Natural Language Does Not Emerge 'Naturally' in Multi-Agent Dialog

A number of recent works have proposed techniques for end-to-end learning of communication protocols among cooperative multi-agent populations, and have simultaneously found the emergence of grounded human-interpretable language in the protocols developed by the agents, all learned without any human supervision! In this paper, using a Task and Tell reference game between two agents as a testbed, we present a sequence of 'negative' results culminating in a 'positive' one -- showing that while most agent-invented languages are effective (i.e. achieve near-perfect task rewards), they are decidedly not interpretable or compositional. In essence, we find that natural language does not emerge 'naturally', despite the semblance of ease of natural-language-emergence that one may gather from recent literature. We discuss how it is possible to coax the invented languages to become more and more human-like and compositional by increasing restrictions on how two agents may communicate.Comment: 9 pages, 7 figures, 2 tables, accepted at EMNLP 2017 as short pape

Arguing Using Opponent Models

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Adversarial Learning for Neural Dialogue Generation

In this paper, drawing intuition from the Turing test, we propose using adversarial training for open-domain dialogue generation: the system is trained to produce sequences that are indistinguishable from human-generated dialogue utterances. We cast the task as a reinforcement learning (RL) problem where we jointly train two systems, a generative model to produce response sequences, and a discriminator---analagous to the human evaluator in the Turing test--- to distinguish between the human-generated dialogues and the machine-generated ones. The outputs from the discriminator are then used as rewards for the generative model, pushing the system to generate dialogues that mostly resemble human dialogues. In addition to adversarial training we describe a model for adversarial {\em evaluation} that uses success in fooling an adversary as a dialogue evaluation metric, while avoiding a number of potential pitfalls. Experimental results on several metrics, including adversarial evaluation, demonstrate that the adversarially-trained system generates higher-quality responses than previous baselines

Comprehensibility and the basic structures of dialogue

The study of what makes utterances difficult or easy to understand is one of the central topics of research in comprehension. It is both theoretically attractive and useful in practice. The more we know about difficulties in understanding the more we know about understanding. And the better we grasp typical problems of understanding in certain types of discourse and for certain recipients the better we can overcome these problems and the better we can advise people whose job it is to overcome such problems. It is therefore not surprising that comprehensibility has been the object of much reflection as far back as the days of classical rhetoric and that it is a center of lively interest in several present-day scientific disciplines, ranging from artificial intelligence and educational psychology to linguistics

Text reconstruction activities and teaching language forms

Even though there is a broad consensus that teaching language forms is facilitative or even necessary in some contexts, there are still disagreements concerning, among other things, how formal aspects of the target language should be taught. One important area of controversy is whether pedagogic intervention should be input-oriented, emphasizing comprehension of the form- meaning mappings represented by specific linguistic features or output-based, requiring learners to produce these features accurately in gradually more communicative activities. The present paper focuses on the latter of these two options and, basing on the claims of Swain‘s (1985, 1995) output hypothesis, it aims to demonstrates how text-reconstruction activities in which learners collaboratively produce written output trigger noticing, hypothesis-testing and metalinguistic reflection on language use. It presents a psycholinguistic and sociolinguistic rationale for the use of such tasks, discusses the types of such activities, provides an overview of research projects investigating their application and, finally, offers a set of implications for classroom use as well as suggestions for further research in this area

A Multilingual Virtual Guide for Self-Attachment Technique

In this work, we propose a computational framework that leverages existing out-of-language data to create a conversational agent for the delivery of Self-Attachment Technique (SAT) in Mandarin. Our framework does not require large-scale human translations, yet it achieves a comparable performance whilst also maintaining safety and reliability. We propose two different methods of augmenting available response data through empathetic rewriting. We evaluate our chatbot against a previous, English-only SAT chatbot through non-clinical human trials (N=42), each lasting five days, and quantitatively show that we are able to attain a comparable level of performance to the English SAT chatbot. We provide qualitative analysis on the limitations of our study and suggestions with the aim of guiding future improvements

Design and implementation of a user-oriented speech recognition interface: the synergy of technology and human factors

The design and implementation of a user-oriented speech recognition interface are described. The interface enables the use of speech recognition in so-called interactive voice response systems which can be accessed via a telephone connection. In the design of the interface a synergy of technology and human factors is achieved. This synergy is very important for making speech interfaces a natural and acceptable form of human-machine interaction. Important concepts such as interfaces, human factors and speech recognition are discussed. Additionally, an indication is given as to how the synergy of human factors and technology can be realised by a sketch of the interface's implementation. An explanation is also provided of how the interface might be integrated in different applications fruitfully