Barcelona, Spain.
- Florian Hönig, degree obatined: Master in Electronic Engineering, Erlangen-Nuremberg University, 2005. Dissertation: “Modifications of Perceptual Linear Prediction and the Mel-Frequency Cepstrum”. Now PhD student at Erlangen-Nuremberg University, Germany.
- Michele Vescovi, degree obtained: degree in informatics, U. Trento, Mar 2003. Dissertation: “Algoritmi per la segmentazione audio basati sul criterio di informazione bayesiano: analisi, implementazione e sperimentazione”. Now PhD Student at U. of Trento.
- Erwin Leeuwis, degree obtained: degree in informatics, U. Twente, Feb 2003. Dissertation: “A Language Model for an ASR System for Lectures”. Now at Capgemini, Utrecht Area, Netherlands.
- Nicola Bertoldi, degree obtained: Laurea degree in mathematics, U. Trento, 2000. Dissertation: “Analysis and implementation of Statistical Models for POS tagging”. Now staff researcher at FBK-irst.
- Christian Girardi, degree obtained: degree in informatics, U. Trento, 2000. Dissertation: “Sviluppo di un’interfaccia grafica per un sistema di comunicazione vocale multilingua”. Now at FBK-irst.
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