Boosting Cross-Domain Speech Recognition with Self-Supervision

The cross-domain performance of automatic speech recognition (ASR) could be severely hampered due to the mismatch between training and testing distributions. Since the target domain usually lacks labeled data, and domain shifts exist at acoustic and linguistic levels, it is challenging to perform unsupervised domain adaptation (UDA) for ASR. Previous work has shown that self-supervised learning (SSL) or pseudo-labeling (PL) is effective in UDA by exploiting the self-supervisions of unlabeled data. However, these self-supervisions also face performance degradation in mismatched domain distributions, which previous work fails to address. This work presents a systematic UDA framework to fully utilize the unlabeled data with self-supervision in the pre-training and fine-tuning paradigm. On the one hand, we apply continued pre-training and data replay techniques to mitigate the domain mismatch of the SSL pre-trained model. On the other hand, we propose a domain-adaptive fine-tuning approach based on the PL technique with three unique modifications: Firstly, we design a dual-branch PL method to decrease the sensitivity to the erroneous pseudo-labels; Secondly, we devise an uncertainty-aware confidence filtering strategy to improve pseudo-label correctness; Thirdly, we introduce a two-step PL approach to incorporate target domain linguistic knowledge, thus generating more accurate target domain pseudo-labels. Experimental results on various cross-domain scenarios demonstrate that the proposed approach effectively boosts the cross-domain performance and significantly outperforms previous approaches.Comment: Accepted by IEEE/ACM Transactions on Audio, Speech and Language Processing (TASLP), 202

EmotionPrompt: Leveraging Psychology for Large Language Models Enhancement via Emotional Stimulus

Large language models (LLMs) have achieved significant performance in many fields such as reasoning, language understanding, and math problem-solving, and are regarded as a crucial step to artificial general intelligence (AGI). However, the sensitivity of LLMs to prompts remains a major bottleneck for their daily adoption. In this paper, we take inspiration from psychology and propose EmotionPrompt to explore emotional intelligence to enhance the performance of LLMs. EmotionPrompt operates on a remarkably straightforward principle: the incorporation of emotional stimulus into prompts. Experimental results demonstrate that our EmotionPrompt, using the same single prompt templates, significantly outperforms original zero-shot prompt and Zero-shot-CoT on 8 tasks with diverse models: ChatGPT, Vicuna-13b, Bloom, and T5. Further, EmotionPrompt was observed to improve both truthfulness and informativeness. We believe that EmotionPrompt heralds a novel avenue for exploring interdisciplinary knowledge for humans-LLMs interaction.Comment: Work in progress; 9 page

Can minority shareholders’ “hand-voting” promote green innovation of Enterprises—Empirical evidence from Chinese listed companies

China’s listed companies have serious Principal-agent problem of the second kind. Large shareholders have violated the rights and interests of minority shareholders in an endless stream of cases. However, the voice of encouraging minority shareholders to actively participate in enterprise decision-making is growing day-by-day. However, there is no consensus on whether the enthusiasm of minority shareholders in decision-making can have a positive impact on enterprises. Therefore, this article takes China’s A-share listed companies from 2016 to 2020 as the research sample, and from the perspective of green innovation, discusses whether the minority shareholders’ active participation in enterprise decision-making can improve the level of green innovation of enterprises. The study found that the minority shareholders’ active participation in enterprise decision-making can improve the level of green innovation. Moreover, the minority shareholders’ “hand voting” improves the green innovation level of enterprises by influencing the media attention; A higher level of legal environment is conducive to strengthening the role of minority shareholders’ participation in the shareholders’ meeting in green innovation. Based on the property right nature, regional and industrial level, further research found that the minority share-holders’ role in improving green innovation capacity is more significant in non-state-owned enterprises, eastern regions and heavy pollution industries. The research results show that minority shareholders, as an important force to monitor the senior executives’ behavior and enhance corporate value, actively participate in corporate decision-making, can not only improve corporate governance, but also benefit the sustainable development of enterprises

Quantum Computing for MIMO Beam Selection Problem: Model and Optical Experimental Solution

Massive multiple-input multiple-output (MIMO) has gained widespread popularity in recent years due to its ability to increase data rates, improve signal quality, and provide better coverage in challenging environments. In this paper, we investigate the MIMO beam selection (MBS) problem, which is proven to be NP-hard and computationally intractable. To deal with this problem, quantum computing that can provide faster and more efficient solutions to large-scale combinatorial optimization is considered. MBS is formulated in a quadratic unbounded binary optimization form and solved with Coherent Ising Machine (CIM) physical machine. We compare the performance of our solution with two classic heuristics, simulated annealing and Tabu search. The results demonstrate an average performance improvement by a factor of 261.23 and 20.6, respectively, which shows that CIM-based solution performs significantly better in terms of selecting the optimal subset of beams. This work shows great promise for practical 5G operation and promotes the application of quantum computing in solving computationally hard problems in communication.Comment: Accepted by IEEE Globecom 202

On the Robustness of ChatGPT: An Adversarial and Out-of-distribution Perspective

ChatGPT is a recent chatbot service released by OpenAI and is receiving increasing attention over the past few months. While evaluations of various aspects of ChatGPT have been done, its robustness, i.e., the performance to unexpected inputs, is still unclear to the public. Robustness is of particular concern in responsible AI, especially for safety-critical applications. In this paper, we conduct a thorough evaluation of the robustness of ChatGPT from the adversarial and out-of-distribution (OOD) perspective. To do so, we employ the AdvGLUE and ANLI benchmarks to assess adversarial robustness and the Flipkart review and DDXPlus medical diagnosis datasets for OOD evaluation. We select several popular foundation models as baselines. Results show that ChatGPT shows consistent advantages on most adversarial and OOD classification and translation tasks. However, the absolute performance is far from perfection, which suggests that adversarial and OOD robustness remains a significant threat to foundation models. Moreover, ChatGPT shows astounding performance in understanding dialogue-related texts and we find that it tends to provide informal suggestions for medical tasks instead of definitive answers. Finally, we present in-depth discussions of possible research directions.Comment: Technical report; code is at: https://github.com/microsoft/robustlear

Vulto-van Silfhout-de Vries syndrome caused by de novo variants of DEAF1 gene: a case report and literature review

Vulto-van Silfhout-de Vries syndrome (VSVS; MIM 615828) is an extremely rare autosomal dominant disorder with unknown incidence. It is always caused by de novo heterozygous pathogenic variants in the DEAF1 gene, which encodes deformed epidermal autoregulatory factor-1 homology. VSVS is characterized by mild to severe intellectual disability (ID) and/or global developmental delay (GDD), seriously limited language expression, behavioral abnormalities, somnipathy, and reduced pain sensitivity. In this study, we present a Chinese boy with moderate GDD and ID, severe expressive language impairment, behavioral issues, autism spectrum disorder (ASD), sleeping dysfunction, high pain threshold, generalized seizures, imbalanced gait, and recurrent respiratory infections as clinical features. A de novo heterozygous pathogenic missense variant was found in the 5th exon of DEAF1 gene, NM_021008.4 c.782G>C (p. Arg261Pro) variant by whole exome sequencing (WES). c.782G>C had not been previously reported in genomic databases and literature. According to the ACMG criteria, this missense variant was considered to be “Likely Pathogenic”. We diagnosed the boy with VSVS both genetically and clinically. At a follow-up of 2.1 years, his seizures were well controlled after valproic acid therapy. In addition, the child’s recurrent respiratory infections improved at 3.5 years of age, which has not been reported in previous individuals. Maybe the recurrent respiratory infections like sleep problems reported in the literature are not permanent but may improve naturally over time. The literature review showed that there were 35 individuals with 28 different de novo pathogenic variants of DEAF1-related VSVS. These variants were mostly missense and the clinical manifestations were similar to our patient. Our study expands the genotypic and phenotypic profiles of de novo DEAF1

31st Annual Meeting and Associated Programs of the Society for Immunotherapy of Cancer (SITC 2016) : part two

Background The immunological escape of tumors represents one of the main ob- stacles to the treatment of malignancies. The blockade of PD-1 or CTLA-4 receptors represented a milestone in the history of immunotherapy. However, immune checkpoint inhibitors seem to be effective in specific cohorts of patients. It has been proposed that their efficacy relies on the presence of an immunological response. Thus, we hypothesized that disruption of the PD-L1/PD-1 axis would synergize with our oncolytic vaccine platform PeptiCRAd. Methods We used murine B16OVA in vivo tumor models and flow cytometry analysis to investigate the immunological background. Results First, we found that high-burden B16OVA tumors were refractory to combination immunotherapy. However, with a more aggressive schedule, tumors with a lower burden were more susceptible to the combination of PeptiCRAd and PD-L1 blockade. The therapy signifi- cantly increased the median survival of mice (Fig. 7). Interestingly, the reduced growth of contralaterally injected B16F10 cells sug- gested the presence of a long lasting immunological memory also against non-targeted antigens. Concerning the functional state of tumor infiltrating lymphocytes (TILs), we found that all the immune therapies would enhance the percentage of activated (PD-1pos TIM- 3neg) T lymphocytes and reduce the amount of exhausted (PD-1pos TIM-3pos) cells compared to placebo. As expected, we found that PeptiCRAd monotherapy could increase the number of antigen spe- cific CD8+ T cells compared to other treatments. However, only the combination with PD-L1 blockade could significantly increase the ra- tio between activated and exhausted pentamer positive cells (p= 0.0058), suggesting that by disrupting the PD-1/PD-L1 axis we could decrease the amount of dysfunctional antigen specific T cells. We ob- served that the anatomical location deeply influenced the state of CD4+ and CD8+ T lymphocytes. In fact, TIM-3 expression was in- creased by 2 fold on TILs compared to splenic and lymphoid T cells. In the CD8+ compartment, the expression of PD-1 on the surface seemed to be restricted to the tumor micro-environment, while CD4 + T cells had a high expression of PD-1 also in lymphoid organs. Interestingly, we found that the levels of PD-1 were significantly higher on CD8+ T cells than on CD4+ T cells into the tumor micro- environment (p < 0.0001). Conclusions In conclusion, we demonstrated that the efficacy of immune check- point inhibitors might be strongly enhanced by their combination with cancer vaccines. PeptiCRAd was able to increase the number of antigen-specific T cells and PD-L1 blockade prevented their exhaus- tion, resulting in long-lasting immunological memory and increased median survival

Analysis and design of substrate integrated waveguide cavity filter for microwave & millimeter wave applications

Synthesis and analysis of pseudo elliptic filter -- Physical realization of pseudo elliptic filter -- Microstrip transition design -- Fabrication and measurements