AISHELL-1: An Open-Source Mandarin Speech Corpus and A Speech Recognition Baseline

An open-source Mandarin speech corpus called AISHELL-1 is released. It is by far the largest corpus which is suitable for conducting the speech recognition research and building speech recognition systems for Mandarin. The recording procedure, including audio capturing devices and environments are presented in details. The preparation of the related resources, including transcriptions and lexicon are described. The corpus is released with a Kaldi recipe. Experimental results implies that the quality of audio recordings and transcriptions are promising.Comment: Oriental COCOSDA 201

Statistical inference for transfer learning with high-dimensional quantile regression

Transfer learning has become an essential technique to exploit information from the source domain to boost performance of the target task. Despite the prevalence in high-dimensional data, heterogeneity and/or heavy tails are insufficiently accounted for by current transfer learning approaches and thus may undermine the resulting performance. We propose a transfer learning procedure in the framework of high-dimensional quantile regression models to accommodate the heterogeneity and heavy tails in the source and target domains. We establish error bounds of the transfer learning estimator based on delicately selected transferable source domains, showing that lower error bounds can be achieved for critical selection criterion and larger sample size of source tasks. We further propose valid confidence interval and hypothesis test procedures for individual component of high-dimensional quantile regression coefficients by advocating a double transfer learning estimator, which is the one-step debiased estimator for the transfer learning estimator wherein the technique of transfer learning is designed again. Simulation results demonstrate that the proposed method exhibits some favorable performances, further corroborating our theoretical results.Comment: 122 pages, 6 figure

FedLE: Federated Learning Client Selection with Lifespan Extension for Edge IoT Networks

Federated learning (FL) is a distributed and privacy-preserving learning framework for predictive modeling with massive data generated at the edge by Internet of Things (IoT) devices. One major challenge preventing the wide adoption of FL in IoT is the pervasive power supply constraints of IoT devices due to the intensive energy consumption of battery-powered clients for local training and model updates. Low battery levels of clients eventually lead to their early dropouts from edge networks, loss of training data jeopardizing the performance of FL, and their availability to perform other designated tasks. In this paper, we propose FedLE, an energy-efficient client selection framework that enables lifespan extension of edge IoT networks. In FedLE, the clients first run for a minimum epoch to generate their local model update. The models are partially uploaded to the server for calculating similarities between each pair of clients. Clustering is performed against these client pairs to identify those with similar model distributions. In each round, low-powered clients have a lower probability of being selected, delaying the draining of their batteries. Empirical studies show that FedLE outperforms baselines on benchmark datasets and lasts more training rounds than FedAvg with battery power constraints.Comment: 6 pages, 6 figures, accepted to 2023 IEEE International Conference on Communications (ICC 2023

Design driven user study workshop for Chinese startup innovation

The paper illustrates a serial user study workshop designed for startups seeking disruptive innovation and business opportunities based on the lean process from the point view of user-centered design approach. In the Chinese market, business process moves fast. The product development cycle is relatively short which makes it easy to be interrupted and changed. Making sure the product is targeting the right marketing segment is the key to business success. Therefore, innovation has to be created on the true needs of the accurate end users. User-centered design approaches have the natural advantage to forge innovation by defining the problems of the existing products usage for the users and creating the solution that seamlessly meets the potential demands of the product users. This capability of user-centered design is extremely suitable for the early stage of the startup innovation process especially in the customer identification, market positioning, and business model generation. User study is located in the core of this user-centered innovation process. Performing a good user study ensures the product is aimed at users’ needs, which guarantees once the product is given birth it is already well-positioned in the market sharing. This is the key to the success of startup business. In this paper, a serial workshop covers the topics from what are the user study methods suitable for the lean startup innovation, how to conduct an effective interview, and how to synthesize users’ insights and find new business opportunities. By doing the workshop we try to answer the following questions which ultimately influence the nurturing process in the incubator about how design thinking can intervene to create radical innovation in startup teams: why the design driven user study is so important to the startup business? What is design thinking in the non-design background startuper’s mind and how can they incorporate the mindset in the business operation? What Chinese business environment impacts in the innovation process and how could the startups position the empathy for the users as the key for the product success

AHRC Design Fellows: Challenges of the future: Mobility

In December 2019, the Arts and Humanities Research Council (AHRC) issued a call for a three-month Design Fellowship at a Design Research Centre of Excellence in Mobility Research to review the British university-led design research landscape working on The Future of Mobility. The aim was to better understand the role of design research in this challenging area, the economic and social impact of design research and provide recommendations about how to support design researchers in academia, highlighting their contributions to the country as a whole. This resulting report provides insights through the lens of design professionals about design research in the context of the Future of Mobility – key research topics, where design is and is not used, emerging areas of design research in mobility, collaborations between design and other disciplines, the commercial value of design research, identified skill-sets for mobility design researchers, and supporting infrastructure

Robert Brandom on Semantics and the Objectivity of Conceptual Norms

In arguing for an inferentialist understanding of conceptual contents, Robert Brandom claims that a fundamental feature of the norms that govern our concept-using practices is that they are objective. Brandom believes that the objective aspect of conceptual norms is grounded in the distinction between the normative status of a performance being a correct (or incorrect) application of a concept and the normative attitude of a performance being taken as a correct (or incorrect) application. In the first two sections of this thesis, I will offer an overview of Brandom’s inferential approach to semantics and his normative approach to pragmatics. In the third section, I will explain what Brandom calls a “deontic scorekeeping” model of discursive practice, which is the result of combining his inferential semantics and normative pragmatics. In the fourth section, I will explain why the notion of normative attitude matters for Brandom’s understanding of conceptual norms. This gives rise to his normative phenomenalism, which is the idea that normative statuses are instituted by normative attitudes. I will then point out that, because Brandom understands normative attitude as a kind of communal assessment, he needs to demonstrate how it is that conceptual norms have an essentially objective aspect, for without this his argument will be unable to avoid collapsing into the position that whatever the community takes to be correct is correct. Finally, I will examine Brandom’s account of the objectivity that he takes conceptual norms to have and further argue that although this account satisfies a weak notion of objectivity, it is not compatible with Brandom’s overall phenomenalist approach toward conceptual norms

Towards transparency between the autonomous vehicle and the pedestrian

This paper addresses the new problem of transparency in relation to pedestrians’ interaction with driverless vehicles, arising from their lack of visual cues to replace those currently provided by the visible behaviours of the driver. It reports two observational investigations of the affordances of the street, one looking at the street as static environment, the other at pedestrian behaviours in relation to driven vehicles. The findings of the research were used to identify the decision-making process, timings and exhibited behaviours of pedestrians and drivers in the street environment