Is it Possible to Preserve a Language using only Data?

Many of our spoken languages are endangered and rapidly becoming extinct. Due to this, there are attempts to preserve as many of those languages as possible. One preservation approach is combining data collection and artificial intelligence-based language models.

A parametric analysis of procedural fidelity errors following mastery of a task: A translational study.

Procedural fidelity is defined as the extent to which the independent variable is implemented as prescribed. Research using computerized tasks has shown that fidelity errors involving consequences for behavior can hinder skill acquisition. However, studies examining the effects of these errors once skills have been mastered are lacking.

The effects of implementing phenomenology in a deep neural network.

There have been several recent attempts at using Artificial Intelligence systems to model aspects of consciousness (Gamez, 2008; Reggia, 2013). Deep Neural Networks have been given additional functionality in the present attempt, allowing them to emulate phenological aspects of consciousness by self-generating information representing multi-modal inputs as either sounds or images. We added these functions to determine whether knowledge of the input's modality aids the networks' learning.

The effects of changeover delays on local choice.

In concurrent schedules with a changeover delay (COD), choice often strongly favours the just-reinforced alternative immediately after a reinforcer delivery. These 'preference pulses' may be caused by a change in reinforcer availability created by the COD, and/or because the COD decreases the overall probability of switching. We investigated which explanation better accounts for preference pulses by arranging concurrent schedules that allowed us to separate the COD's effects on reinforcer availability from its effects on the probability of switching.

Training reinforcement rates, resistance to extinction, and the role of context in reinstatement.

Behavior reduced as a consequence of extinction or intervention can relapse. According to behavioral momentum theory, the extent to which behavior persists and relapses once it has been eliminated depends on the relative training reinforcement rate among discriminative stimuli. In addition, studies of context renewal reveal that relapse depends on the similarity between the training stimulus context and the test stimulus context following disruption by extinction.

Steady-state choice between four alternatives obeys the constant-ratio rule.

We investigated why violations to the constant-ratio rule, an assumption of the generalized matching law, occur in procedures that arrange frequent changes to reinforcer ratios. Our investigation produced steady-state data and compared them with data from equivalent, frequently changing procedures. Six pigeons responded in a four-alternative concurrent-schedule experiment with an arranged reinforcer-rate ratio of 27:9:3:1.

Law of effect models and choice between many alternatives.

Data from five experiments on choice between more than two variable-interval schedules were modeled with different equations for the Law of Effect. Navakatikyan's (2007) component-functions models with three, four and five free parameters were compared with Stevens' (1957), Herrnstein's (1970) and Davison and Hunter's (1976) equations. These latter models are consistent with the generalized-matching principle, whereas Navakatikyan's models are not.