From a scientific/technical perspective, LiveMemories aimed at scaling up content extraction techniques towards very large scale extraction from multimedia sources, setting the scene for a Content Management Platform for Trentino; using this information to support new ways of linking, summarizing and classifying data in a new generation of digital memories which are `alive’ and user-centered; and to turn the creation of such memories into a communal web activity. Achieving these objectives made Trento a key player in the new Web Science Initiative, digital memories, and Web 2.0. But LiveMemories was also intended to have a social and cultural impact besides the scientific one: through the collection, analysis and preservation of digital memories of Trentino; by facilitating and encouraging the preservation of such community memories; and the fostering of new forms of community, and enrichment of our cultural and social heritage.
Our pick of the week by
@lina_conti
: "Greater accessibility can amplify discrimination in generative AI" by
@CarolinHolterm, @minhducbui_nlp, @KaitlynZhou, @vjhofmann, @kelina1124, @anne_lauscher
📰
#GenderBias #SpeechLLM
Pick of the week @fbk_mt: "Greater accessibility can amplify discrimination in generative AI"
Gender bias in speech-based LLMs examined from multiple angles: a user survey, automatic bias measurement, and pitch manipulation experiments.
https://arxiv.org/pdf/2603.22260
Late update, but we had two great talks last month!
#MachineTranslation #FBK #NLProc #GenderBias #SpeechSynthesis
Our pick of the week by @dhairya_su47605
: "Scaling Laws for Precision" by @tanishqkumar07, Zachary Ankner, @bfspectorShiekh, @blake__bordelon, @Muennighoff, @mansiege, @CPehlevan, Christopher R´e, @AdtRaghunathan
📰
#Quantization #LLM #ScalingLaw
Pick of the week @fbk_mt
Super interesting paper on the limitations of quantization, demonstrating how post-training quantization scales poorly in data.
https://arxiv.org/abs/2411.04330
⭐ For our #PickOfTheWeek, this paper explores an important question for modern speech AI:
🎙️ Which Evaluation for Which Speech Model?
👥 Authors: @Maureendss , @EeshanDhekane
Speech foundation models are evolving rapidly, but evaluation practices are still fragmented.