52,699 research outputs found
Rating scale development: a multistage exploratory sequential design
The project chosen to showcase the application of the exploratory sequential design in second/ foreign (L2) language assessment comes from the context of rating scale development and focuses on the development of a set of scales for a suite of high-stakes L2 speaking tests. The assessment of speaking requires assigning scores to a speech sample in a systematic fashion by focusing on explicitly defined criteria which describe different levels of performance (Ginther 2013). Rating scales are the instruments used in this evaluation process, and they can be either holistic (i.e. providing a global overall assessment) or analytic (i.e. providing an independent evaluations for a number of assessment criteria, e.g. Grammar, Vocabulary, Organisation, etc.). The discussion in this chapter is framed within the context of rating scales in speaking assessment. However, it is worth noting that the principles espoused, stages employed and decisions taken during the development process have wider applicability to performance assessment in general
Compositional Morphology for Word Representations and Language Modelling
This paper presents a scalable method for integrating compositional
morphological representations into a vector-based probabilistic language model.
Our approach is evaluated in the context of log-bilinear language models,
rendered suitably efficient for implementation inside a machine translation
decoder by factoring the vocabulary. We perform both intrinsic and extrinsic
evaluations, presenting results on a range of languages which demonstrate that
our model learns morphological representations that both perform well on word
similarity tasks and lead to substantial reductions in perplexity. When used
for translation into morphologically rich languages with large vocabularies,
our models obtain improvements of up to 1.2 BLEU points relative to a baseline
system using back-off n-gram models.Comment: Proceedings of the 31st International Conference on Machine Learning
(ICML
How do you say ‘hello’? Personality impressions from brief novel voices
On hearing a novel voice, listeners readily form personality impressions of that speaker. Accurate or not, these impressions are known to affect subsequent interactions; yet the underlying psychological and acoustical bases remain poorly understood. Furthermore, hitherto studies have focussed on extended speech as opposed to analysing the instantaneous impressions we obtain from first experience. In this paper, through a mass online rating experiment, 320 participants rated 64 sub-second vocal utterances of the word ‘hello’ on one of 10 personality traits. We show that: (1) personality judgements of brief utterances from unfamiliar speakers are consistent across listeners; (2) a two-dimensional ‘social voice space’ with axes mapping Valence (Trust, Likeability) and Dominance, each driven by differing combinations of vocal acoustics, adequately summarises ratings in both male and female voices; and (3) a positive combination of Valence and Dominance results in increased perceived male vocal Attractiveness, whereas perceived female vocal Attractiveness is largely controlled by increasing Valence. Results are discussed in relation to the rapid evaluation of personality and, in turn, the intent of others, as being driven by survival mechanisms via approach or avoidance behaviours. These findings provide empirical bases for predicting personality impressions from acoustical analyses of short utterances and for generating desired personality impressions in artificial voices
Multimodal Grounding for Language Processing
This survey discusses how recent developments in multimodal processing
facilitate conceptual grounding of language. We categorize the information flow
in multimodal processing with respect to cognitive models of human information
processing and analyze different methods for combining multimodal
representations. Based on this methodological inventory, we discuss the benefit
of multimodal grounding for a variety of language processing tasks and the
challenges that arise. We particularly focus on multimodal grounding of verbs
which play a crucial role for the compositional power of language.Comment: The paper has been published in the Proceedings of the 27 Conference
of Computational Linguistics. Please refer to this version for citations:
https://www.aclweb.org/anthology/papers/C/C18/C18-1197
Improving Search through A3C Reinforcement Learning based Conversational Agent
We develop a reinforcement learning based search assistant which can assist
users through a set of actions and sequence of interactions to enable them
realize their intent. Our approach caters to subjective search where the user
is seeking digital assets such as images which is fundamentally different from
the tasks which have objective and limited search modalities. Labeled
conversational data is generally not available in such search tasks and
training the agent through human interactions can be time consuming. We propose
a stochastic virtual user which impersonates a real user and can be used to
sample user behavior efficiently to train the agent which accelerates the
bootstrapping of the agent. We develop A3C algorithm based context preserving
architecture which enables the agent to provide contextual assistance to the
user. We compare the A3C agent with Q-learning and evaluate its performance on
average rewards and state values it obtains with the virtual user in validation
episodes. Our experiments show that the agent learns to achieve higher rewards
and better states.Comment: 17 pages, 7 figure
Ecological IVIS design : using EID to develop a novel in-vehicle information system
New in-vehicle information systems (IVIS) are emerging which purport to encourage more environment friendly or ‘green’ driving. Meanwhile, wider concerns about road safety and in-car distractions remain. The ‘Foot-LITE’ project is an effort to balance these issues, aimed at achieving safer and greener driving through real-time driving information, presented via an in-vehicle interface which facilitates the desired behaviours while avoiding negative consequences. One way of achieving this is to use ecological interface design (EID) techniques. This article presents part of the formative human-centred design process for developing the in-car display through a series of rapid prototyping studies comparing EID against conventional interface design principles. We focus primarily on the visual display, although some development of an ecological auditory display is also presented. The results of feedback from potential users as well as subject matter experts are discussed with respect to implications for future interface design in this field
- …