LCB-net: Long-Context Biasing for Audio-Visual Speech Recognition

The growing prevalence of online conferences and courses presents a new challenge in improving automatic speech recognition (ASR) with enriched textual information from video slides. In contrast to rare phrase lists, the slides within videos are synchronized in real-time with the speech, enabling the extraction of long contextual bias. Therefore, we propose a novel long-context biasing network (LCB-net) for audio-visual speech recognition (AVSR) to leverage the long-context information available in videos effectively. Specifically, we adopt a bi-encoder architecture to simultaneously model audio and long-context biasing. Besides, we also propose a biasing prediction module that utilizes binary cross entropy (BCE) loss to explicitly determine biased phrases in the long-context biasing. Furthermore, we introduce a dynamic contextual phrases simulation to enhance the generalization and robustness of our LCB-net. Experiments on the SlideSpeech, a large-scale audio-visual corpus enriched with slides, reveal that our proposed LCB-net outperforms general ASR model by 9.4%/9.1%/10.9% relative WER/U-WER/B-WER reduction on test set, which enjoys high unbiased and biased performance. Moreover, we also evaluate our model on LibriSpeech corpus, leading to 23.8%/19.2%/35.4% relative WER/U-WER/B-WER reduction over the ASR model.Comment: Accepted by ICASPP 202

A Review on Robot Manipulation Methods in Human-Robot Interactions

Robot manipulation is an important part of human-robot interaction technology. However, traditional pre-programmed methods can only accomplish simple and repetitive tasks. To enable effective communication between robots and humans, and to predict and adapt to uncertain environments, this paper reviews recent autonomous and adaptive learning in robotic manipulation algorithms. It includes typical applications and challenges of human-robot interaction, fundamental tasks of robot manipulation and one of the most widely used formulations of robot manipulation, Markov Decision Process. Recent research focusing on robot manipulation is mainly based on Reinforcement Learning and Imitation Learning. This review paper shows the importance of Deep Reinforcement Learning, which plays an important role in manipulating robots to complete complex tasks in disturbed and unfamiliar environments. With the introduction of Imitation Learning, it is possible for robot manipulation to get rid of reward function design and achieve a simple, stable and supervised learning process. This paper reviews and compares the main features and popular algorithms for both Reinforcement Learning and Imitation Learning

Quantitative liquid storage by billiards‐like droplet collision on surfaces with patterned wettability

Abstract There has been significant interest in researching droplet transport behavior on composite wetting surfaces. However, current research is primarily focused on modifying individual droplets and lacks an in‐depth investigation into high‐precision droplet storage. This study introduces a “billiard ball” droplet transport and storage platform (TSP) with differentiated areas. Within this platform, the volume of droplets stored in the area reaches a consistent threshold through droplet “scrambling,” inspired by the water‐gathering behavior of spiders. The TSP involves connecting two regions of different sizes using a three‐dimensional stepped wedge angle structure. However, this connection is not seamless, leaving a 2‐mm gap between the regions. This gap is intentionally designed to enable continuous droplet transfer while preventing any static migration. Through systematic experimental and simulation analysis, we investigated the influence of superhydrophilic pattern structures and parameters on quantitative droplet storage. We established a functional relationship between the pattern area and the stored volume, and analyzed the intrinsic mechanism of droplet collision separation. This enabled us to achieve on‐demand quantitative droplet storage and autonomize the storage process. The “billiard ball” droplet transport–storage platform proposed in this study holds promising applications in the fields of biomedical and organic chemistry

Comparative study of the anti-corrosive properties of thiols induced superhydrophobic surfaces

Fluoroalkyl thiols and alkyl thiols are widely used as low surface energy reagents for the preparation of superhydrophobic surfaces and corrosion resistant surfaces. Although the corrosion resistance of thiol-induced superhydrophobic surfaces has been well addressed previously, few studies have devoted to revealing the difference of fluoroalkyl thiol and alkyl thiol modified surfaces towards anti-corrosion. In this work, two types of superhydrophobic surfaces were prepared by respectively coating self-assembled monolayers (SAMs) of 1 H,1 H,2 H,2 H-perfluorodecanethiol (PFDT) and 1-dodecanethiol (DDT) on femtosecond laser engineered copper substrates. The formation mechanism of the SAMs was explained by analyzing the surface chemical composition. The water contact angle of the PFDT and DDT modified surfaces were measured to be 157.7° and 154.6°, respectively. Electrochemical tests showed that both SAMs significantly reduced the corrosion current density (Icorr) and corrosion rate of the copper surfaces, while simultaneously increased the charge transfer resistance (Rct) value by an order of magnitude compared to the pristine copper surface. The surface with PFDT SAM had the smallest Icorr and its Rct value was about 1.5 times larger than that with the DDT SAM. These results confirmed that both the SAMs enhanced the anti-corrosion properties of the copper surfaces, and the PFDT SAM was proved to be more effective. Furthermore, the anti-corrosion durability of the PFDT and DDT modified surfaces were compared after exposing them to salt, acid, and alkali solutions for 12 h, and the results showed that the surfaces maintained to be hydrophobic and anti-corrosive, and the PFDT induced superhydrophobic surface indicated better durability. Our results demonstrated that thiols SAMs could significantly improve the anti-corrosion property of structured metal surfaces, and that fluoroalkyl thiol was more desired for long-term anti-corrosive applications in comparison with alkyl thiol

Biophysical Characteristics of Meridians and Acupoints: A Systematic Review

As an integral part of traditional Chinese medicine (TCM), acupuncture is a convenient and effective therapy with fewer adverse effects. Recently, researches on meridian essence have become core issues of modern TCM. Numerous experiments have demonstrated the objective existence of meridians by different technologies since 1950s, such as biophysics, biochemistry, and molecular biology. In this paper, we review biophysical studies on electric, acoustic, thermal, optical, magnetic, isotopic, and myoelectric aspects of meridians and acupoints. These studies suggest that meridians/acupoints have biophysical characteristics which are different from nonacupuncture points. Owing to the limitations of previous studies, future research using highthroughput technologies such as omics and multicenter randomized controlled trials should be performed to explore the acupuncture's mechanisms of action and demonstration of efficacy