Efficient training strategies for natural sounding speech synthesis and speaker adaptation based on FastPitch
AI4TRUST partners submitted a Paper at the 2024 IEEE 20th International Conference on Intelligent Computer Communication and Processing (ICCP 2024) , Cluj-Napoca, Romania, in October 2024.
Translating speech with just images
AI4TRUST partners presented a paper on visually grounded speech models link speech to images – linking images to text via an existing image captioning system, and as a result gain the ability to map speech audio directly to text, at Interspeech 2024, Kos, Greece in September 2024.
Hybrid-Diarization System with Overlap Post-Processing for the DISPLACE 2024 Challenge
AI4TRUST partners presented a paper at Interspeech 2024, Kos, Greece on the team’s collaborative efforts in participating in the Track 1 for Speaker Diarization of the Diarization of Speaker and Language in conversational Environments (DISPLACE) Challenge 2024, in September 2024.
Towards generalisable and calibrated audio deepfake detection with self-supervised representations
AI4TRUST partners submitted a Paper to discuss how Generalisation—the ability of a model to perform well on unseen data—is crucial for building reliable deepfake detectors. However, recent studies have shown that the current audio deepfake models fall short of this desideratum at Interspeech 2024, Kos, Greece in September 2024.
Early morning hour and evening usage habits increase misinformation-spread
AI4TRUST partners published a paper in Nature Scientific Report on social media manipulation and how it poses a significant threat to cognitive autonomy and unbiased opinion formation in August 2024.
WavLM model ensemble for audio deepfake detection
AI4TRUST partners submitted a Paper at Automatic Speaker Verification and Spoofing Countermeasures Challenge (ASVSpoof5) in August 2024.
Visually Grounded Speech Models Have a Mutual Exclusivity Bias
AI4TRUST partners published a Journal article in Transactions of the Association for Computational Linguistics to investigate the ME bias in the context of visually grounded speech models that learn from natural images and continuous speech audio in June 2024.
Towards Quantitative Evaluation of Explainable AI Methods for Deepfake Detection
AI4TRUST partners submitted a Conference Paper discussing a new framework for evaluating the performance of explanation methods on the decisions of a deepfake detector at Proc. ACM Int. Workshop on Multimedia AI against Disinformation (MAD’24) at the ACM Int. Conf. on Multimedia Retrieval (ICMR’24) in June 2024.
VARIATIONIST: Exploring Multifaceted Variation and Bias in Written Language Data
AI4TRUST partners submitted a paper on Exploring and understanding language data is a fundamental stage in all areas dealing with human language and presented at the 62nd Annual Meeting of the Association for Computational Linguistics (ACL 2024) in Bangkok, Thailand in August 2024
Towards Quantitative Evaluation of Explainable AI Methods for Deepfake Detection
AI4TRUST partners submitted a Conference Paper discussing a new framework for evaluating the performance of explanation methods on the decisions of a deepfake detector at Proc. ACM Int. Workshop on Multimedia AI against Disinformation (MAD’24) at the ACM Int. Conf. on Multimedia Retrieval (ICMR’24) in June 2024.