A Weakly-Supervised Streaming Multilingual Speech Model with Truly Zero-Shot Capability

In this paper, we introduce our work of building a Streaming Multilingual Speech Model (SM2), which can transcribe or translate multiple spoken languages into texts of the target language. The backbone of SM2 is Transformer Transducer, which has high streaming capability. Instead of human labeled speech translation (ST) data, SM2 models are trained using weakly supervised data generated by converting the transcriptions in speech recognition corpora with a machine translation service. With 351 thousand hours of anonymized speech training data from 25 languages, SM2 models achieve comparable or even better ST quality than some recent popular large-scale non-streaming speech models. More importantly, we show that SM2 has the truly zero-shot capability when expanding to new target languages, yielding high quality ST results for {source-speech, target-text} pairs that are not seen during training.Comment: submitted to ICASSP 202

Synthesis of Silver Nanowires with Reduced Diameters Using Benzoin-Derived Radicals to Make Transparent Conductors with High Transparency and Low Haze.

Reducing the diameter of silver nanowires has been proven to be an effective way to improve their optoelectronic performance by lessening light attenuation. The state-of-the-art silver nanowires are typically around 20 nm in diameter. Herein we report a modified polyol synthesis of silver nanowires with average diameters as thin as 13 nm and aspect ratios up to 3000. The success of this synthesis is based on the employment of benzoin-derived radicals in the polyol approach and does not require high-pressure conditions. The strong reducing power of radicals allows the reduction of silver precursors to occur at relatively low temperatures, wherein the lateral growth of silver nanowires is restrained because of efficient surface passivation. The optoelectronic performance of as-prepared 13 nm silver nanowires presents a sheet resistance of 28 Ω sq-1 at a transmittance of 95% with a haze factor of ∼1.2%, comparable to that of commercial indium tin oxide (ITO)

LAMASSU: Streaming Language-Agnostic Multilingual Speech Recognition and Translation Using Neural Transducers

End-to-end formulation of automatic speech recognition (ASR) and speech translation (ST) makes it easy to use a single model for both multilingual ASR and many-to-many ST. In this paper, we propose streaming language-agnostic multilingual speech recognition and translation using neural transducers (LAMASSU). To enable multilingual text generation in LAMASSU, we conduct a systematic comparison between specified and unified prediction and joint networks. We leverage a language-agnostic multilingual encoder that substantially outperforms shared encoders. To enhance LAMASSU, we propose to feed target LID to encoders. We also apply connectionist temporal classification regularization to transducer training. Experimental results show that LAMASSU not only drastically reduces the model size but also outperforms monolingual ASR and bilingual ST models.Comment: Submitted to ICASSP 202

Simulation of centrifugal pumps based on MPS solver

In this article, a three dimensional full-scale centrifugal pump is, for the first time, simulated using the moving particle semi-implicit method(MPS). The genetic smooth wall boundary(GSW) is used and extended to three dimension to deal with the complicated wall shape and thin blades in turbo-machines. The non-surface detection technique(NSD) based on conceptual particles is combined with this wall model to avoid the loss of particle number density near wall boundaries. A local wall particle refinement method is developed. Fine particles and coarse particles are applied to curved surface and flat surface respectively so as to reduce the computational cost while maintain the high discretization precision. The fully developed velocity inflow and pressure outflow boundary conditions are proposed. Three typical cases including hydrostatic cases with complicated geometry, flows over a two-dimensional backward-facing step, and flows in a three-dimensional tube are tested to verify the proposed models. This paper constructs a framework for the simulation of incompressible fluid machines, in which 3D complex revolving bodies can be integrally discretized and interactions between the stator and rotor can be integrally solved within a single coordinate. This paper provides a particle-based solver for incompressible fluid machinery and has the potential to study its inner flow with multiphase or phase change

STICKERCONV: Generating Multimodal Empathetic Responses from Scratch

Stickers, while widely recognized for enhancing empathetic communication in online interactions, remain underexplored in current empathetic dialogue research, notably due to the challenge of a lack of comprehensive datasets. In this paper, we introduce the Agent for STICKERCONV (Agent4SC), which uses collaborative agent interactions to realistically simulate human behavior with sticker usage, thereby enhancing multimodal empathetic communication. Building on this foundation, we develop a multimodal empathetic dialogue dataset, STICKERCONV, comprising 12.9K dialogue sessions, 5.8K unique stickers, and 2K diverse conversational scenarios. This dataset serves as a benchmark for multimodal empathetic generation. To advance further, we propose PErceive and Generate Stickers (PEGS), a multimodal empathetic response generation framework, complemented by a comprehensive set of empathy evaluation metrics based on LLM. Our experiments demonstrate PEGS's effectiveness in generating contextually relevant and emotionally resonant multimodal empathetic responses, contributing to the advancement of more nuanced and engaging empathetic dialogue systems

Building High-accuracy Multilingual ASR with Gated Language Experts and Curriculum Training

We propose gated language experts and curriculum training to enhance multilingual transformer transducer models without requiring language identification (LID) input from users during inference. Our method incorporates a gating mechanism and LID loss, enabling transformer experts to learn language-specific information. By combining gated transformer experts with shared transformer layers, we construct multilingual transformer blocks and utilize linear experts to effectively regularize the joint network. The curriculum training scheme leverages LID to guide the gated experts in improving their respective language performance. Experimental results on a bilingual task involving English and Spanish demonstrate significant improvements, with average relative word error reductions of 12.5% and 7.3% compared to the baseline bilingual and monolingual models, respectively. Notably, our method achieves performance comparable to the upper-bound model trained and inferred with oracle LID. Extending our approach to trilingual, quadrilingual, and pentalingual models reveals similar advantages to those observed in the bilingual models, highlighting its ease of extension to multiple languages

Cell cycle arrest mediated by Cd-induced DNA damage in Arabidopsis root tips

Accumulating evidence demonstrates that the aberrant expression of cell cycle regulation and DNA repair genes can result in abnormal cell proliferation and genomic instability in eukaryotic cells under different stresses. Herein, Arabidopsis thaliana (Arabidopsis) seedlings were grown hydroponically on 0.5 × MS media containing cadmium (Cd) at 0–2.5 mg L−1 for 5 d of treatment. Real time quantitative reverse transcription-polymerase chain reaction (qRT-PCR) analysis revealed that expression of DNA damage repair and cell cycle regulation genes, including BRCA1, MRE11, WEE1, CDKA;1 and PCNA1, showed an inverted U-shaped dose-response. In contrast, notably reduced expression was observed for G1-to-S transition-related genes, Histone H4, E2Fa and PCNA2; DSB end processing, GR1; G2-to-M transition-related gene, CYCB1;1; and DNA mismatch repair, MSH2, MSH6 and MLH1 genes in root tips exposed to 0.125–2.5 mg/L Cd for 5 d. Flow cytometry (FCM) analysis revealed significant increases of cells with a 2C nuclear content and with a 4C and 8C nuclear content under Cd stresses of 0.125 and 1–2.5 mg L−1, respectively. Our results suggest that 0.125 mg L−1 Cd-induced DNA damage induced the marked G1/S arrest, leading to accelerated growth in root tips, while 1.0–2.5 mg L−1 Cd-induced DNA damage caused a notable G2/M arrest in root tips, leading to reduced growth in root tips. This may be a protective mechanism that prevents cells with damaged DNA from dividing under Cd stress

A Single-Cell Atlas of Bovine Skeletal Muscle Reveals Mechanisms Regulating Intramuscular Adipogenesis and Fibrogenesis

Background Intramuscular fat (IMF) and intramuscular connective tissue (IMC) are often seen in human myopathies and are central to beef quality. The mechanisms regulating their accumulation remain poorly understood. Here, we explored the possibility of using beef cattle as a novel model for mechanistic studies of intramuscular adipogenesis and fibrogenesis. Methods Skeletal muscle single-cell RNAseq was performed on three cattle breeds, including Wagyu (high IMF), Brahman (abundant IMC but scarce IMF), and Wagyu/Brahman cross. Sophisticated bioinformatics analyses, including clustering analysis, gene set enrichment analyses, gene regulatory network construction, RNA velocity, pseudotime analysis, and cell-cell communication analysis, were performed to elucidate heterogeneities and differentiation processes of individual cell types and differences between cattle breeds. Experiments were conducted to validate the function and specificity of identified key regulatory and marker genes. Integrated analysis with multiple published human and non-human primate datasets was performed to identify common mechanisms. Results A total of 32 708 cells and 21 clusters were identified, including fibro/adipogenic progenitor (FAP) and other resident and infiltrating cell types. We identified an endomysial adipogenic FAP subpopulation enriched for COL4A1 and CFD (log2FC = 3.19 and 1.92, respectively; P \u3c 0.0001) and a perimysial fibrogenic FAP subpopulation enriched for COL1A1 and POSTN (log2FC = 1.83 and 0.87, respectively; P \u3c 0.0001), both of which were likely derived from an unspecified subpopulation. Further analysis revealed more progressed adipogenic programming of Wagyu FAPs and more advanced fibrogenic programming of Brahman FAPs. Mechanistically, NAB2 drives CFD expression, which in turn promotes adipogenesis. CFD expression in FAPs of young cattle before the onset of intramuscular adipogenesis was predictive of IMF contents in adulthood (R2 = 0.885, P \u3c 0.01). Similar adipogenic and fibrogenic FAPs were identified in humans and monkeys. In aged humans with metabolic syndrome and progressed Duchenne muscular dystrophy (DMD) patients, increased CFD expression was observed (P \u3c 0.05 and P \u3c 0.0001, respectively), which was positively correlated with adipogenic marker expression, including ADIPOQ (R2 = 0.303, P \u3c 0.01; and R2 = 0.348, P \u3c 0.01, respectively). The specificity of Postn/POSTN as a fibrogenic FAP marker was validated using a lineage-tracing mouse line. POSTN expression was elevated in Brahman FAPs (P \u3c 0.0001) and DMD patients (P \u3c 0.01) but not in aged humans. Strong interactions between vascular cells and FAPs were also identified. Conclusions Our study demonstrates the feasibility of beef cattle as a model for studying IMF and IMC. We illustrate the FAP programming during intramuscular adipogenesis and fibrogenesis and reveal the reliability of CFD as a predictor and biomarker of IMF accumulation in cattle and humans