How to Do Things With Words

言语行为理论是哲学和语言学,特别是语言哲学和语用学的重要理论之一。与言语行为理论有关的诸多著作中,最重要最经典的是奥斯汀的How to Do Things with Words。然而这不是一本易读的书,为此作者分析了该书的脉络,给准备精读该书的读者提供一些参考。

How to Do Things with Words之脉络分析

An overview on spectral and spatial information fusion for hyperspectral image classification: Current trends and challenges

Image forensics has attracted wide attention during the past decade. However, most existing works aim at detecting a certain operation, which means that their proposed features usually depend on the investigated image operation and they consider only binary classification. This usually leads to misleading results if irrelevant features and/or classifiers are used. For instance, a JPEG decompressed image would be classified as an original or median filtered image if it was fed into a median filtering detector. Hence, it is important to develop forensic methods and universal features that can simultaneously identify multiple image operations. Based on extensive experiments and analysis, we find that any image operation, including existing anti-forensics operations, will inevitably modify a large number of pixel values in the original images. Thus, some common inherent statistics such as the correlations among adjacent pixels cannot be preserved well. To detect such modifications, we try to analyze the properties of local pixels within the image in the residual domain rather than the spatial domain considering the complexity of the image contents. Inspired by image steganalytic methods, we propose a very compact universal feature set and then design a multiclass classification scheme for identifying many common image operations. In our experiments, we tested the proposed features as well as several existing features on 11 typical image processing operations and four kinds of anti-forensic methods. The experimental results show that the proposed strategy significantly outperforms the existing forensic methods in terms of both effectiveness and universality.

Identification of Various Image Operations Using Residual-Based Features

Part I. The Theory 1. Introduction 2. Singers: Performance and Training 3. The Formula 4. The Theme 5. Songs and the Song 6. Writing and Oral Tradition Part II. The Application 7. Homer 8. The Odyssey 9. The Iliad 10. Some Notes on Medieval Epic Appendices Notes Index

The Singer of Tales

Video activity recognition, although being an emerging task, has been the subject of important research efforts due to the importance of its everyday applications. Surveillance by video cameras could benefit greatly by advances in this field. In the area of robotics, the tasks of autonomous navigation or social interaction could also take advantage of the knowledge extracted from live video recording. The aim of this paper is to survey the state-of-the-art techniques for video activity recognition while at the same time mentioning other techniques used for the same task that the research community has known for several years. For each of the analyzed methods, its contribution over previous works and the proposed approach performance are discussed.

https://www.mdpi.com/1424-8220/19/14/3160/pdf

Video Activity Recognition: State-of-the-Art.

The work presented here proposes two different ROS packages to enrich the teleoperation of the robot NAO: speech-based teleoperation (in Basque) and gesture-based teleoperation together with arm control. These packages have been used and evaluated in a human mimicking experiment. The tools offered can serve as a base for many applications.

Humanizing NAO robot teleoperation using ROS

Spontaneous talking gestures using Generative Adversarial Networks

Bertsolaritza, Basque improvised contest poetry, offers another sphere to develop robot body language and robot communication capabilities, that shares some similarities with theatrical performances. It is also a new area to work on social robotics. The work presented in this paper makes some steps forward in designing and implementing the set of behaviors the robots need to show in the stage to increase, on the one hand robot autonomy and on the other hand, credibility and sociability.

Singing minstrel robots, a means for improving social behaviors

This paper presents a neural-based approach for generating natural gesticulation movements for a humanoid robot enriched with other relevant social signals depending on sentiment processing. In particular, we take into account some simple head postures, voice parameters, and eyes colors as expressiveness enhancing elements. A Generative Adversarial Network (GAN) allows the proposed system to extend the variability of basic gesticulation movements while avoiding repetitive and monotonous behavior. Using sentiment analysis on the text that will be pronounced by the robot, we derive a value for emotion valence and coherently choose suitable parameters for the expressive elements. In this way, the robot has an adaptive expression generation during talking. Experiments validate the proposed approach by analyzing the contribution of all the factors to understand the naturalness perception of the robot behavior.

Igor Rodriguez

Papers

Video Activity Recognition: State-of-the-Art.

Humanizing NAO robot teleoperation using ROS

Spontaneous talking gestures using Generative Adversarial Networks

Singing minstrel robots, a means for improving social behaviors

Talking with Sentiment: Adaptive Expression Generation Behavior for Social Robots