“听音辨形”——英语现场新闻听力理解的先决条件

从英语现场新闻的语音规律和语境功能的角度认识"听音辨形"的实现途径,从语音认知本质的角度尝试提高"听音辨形"的教学方法,认为英语现场新闻语音在语流中的音变规律是"听音辨形"的关键凭借,其背景声音有时候是"听音辨形"的有效辅助;由于"感知磁效"现象表明听者通过"原型音"来识别语音变体,这就意味着要从本质上提高"听音辨形",就应拓展听者识别语音变体的能力,因而听写是从根本上提高"听音辨形"的有效方法.     

Graphon estimation via nearest-neighbour algorithm and two-dimensional fused-lasso denoising

We propose a class of methods for graphon estimation based on exploiting connections with nonparametric regression. The idea is to construct an ordering of the nodes in the network, similar in spirit to Chan & Airoldi (2014). However, rather than considering orderings based only on the empirical degree as in Chan & Airoldi (2014), we use the nearest-neighbour algorithm which is an approximative solution to the travelling salesman problem. This algorithm in turn can handle general distances $\widehat{d}$ between the nodes, allowing us to incorporate rich information from the network. Once an ordering is constructed, we formulate a two-dimensional-grid graph-denoising problem that we solve through fused-lasso regularization. For particular choices of the metric $\widehat{d}$, we show that the corresponding two-step estimator can attain competitive rates when the true model is the stochastic block model, and when the underlying graphon is piecewise Hölder or has bounded variation.