The project includes technology transfer activities from FBK-irst to Pervoice and development activities such as improvements of automatic transcription technology (rich transcription, automatic text polishing), speech analytics technologies for call centers (emotional state recognition, segmentation and classification of utterances, monitoring of transactions), and advanced acoustic normalization techniques.
Our pick of the week by @FBKZhihangXie: "#Speech Discrete Tokens or Continuous Features? A Comparative Analysis for Spoken Language Understanding in #SpeechLLMs" by @WangDingdo2603, Junan Li, @HelenMeng_CUHK, et al. (#EMNLP2025)
#SLU #SpeechTech
๐ New paper: Speech Discrete Tokens or Continuous Features?
๐ https://aclanthology.org/2025.emnlp-main.1266.pdf
๐งฉ A comprehensive benchmark of SpeechLLMs using HuBERT/WavLM with Qwen & LLaMA.
โจ Continuous features outperform overall, while discrete tokens excel at phoneme-level detail.
๐ Exciting news from the @FBK_MT group!
Four of our members @BeatriceSavoldi, @lina_conti, @negri_teo & @luisabentivogli are attending #EMNLP2025 in Suzhou ๐จ๐ณ with 5 accepted papers!
Come to our sessions & let's connect:
๐ https://mt.fbk.eu/fbk-mt-at-emnlp-2025/
Weโre also hiring postdocs!โก
๐๐Congratulations to our PhD student @DennisFucci on a very successful thesis defense! ๐
Many thanks to the evaluation committee members @debora_nozza, @mirco_ravanelli, and Leonardo Badino for their insightful feedback and appreciation of his work!
#nlproc