6 accepted papers
Recent advancements in image generation models enable the creation of high-quality images and targeted modifications based on textual instructions. Some models even support multimodal complex guidance and demonstrate robust task generalization capabilities. However, they still fall short of meeting…
This paper describes the legends-tencent team’s real-time General Speech Restoration (Gesper) system submitted to the ICASSP 2023 Speech Signal Improvement (SSI) Challenge. This newly proposed system is a two-stage architecture, in which the speech restoration is performed, and then followed by spee…
Traditional face-to-face subjective listening test has become a challenge due to the COVID-19 pandemic. We developed a remote assessment system with Tencent Meeting, a video conferencing application, to address this issue. This paper presents our work on evaluating the reliability of the remote asse…
Semantic image synthesis is a challenging task with many practical applications. Albeit remarkable progress has been made in semantic image synthesis with spatially-adaptive normalization and existing methods normalize the feature activations under the coarse-level guidance (e.g., semantic class). H…
Signal processing strategies in most clinical cochlear implants (CIs) extract and transmit speech envelopes to stimulate the auditory neurons. The incomplete representation of the rich fine structures in speech has significantly degraded the CI recipients’ ability in high- level perception, includin…
Unsupervised disentanglement learning is a crucial issue for understanding and exploiting deep generative models. Recently, SeFa tries to find latent disentangled directions by performing SVD on the first projection of a pre-trained GAN. However, it is only applied to the first layer and works in a…