End-to-end spoken language understanding using joint CTC loss and self-supervised, pretrained acoustic encoders

It is challenging to extract semantic meanings directly from audio signals in spoken language understanding (SLU), due to the lack of textual information. Popular end-to-end (E2E) SLU models utilize sequence-to-sequence automatic speech recognition (ASR) models to extract textual embeddings as input to infer semantics, which, however, require computationally expensive auto-regressive decoding. In this work, we leverage self-supervised acoustic encoders fine-tuned with Connectionist Temporal Classification (CTC) to extract textual embeddings and use joint CTC and SLU losses for utterance-level SLU tasks. Experiments show that our model achieves 4% absolute improvement over the the state-of-the-art (SOTA) dialogue act classification model on the DSTC2 dataset and 1.3% absolute improvement over the SOTA SLU model on the SLURP dataset.Comment: ICASSP 202

Genetic and Molecular Characterization of Flagellar Assembly in Shewanella oneidensis

Shewanella oneidensis is a highly motile organism by virtue of a polar flagellum. Unlike most flagellated bacteria, it contains only one major chromosome segment encoding the components of the flagellum with the exception of the motor proteins. In this region, three genes encode flagellinsaccording to the original genome annotation. However, we find that only flaA and flaB encode functional filament subunits. Although these two genesare under the control of different promoters, they are actively transcribed and subsequently translated, producing a considerable number of flagellin proteins. Additionally, both flagellins are able to interact with their chaperon FliS and are subjected to feedback regulation. Furthermore, FlaA and FlaB are glycosylated by a pathwayinvolving a major glycosylating enzyme,PseB, in spite of the lack of the majority of theconsensus glycosylation sites. In conclusion, flagellar assembly in S. oneidensis has novel features despite the conservation of homologous genes across taxa

Coordinated Replay Sample Selection for Continual Federated Learning

Continual Federated Learning (CFL) combines Federated Learning (FL), the decentralized learning of a central model on a number of client devices that may not communicate their data, and Continual Learning (CL), the learning of a model from a continual stream of data without keeping the entire history. In CL, the main challenge is \textit{forgetting} what was learned from past data. While replay-based algorithms that keep a small pool of past training data are effective to reduce forgetting, only simple replay sample selection strategies have been applied to CFL in prior work, and no previous work has explored coordination among clients for better sample selection. To bridge this gap, we adapt a replay sample selection objective based on loss gradient diversity to CFL and propose a new relaxation-based selection of samples to optimize the objective. Next, we propose a practical algorithm to coordinate gradient-based replay sample selection across clients without communicating private data. We benchmark our coordinated and uncoordinated replay sample selection algorithms against random sampling-based baselines with language models trained on a large scale de-identified real-world text dataset. We show that gradient-based sample selection methods both boost performance and reduce forgetting compared to random sampling methods, with our coordination method showing gains early in the low replay size regime (when the budget for storing past data is small).Comment: 7 pages, 6 figures, accepted to EMNLP (industry track

Analysis of the Association between Intestinal Microflora and Long-lived Elderly People

The intestinal microbiota is the cornerstone of the human intestinal microecosystem and plays an unnegligible role in the growth and health maintenance of the human body. In recent years, many studies have been committed to exploring the potential connection of gut flora and the elderly population. The changes of gut flora are affected by various factors such as age increase, disease, medication, living habits, nutritional structure, and the intestinal flora is expected to be applied to the comprehensive evaluation of elderly health and longevity in the future. Based on this, the research progress of the general elderly and its related influencing factors

A magnetic field sensor based on a dual S-tapered multimode fiber interferometer

A multimode interferometer (MMI) for the measurement of a magnetic field based on concatenated S-tapered fibers is proposed and experimentally demonstrated. Spectrally interrogated magnetic field sensing is achieved by integrating the proposed MMI with magnetic fluids. The magnetic sensitivity of the MMI reaches 0.011 dB Oe?1. Owing to its desirable advantages such as compactness, low cost, fast response and flexible structure, the proposed MMI is anticipated to find potential applications in in situ measurements of the magnetic field