Concept
Speech synthesis
Related publications (611)
Training a Filter-Based Model of the Cochlea in the Context of Pre-Trained Acoustic Models
Auditory research aims in general to lead to understanding of physiological processes. By contrast, the state of the art in automatic speech processing (notably recognition) is dominated by large pre-trained models that are meant to be used as black-boxes. ...
2024On matching data and model in LF-MMI-based dysarthric speech recognition
In light of steady progress in machine learning, automatic speech recognition (ASR) is entering more and more areas of our daily life, but people with dysarthria and other speech pathologies are left behind. Their voices are underrepresented in the trainin ...
EPFL2023Text as a Richer Source of Supervision in Semantic Segmentation Tasks
Devis Tuia, Valérie Zermatten, Javiera Francisca Castillo Navarro, Lloyd Haydn Hughes
This paper introduces TACOSS a text-image alignment approach that allows explainable land cover semantic segmentation by directly integrating semantic concepts encoded from texts. TACOSS combines convolutional neural networks for visual feature extraction ...
The Institute of Electrical and Electronics Engineers, Inc2023Novel Methods For Detection And Analysis Of Atypical Aspects In Speech
Atypical aspects in speech concern speech that deviates from what is commonly considered normal or healthy. In this thesis, we propose novel methods for detection and analysis of these aspects, e.g. to monitor the temporary state of a speaker, diseases tha ...
EPFL2023Can Self-Supervised Neural Networks Pre-Trained on Human Speech distinguish Animal Callers?
Mathew Magimai Doss, Eklavya Sarkar
Self-supervised learning (SSL) models use only the intrinsic structure of a given signal, independent of its acoustic domain, to extract essential information from the input to an embedding space. This implies that the utility of such representations is no ...
ISCA2023A multimodal measurement of the impact of deepfakes on the ethical reasoning and affective reactions of students
Touradj Ebrahimi, Patrick Jermann, Roland John Tormey, Cécile Hardebolle, Vivek Ramachandran, Nihat Kotluk
Deepfakes - synthetic videos generated by machine learning models - are becoming increasingly sophisticated. While they have several positive use cases, their potential for harm is also high. Deepfake production involves input from multiple engineers, maki ...
2023Sparse Autoencoders for Speech Modeling and Recognition
Speech recognition-based applications upon the advancements in artificial intelligence play an essential role to transform most aspects of modern life. However, speech recognition in real-life conditions (e.g., in the presence of overlapping speech, varyin ...
EPFL2023On the Privacy-Robustness-Utility Trilemma in Distributed Learning
Rachid Guerraoui, Nirupam Gupta, John Stephan, Youssef Allouah, Rafaël Benjamin Pinot
The ubiquity of distributed machine learning (ML) in sensitive public domain applications calls for algorithms that protect data privacy, while being robust to faults and adversarial behaviors. Although privacy and robustness have been extensively studied ...
2023Deep Generative Models for Autonomous Driving: from Motion Forecasting to Realistic Image Synthesis
Forecasting is a capability inherent in humans when navigating. Humans routinely plan their paths, considering the potential future movements of those around them. Similarly, to achieve comparable sophistication and safety, autonomous systems must embrace ...
EPFL2023Automatic Multi-Robot Control Design and Optimization Leveraging Multi-Level Modeling: An Exploration Case Study
Alcherio Martinoli, Cyrill Silvan Baumann, Wakana Endo
More specifically, a behavior-based controller for a multi-robot exploration scenario is automatically synthesized using a predefined set of basic behaviors and conditions. A key feature of the used synthesis approach is the tailored use of two modeling le ...
Elsevier2023