Papers with t-SNE

3 papers
Parallax: Visualizing and Understanding the Semantics of Embedding Spaces via Algebraic Formulae (P19-3)

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Challenge: Embeddings are a fundamental component of many modern machine learning and natural language processing models.
Approach: They propose a tool for visualizing embedding spaces using parametric projections . they demonstrate the power of Parallax and propose % task-oriented approach .
Outcome: The proposed tool is based on two-dimensional projections without interpretable semantics . it enhances interpretability and allows for more fine-grained analysis .
Homophone2Vec: Embedding Space Analysis for Empirical Evaluation of Phonological and Semantic Similarity (2024.acl-srw)

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Challenge: Existing studies have shown that homophones with different semantic/syntactic contexts are easier for children to memorize.
Approach: They propose a method for empirically evaluating the relationship between phonological and semantic similarity of linguistic units using embedding spaces.
Outcome: The proposed method shows that Chinese character homophones have a positive semantic relationship at varying levels of sound-sharing.
Augmented Prompt Selection for Evaluation of Spontaneous Speech Synthesis (2020.lrec-1)

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Challenge: Spontaneous speech is unscripted and created on the fly by the speaker, whereas read speech is pre-planned.
Approach: They propose a tool that allows developers to select a varied, representative set of utterances from a spoken genre to be used for evaluation of TTS for a given domain.
Outcome: The proposed tool can be used to evaluate TTS for a given domain using visualisation and tree-based algorithm.

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