TSUP Speaker Diarization System for Conversational Short-phrase Speaker Diarization Challenge

This paper describes the TSUP team's submission to the ISCSLP 2022 conversational short-phrase speaker diarization (CSSD) challenge which particularly focuses on short-phrase conversations with a new evaluation metric called conversational diarization error rate (CDER). In this challenge, we explore three kinds of typical speaker diarization systems, which are spectral clustering(SC) based diarization, target-speaker voice activity detection(TS-VAD) and end-to-end neural diarization(EEND) respectively. Our major findings are summarized as follows. First, the SC approach is more favored over the other two approaches under the new CDER metric. Second, tuning on hyperparameters is essential to CDER for all three types of speaker diarization systems. Specifically, CDER becomes smaller when the length of sub-segments setting longer. Finally, multi-system fusion through DOVER-LAP will worsen the CDER metric on the challenge data. Our submitted SC system eventually ranks the third place in the challenge

AdaMEC: Towards a Context-Adaptive and Dynamically-Combinable DNN Deployment Framework for Mobile Edge Computing

With the rapid development of deep learning, recent research on intelligent and interactive mobile applications (e.g., health monitoring, speech recognition) has attracted extensive attention. And these applications necessitate the mobile edge computing scheme, i.e., offloading partial computation from mobile devices to edge devices for inference acceleration and transmission load reduction. The current practices have relied on collaborative DNN partition and offloading to satisfy the predefined latency requirements, which is intractable to adapt to the dynamic deployment context at runtime. AdaMEC, a context-adaptive and dynamically-combinable DNN deployment framework is proposed to meet these requirements for mobile edge computing, which consists of three novel techniques. First, once-for-all DNN pre-partition divides DNN at the primitive operator level and stores partitioned modules into executable files, defined as pre-partitioned DNN atoms. Second, context-adaptive DNN atom combination and offloading introduces a graph-based decision algorithm to quickly search the suitable combination of atoms and adaptively make the offloading plan under dynamic deployment contexts. Third, runtime latency predictor provides timely latency feedback for DNN deployment considering both DNN configurations and dynamic contexts. Extensive experiments demonstrate that AdaMEC outperforms state-of-the-art baselines in terms of latency reduction by up to 62.14% and average memory saving by 55.21%

The FlySpeech Audio-Visual Speaker Diarization System for MISP Challenge 2022

This paper describes the FlySpeech speaker diarization system submitted to the second \textbf{M}ultimodal \textbf{I}nformation Based \textbf{S}peech \textbf{P}rocessing~(\textbf{MISP}) Challenge held in ICASSP 2022. We develop an end-to-end audio-visual speaker diarization~(AVSD) system, which consists of a lip encoder, a speaker encoder, and an audio-visual decoder. Specifically, to mitigate the degradation of diarization performance caused by separate training, we jointly train the speaker encoder and the audio-visual decoder. In addition, we leverage the large-data pretrained speaker extractor to initialize the speaker encoder

Mobile V-MoEs: Scaling Down Vision Transformers via Sparse Mixture-of-Experts

Sparse Mixture-of-Experts models (MoEs) have recently gained popularity due to their ability to decouple model size from inference efficiency by only activating a small subset of the model parameters for any given input token. As such, sparse MoEs have enabled unprecedented scalability, resulting in tremendous successes across domains such as natural language processing and computer vision. In this work, we instead explore the use of sparse MoEs to scale-down Vision Transformers (ViTs) to make them more attractive for resource-constrained vision applications. To this end, we propose a simplified and mobile-friendly MoE design where entire images rather than individual patches are routed to the experts. We also propose a stable MoE training procedure that uses super-class information to guide the router. We empirically show that our sparse Mobile Vision MoEs (V-MoEs) can achieve a better trade-off between performance and efficiency than the corresponding dense ViTs. For example, for the ViT-Tiny model, our Mobile V-MoE outperforms its dense counterpart by 3.39% on ImageNet-1k. For an even smaller ViT variant with only 54M FLOPs inference cost, our MoE achieves an improvement of 4.66%

The effect of dietary calcium inclusion on broiler gastrointestinal pH: quantification and method optimization

There is little consensus as to the most appropriate methodology for the measurement of gastrointestinal pH in chickens. An experiment was conducted to establish the optimum sampling method for the determination of broiler digesta pH in birds fed differing levels of dietary calcium. Ross 308 broilers (n = 60) were fed one of two experimental diets, one containing 0.8% monocalcium phosphate and 2% limestone and one containing 0.4% monocalcium phosphate and 1% limestone. Four factors were investigated to determine the most appropriate method of measuring broiler gastrointestinal digesta pH: removal from the tract, prolonged air exposure, altering the temperature of the assay, and controlling the water content of the digesta. The conditions were assessed at bird ages from 7 to 42 d post hatch. Dietary Ca content had no significant effect on in situ pH, but it contributed towards variance in ex situ pH of both gizzard and duodenum digesta

A tool kit for rapid cloning and expression of recombinant antibodies

Over the last four decades, molecular cloning has evolved tremendously. Efficient products allowing assembly of multiple DNA fragments have become available. However, cost-effective tools for engineering antibodies of different specificities, isotypes and species are still needed for many research and clinical applications in academia. Here, we report a method for one-step assembly of antibody heavy- and light-chain DNAs into a single mammalian expression vector, starting from DNAs encoding the desired variable and constant regions, which allows antibodies of different isotypes and specificity to be rapidly generated. As a proof of principle we have cloned, expressed and characterized functional recombinant tumor-associated antigen-specific chimeric IgE/κ and IgG(1)/κ, as well as recombinant grass pollen allergen Phl p 7 specific fully human IgE/λ and IgG(4)/λ antibodies. This method utilizing the antibody expression vectors, available at Addgene, has many applications, including the potential to support simultaneous processing of antibody panels, to facilitate mechanistic studies of antigen-antibody interactions and to conduct early evaluations of antibody functions

Survival benefit of local consolidative therapy for patients with single-organ metastatic pancreatic cancer: a propensity score-matched cross-sectional study based on 17 registries

BackgroundThe continuous exploration of oligometastatic disease has led to the remarkable achievements of local consolidative therapy (LCT) and favorable outcomes for this disease. Thus, this study investigated the potential benefits of LCT in patients with single-organ metastatic pancreatic ductal adenocarcinoma (PDAC).MethodsPatients with single-organ metastatic PDAC diagnosed between 2010 - 2019 were identified from the Surveillance, Epidemiology, and End Results (SEER) database. Propensity score matching (PSM) was performed to minimize selection bias. Factors affecting survival were assessed by Cox regression analysis and Kaplan-Meier estimates.ResultsA total of 12900 patients were identified from the database, including 635 patients who received chemotherapy combined with LCT with a 1:1 PSM with patients who received only chemotherapy. Patients with single-organ metastatic PDAC who received chemotherapy in combination with LCT demonstrated extended median overall survival (OS) by approximately 57%, more than those who underwent chemotherapy alone (11 vs. 7 months, p < 0.001). Furthermore, the multivariate Cox regression analysis revealed that patients that received LCT, younger age (< 65 years), smaller tumor size (< 50 mm), and lung metastasis (reference: liver) were favorable prognostic factors for patients with single-organ metastatic PDAC.ConclusionThe OS of patients with single-organ metastatic pancreatic cancer who received LCT may be prolonged compared to those who received only chemotherapy. Nevertheless, additional prospective randomized clinical trials are required to support these findings

[pain]Byte VR Storytelling & Classical Ballet

This initial stage paper focuses on the Virtual Reality (VR) experience of the [pain]Byte ballet. The live and VR experience debut October 1st 2017, as part of the Brighton digital festival. Specifically, the development of the VR environment to compliment live performance by using the same choreography to create an option capture element of the VR story telling experience. Reviewing Virtual & Alternative reality gaming & storytelling works and the use of VR for chronic pain management (Chen, Win). Does the VR experience compare to that of the live theatre for the audience? The data visualisations and VR environment will be continuations of the Network Simulator, [data]Storm 2015. We are visualising and comparing the pain pathway system to that of a social network. Linking pain signals to viral/negative messaging for some of the visuals. The main purpose of the pieces links to how “we" present ourselves online, these better or veiled versions of ourselves. For chronic pain sufferers, this can be daily activity in the real world. The paper concludes by identifying some future directions for the research project. The Ballet: [pain]Byte is a data driven dance classical ballet performance and VR (virtual reality) experience. [pain]Byte, is about chronic pain and biomedical engineering, in particular the use of implanted technology - neuromodulation (Al-Kaisey et al). Using data as a medium for storytelling, what it means to be in chronic pain. The live augmented theatre and VR experience research focuses on how an audience’s exposure and understanding are impacted by the difference mediums used for [pain]byte

Structural and Mutational Analysis of Functional Differentiation between Synaptotagmins-1 and -7

Synaptotagmins are known to mediate diverse forms of Ca2+-triggered exocytosis through their C2 domains, but the principles underlying functional differentiation among them are unclear. Synaptotagmin-1 functions as a Ca2+ sensor in neurotransmitter release at central nervous system synapses, but synaptotagmin-7 does not, and yet both isoforms act as Ca2+ sensors in chromaffin cells. To shed light into this apparent paradox, we have performed rescue experiments in neurons from synaptotagmin-1 knockout mice using a chimera that contains the synaptotagmin-1 sequence with its C2B domain replaced by the synaptotagmin-7 C2B domain (Syt1/7). Rescue was not achieved either with the WT Syt1/7 chimera or with nine mutants where residues that are distinct in synaptotagmin-7 were restored to those present in synaptotagmin-1. To investigate whether these results arise because of unique conformational features of the synaptotagmin-7 C2B domain, we determined its crystal structure at 1.44 Å resolution. The synaptotagmin-7 C2B domain structure is very similar to that of the synaptotagmin-1 C2B domain and contains three Ca2+-binding sites. Two of the Ca2+-binding sites of the synaptotagmin-7 C2B domain are also present in the synaptotagmin-1 C2B domain and have analogous ligands to those determined for the latter by NMR spectroscopy, suggesting that a discrepancy observed in a crystal structure of the synaptotagmin-1 C2B domain arose from crystal contacts. Overall, our results suggest that functional differentiation in synaptotagmins arises in part from subtle sequence changes that yield dramatic functional differences