Development of an Open Source Natural Language Generation Tool for Finnish

Hämäläinen, Mika; Rueter, Jack

doi:10.18653/v1/w18-0205

Cited by 11 publications

(11 citation statements)

References 2 publications

(2 reference statements)

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“…If a verb gets changed in the sentence, its case government rule might be different from the original verb. In this case, we apply Syntax Maker (Hämäläinen and Rueter 2018) to resolve the case of the complements of the new verb. Taking these two different linguistic rules into account while generating results in more syntactic output.…”

Section: Generation Of Poemsmentioning

confidence: 99%

Computational Understanding, Generation and Evaluation of Creative Expressions

Alnajjar¹

2021

Preprint

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Computational creativity has received a good amount of research interest in generating creative artefacts programmatically. At the same time, research has been conducted in computational aesthetics, which essentially tries to analyse creativity exhibited in art. This thesis aims to unite these two distinct lines of research in the context of natural language generation by building, from models for interpretation and generation, a cohesive whole that can assess its own generations. I present a novel method for interpreting one of the most difficult rhetoric devices in the figurative use of language: metaphors. The method does not rely on hand-annotated data and it is purely data-driven. It obtains the state of the art results and is comparable to the interpretations given by humans. We show how a metaphor interpretation model can be used in generating metaphors and metaphorical expressions. Furthermore, as a creative natural language generation task, we demonstrate assigning creative names to colours using an algorithmic approach that leverages a knowledge base of stereotypical associations for colours. Colour names produced by the approach were favoured by human judges to names given by humans 70% of the time. A genetic algorithm-based method is elaborated for slogan generation. The use of a genetic algorithm makes it possible to model the generation of text while optimising multiple fitness functions, as part of the evolutionary process, to assess the aesthetic quality of the output. Our evaluation indicates that having multiple balanced aesthetics outperforms a single maximised aesthetic. From an interplay of neural networks and the traditional AI approach of genetic algorithms, we present a symbiotic framework. This is called the master-apprentice framework. This makes it possible for the system to produce more diverse output as the neural network can learn from both the genetic algorithm and real people. The master-apprentice framework emphasises a strong theoretical foundation for the creative problem one seeks to solve. From this theoretical foundation, a reasoned evaluation method can be derived. This thesis presents two different evaluation practices based on two different theories on computational creativity. This research is conducted in two distinct practical tasks: pun generation in English and poetry generation in Finnish.

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Section: Generation Of Poemsmentioning

confidence: 99%

Computational Understanding, Generation and Evaluation of Creative Expressions

Alnajjar¹

2021

Preprint

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“…We are interested in seeing what the effect of the automatically adapted dialect is on computer generated text. We use an existing Finnish poem generator (Hämäläinen 2018) that produces standard Finnish (SF) text as it relies heavily on hand defined syntactic structures that are filled with lemmatized words that are inflected with a normative Finnish morphological generator by using a tool called Syntax Maker (Hämäläinen and Rueter 2018). We use this generator to generate 10 different poems.…”

Section: Effect On Perceived Creativitymentioning

confidence: 99%

Automatic Dialect Adaptation in Finnish and its Effect on Perceived Creativity

Hämäläinen¹,

Partanen²,

Alnajjar³

et al. 2020

Preprint

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We present a novel approach for adapting text written in standard Finnish to different dialects. We experiment with character level NMT models both by using a multi-dialectal and transfer learning approaches. The models are tested with over 20 different dialects. The results seem to favor transfer learning, although not strongly over the multi-dialectal approach. We study the influence dialectal adaptation has on perceived creativity of computer generated poetry. Our results suggest that the more the dialect deviates from the standard Finnish, the lower scores people tend to give on an existing evaluation metric. However, on a word association test, people associate creativity and originality more with dialect and fluency more with standard Finnish.

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“…In case government, the case of the complements of the verb depends on the verb itself. For this reason, we inflect words with an object relation with Syntax Maker (Hämäläinen and Rueter, 2018) to produce a grammatical surface form even if the predicate verb is changed.…”

Section: Mastermentioning

confidence: 99%

Let’s FACE it. Finnish Poetry Generation with Aesthetics and Framing

Hämäläinen¹,

Alnajjar

2019

Proceedings of the 12th International Conference on Natural Language Generation

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We present a creative poem generator for the morphologically rich Finnish language. Our method falls into the master-apprentice paradigm, where a computationally creative genetic algorithm teaches a BRNN model to generate poetry. We model several parts of poetic aesthetics in the fitness function of the genetic algorithm, such as sonic features, semantic coherence, imagery and metaphor. Furthermore, we justify the creativity of our method based on the FACE theory on computational creativity and take additional care in evaluating our system by automatic metrics for concepts together with human evaluation for aesthetics, framing and expressions.

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Development of an Open Source Natural Language Generation Tool for Finnish

Cited by 11 publications

References 2 publications

Computational Understanding, Generation and Evaluation of Creative Expressions

Computational Understanding, Generation and Evaluation of Creative Expressions

Automatic Dialect Adaptation in Finnish and its Effect on Perceived Creativity

Let’s FACE it. Finnish Poetry Generation with Aesthetics and Framing

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