Phonological studies of ATR harmony have led to advances in autosegmental phonology, markedness theory, and locality. Nevertheless, many of our theoretical assumptions may have been based on misanalyzed data or non-rigorous typological assumptions. For example, detailed acoustic and/or articulatory studies have shown that transparent vowels are not always transparent (Gick et al 2006, Richart &...

Finnish vowel harmony rules require that if the vowel in the first syllable of a word belongs to one of two vowel sets, then all subsequent vowels in that word must belong either to the same set or to a neutral set. A harmony mismatch between two syllables containing vowels from the opposing sets thus signals a likely word boundary. We report five experiments showing that Finnish listeners can ...

Even adults with no formal music lessons have implicit musical knowledge acquired through exposure to the music of their culture. Two of these abilities are knowledge of key membership (which notes belong in a key) and harmony (chord progressions). Studies to date suggest that perception of harmony emerges around 5-6 years of age. Using simple tasks, we found that formal music training influenc...

The requirement of proof-theoretic harmony has played a pivotal role in a number of debates in the philosophy of logic. Different authors have attempted to precisify the notion in different ways. Among these, three proposals have been prominent in the literature: Harmony-as-conservative extension, Harmony-as-levelling procedure and Tennant’s Harmony-as-deductive equilibrium. In this paper I pro...

In the proof-theoretic semantics approach to meaning, harmony, requiring a balance between introduction-rules (I-rules) and elimination rules (E-rules) within a meaning conferring natural-deduction proof-system, is a central notion. In this paper, we consider two notions of harmony that were proposed in the literature: 1. GE-harmony, requiring a certain form of the E-rules, given the form of th...

Harmony search (HS) was introduced in 2001 as a heuristic population-based optimisation algorithm. Since then HS has become a popular alternative to other heuristic algorithms like simulated annealing and particle swarm optimisation. However, some flaws, like the need for parameter tuning, were identified and have been a topic of study for much research over the last 10 years. Many variants of ...

Artificial language learning experiments typically show non-categorical results after training on categorical data. This is generally due to incomplete learning, but these can also reveal biases. One example that participants trained a vowel harmony with alternating and non-alternating affixes prefer the affix in harmonic contexts (Finley 2021). In this paper, I (i) preference for items replica...

This paper presents an aggregation approach of similarity measures for ontology matching called n-Harmony. The n-Harmony measure identifies top-n highest values in each similarity matrix to assign a weight to the corresponding similarity measure for aggregation. We can also exclude noisy similarity measures that have a low weight and the n-Harmony outperforms previous methods in our experimenta...

Harmony search algorithm is a meta-heuristic optimization method imitating the music improvisation process, where musicians improvise their instruments’ pitches searching for a perfect state of harmony. First, an improved harmony search algorithm is presented using the concept of swarm intelligence. Next, it is employed for training feedforward neural networks for three benchmark classification...

We, in 1956 the Department of Architecture at the Budapest University of Technology and Economics, decided to start an extensive color harmony experiment. The experimental work, the collation, and processing of the collected data, lasting 50 years, was completed in 2006. The experiments described in this article are based on earlier experimental results obtained from investigation into the harm...