14 accepted papers
Reinforcement learning has emerged as a paradigm for post-training large language models, boosting their reasoning capabilities. Such approaches compute an advantage value for each sample, reflecting better or worse performance than expected, thereby yielding both positive and negative signals for t
Multimodal large language models (MLLMs) have made significant progress in mobile agent development, yet their capabilities are predominantly confined to a reactive paradigm, where they merely execute explicit user commands. The emerging paradigm of proactive intelligence, where agents autonomously
There are many methods for detecting forged audio produced by conversion and synthesis. However, as a simpler method of forgery, splicing has not attracted widespread attention. Based on the characteristic that the tampering operation will cause singularities at high-frequency components, we propose…
Audio deepfake detection is an emerging topic, which was included in the ASVspoof 2021. However, the recent shared tasks have not covered many real-life and challenging scenarios. The first Audio Deep synthesis Detection challenge (ADD) was motivated to fill in the gap. The ADD 2022 includes three t…
Intelligent surfaces at millimeter wave and terahertz band employ large antenna arrays based on advanced metamaterials to realize controllable wireless propagation. Such intelligent surfaces can achieve polarization tuning of electromagnetic waves, which allows polarization diversity under the ultra…
Recent techniques utilizing reflectarrays or novel metamaterial-based surfaces to control wireless propagation environments have attracted great attention. While most solutions focus on sub-6 GHz wireless channel to assist in throughput enhancement, these intelligent surfaces have significant potent…
Programmable wireless environments (PWEs) utilize electromagnetic metasurfaces to transform wireless propagation into a software-controlled resource. In this work we study the effects of user device mobility on the efficiency of PWEs. An analytical model is proposed, which describes the potential mi…
In almost all adaptive dereverberation algorithms based on the multi-channel linear prediction (MCLP) model, it is assumed that the filter length can cover the reverberation time. However, in many practical situations, a deficient length filter, whose length is less than the reverberation time, is e…
Millimeter-wave (30-300 GHz) and Terahertz-band communications (0.3-10 THz) are envisioned as key wireless technologies to satisfy the demand for Terabit-per-second (Tbps) links in the 5G and beyond eras. The very large available bandwidth in this ultra-broadband frequency range comes at the cost of…
Keyword spotting (KWS) system constitutes a critical component of human-computer interfaces, which detects the specific keyword from a continuous stream of audio. The goal of KWS is providing a high detection accuracy at a low false alarm rate while having small memory and computation requirements.…
Domain adaptation has shown promising advances for alleviating domain shift problem. However, recent visual domain adaptation works usually focus on non-sequential object recognition with a global coarse alignment, which is inadequate to transfer effective knowledge for sequence-like text images wit…
In realistic environments, speech is usually interfered by various noise and reverberation, which dramatically degrades the performance of automatic speech recognition (ASR) systems. To alleviate this issue, the commonest way is to use a well-designed speech enhancement approach as the front-end of…
The targets of speech separation, whether ideal masks or magnitude spectrograms of interest, have prominent spectro-temporal structures. These characteristics are very worthy to be exploited for speech separation, however, they are usually ignored in previous works. In this paper, we use nonnegative…
Pitch information is an important cue for speech separation. However, pitch estimation in noisy condition is also a task as challenging as speech separation. In this paper, we propose a supervised learning architecture which combines these two problems concisely. The proposed algorithm is based on d…