Tootfinder

Children's Voice Privacy: First Steps And Emerging Challenges
Ajinkya Kulkarni, Francisco Teixeira, Enno Hermann, Thomas Rolland, Isabel Trancoso, Mathew Magimai Doss
https://arxiv.org/abs/2506.00100

Children's Voice Privacy: First Steps And Emerging Challenges
Children are one of the most under-represented groups in speech technologies, as well as one of the most vulnerable in terms of privacy. Despite this, anonymization techniques targeting this population have received little attention. In this study, we seek to bridge this gap, and establish a baseline for the use of voice anonymization techniques designed for adult speech when applied to children's voices. Such an evaluation is essential, as children's speech presents a distinct set of challenge…

Computing Tree Structures in Anonymous Graphs via Mobile Agents
Prabhat Kumar Chand, Manish Kumar, Anisur Rahaman Molla
https://arxiv.org/abs/2506.19365 ht…

Computing Tree Structures in Anonymous Graphs via Mobile Agents
Minimum Spanning Tree (MST) and Breadth-First Search (BFS) tree constructions are classical problems in distributed computing, traditionally studied in the message-passing model, where static nodes communicate via messages. This paper investigates MST and BFS tree construction in an agent-based network, where mobile agents explore a graph and compute. Each node hosts one agent, and communication occurs when agents meet at a node. We consider $n$ agents initially dispersed (one per node) in an a…

👁️ Um einen breiteren Einblick in die Bedarfe der #GLAM - Institutionen und Forschungseinrichtungen im Bezug auf gegenwärtige und zukünftige #Datenkompetenzen zu gewinnen, lädt das Datenkompetenzzentrum “Humanities Education in Research, Data, and Methods” (HERMES) herzlich dazu ein, an einer anonyme…

"Despite good-faith efforts by DSI [dense street imagery] providers to protect individual privacy through blurring faces and license plates, these measures fail to address broader privacy concerns. In this work, we find that increased data density and advancements in artificial intelligence enable harmful group membership inferences from supposedly anonymized data."
via @…

Privacy of Groups in Dense Street Imagery
Spatially and temporally dense street imagery (DSI) datasets have grown unbounded. In 2024, individual companies possessed around 3 trillion unique images of public streets. DSI data streams are only set to grow as companies like Lyft and Waymo use DSI to train autonomous vehicle algorithms and analyze collisions. Academic researchers leverage DSI to explore novel approaches to urban analysis. Despite good-faith efforts by DSI providers to protect individual privacy through blurring faces and l…

This https://arxiv.org/abs/2506.00100 has been replaced.
initial toot: https://mastoxiv.page/@arXiv_csCY_…

Children's Voice Privacy: First Steps And Emerging Challenges
Children are one of the most under-represented groups in speech technologies, as well as one of the most vulnerable in terms of privacy. Despite this, anonymization techniques targeting this population have received little attention. In this study, we seek to bridge this gap, and establish a baseline for the use of voice anonymization techniques designed for adult speech when applied to children's voices. Such an evaluation is essential, as children's speech presents a distinct set of challenge…