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Scansani, Randy; Bernardini, Silvia; Ferraresi, Adriano; Bentivogli, Luisa,Proceedings of Machine Translation Summit XVII Volume 2: Translator, Project and User Tracks,vol. 2,2019, pp. 73-79
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Scansani, Randy; Bentivogli, Luisa; Bernardini, Silvia; Ferraresi, Adriano,Proceedings of Machine Translation Summit XVII Volume 1: Research Track,vol. 1,2019, pp. 78-86
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Di Gangi, Mattia Antonino; Negri, Matteo; Cattoni, Roldano; Dessi, Roberto; Turchi, Marco,Proceedings of Machine Translation Summit XVII Volume 1: Research Track,European Association for Machine Translation,2019, pp. 21-31
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Niehues, Jan; Cattoni, Roldano; Stuker, Sebastian; Negri, Matteo; Turchi, Marco; Salesky, Elizabeth; Sanabria, Ramon; Barrault, Loic; Specia, Lucia; Federico, Marcello,Proceedings of the 16th International Workshop on Spoken Language Translation 2019,2019
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Palmero Aprosio, Alessio; Tonelli, Sara; Turchi, Marco; Negri, Matteo; Di Gangi Mattia, A.,Proceedings of the Workshop on Methods for Optimizing and Evaluating Neural Language Generation (NeuralGen),Association for Computational Linguistics (ACL),2019, pp. 37-44
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Di Gangi, Mattia A.; Negri, Matteo; Turchi, Marco,Proceedings of INTERSPEECH 2019,International Speech Communication Association (ISCA),2019, pp. 1133-1137
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Karakanta, Alina; Negri, Matteo; Turchi, Marco,Proceedings of the Sixth Italian Conference on Computational Linguistics (CLiC-It),CEUR Workshop Proceedings,2019
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Di Gangi, Mattia A.; Negri, Matteo; Turchi, Marco,Proceedings of the 2019 IEEE Automatic Speech Recognition and Understanding Workshop (ASRU),IEEE,2019, pp. 585-592
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Farajian, M.; Bertoldi, Nicola; Negri, Matteo; Turchi, Marco; Federico, Marcello,Proceedings of the 21st Annual Conference of the European Association for Machine Translation,2018, pp. 149-158
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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
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
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/
🚀 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
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
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. 🔍🗣️📄