An algorithm for word stress assignment in German compounds is introduced. First, a metrical tree is automatically derived from adjacent morpheme cohesion scores which are based on co-occurrence statistics. This tree is used to identify the stressed compound part by applying the compound stress rule of metrical phonology. Then the stressed syllable is identified within this compound part by means of a k-nearest-neighbor classifier using weighted vowel quantity and syllable coda type features. The accuracy of the metrical compound analysis amounted to 83%. Compound stress assignment was successful in 95%, and stress location within multi-syllable word stems in 84% of all cases
This paper tests the hypothesis that stress assignment to English compounds works on the basis of an...
The paper related to this dataset investigates how stress perception in German is affected by differ...
Previous research into Spanish stress assignment suggests that accentuation involves learning and st...
An algorithm for word stress assignment in German compounds is introduced. First, a metrical tree is...
Wagner P. Improving automatic prediction of German lexical stress. In: Proceedings of the 15th Inte...
Traditional approaches have regarded German stress to be predictable by localizing the initial stem ...
The purpose of this paper is to · describe an algorithm that has been developed to determine the str...
This paper proposes a stress detection method using word-length dependent classifiers. Most of the p...
For about four decades, phonological theories have claimed that word stress assignment depends on th...
Some English noun-noun compounds, e.g. ápple juice and téabag, usually have stress on the lefthand c...
This paper investigates the implementation of stress in English noun-noun compounds. First, a percep...
Stress assignment in learned compounds in contemporary English raises a number of theoretical proble...
QITL-4 - Proceedings of Quantitative Investigations in Theoretical Linguistics 4, 29.03.2011 - 31.03...
Stress is a useful cue for English word segmentation. A wide range of computational models have foun...
Abstract. We tested the ability of humans and machines (data mining techniques) to assign stress to ...
This paper tests the hypothesis that stress assignment to English compounds works on the basis of an...
The paper related to this dataset investigates how stress perception in German is affected by differ...
Previous research into Spanish stress assignment suggests that accentuation involves learning and st...
An algorithm for word stress assignment in German compounds is introduced. First, a metrical tree is...
Wagner P. Improving automatic prediction of German lexical stress. In: Proceedings of the 15th Inte...
Traditional approaches have regarded German stress to be predictable by localizing the initial stem ...
The purpose of this paper is to · describe an algorithm that has been developed to determine the str...
This paper proposes a stress detection method using word-length dependent classifiers. Most of the p...
For about four decades, phonological theories have claimed that word stress assignment depends on th...
Some English noun-noun compounds, e.g. ápple juice and téabag, usually have stress on the lefthand c...
This paper investigates the implementation of stress in English noun-noun compounds. First, a percep...
Stress assignment in learned compounds in contemporary English raises a number of theoretical proble...
QITL-4 - Proceedings of Quantitative Investigations in Theoretical Linguistics 4, 29.03.2011 - 31.03...
Stress is a useful cue for English word segmentation. A wide range of computational models have foun...
Abstract. We tested the ability of humans and machines (data mining techniques) to assign stress to ...
This paper tests the hypothesis that stress assignment to English compounds works on the basis of an...
The paper related to this dataset investigates how stress perception in German is affected by differ...
Previous research into Spanish stress assignment suggests that accentuation involves learning and st...