mlsanityData to 14 Oct 2026

ProsoBeast Prosody Annotation Tool

arXiv 2104.02397 ↗First posted 6 Apr 2021eess.AS cs.LGcited by 0

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Abstract (arXiv)

The labelling of speech corpora is a laborious and time-consuming process. The ProsoBeast Annotation Tool seeks to ease and accelerate this process by providing an interactive 2D representation of the prosodic landscape of the data, in which contours are distributed based on their similarity. This interactive map allows the user to inspect and label the utterances. The tool integrates several state-of-the-art methods for dimensionality reduction and feature embedding, including variational autoencoders. The user can use these to find a good representation for their data. In addition, as most of these methods are stochastic, each can be used to generate an unlimited number of different prosodic maps. The web app then allows the user to seamlessly switch between these alternative representations in the annotation process. Experiments with a sample prosodically rich dataset have shown that the tool manages to find good representations of varied data and is helpful both for annotation and label correction. The tool is released as free software for use by the community.

Key facts. No citing papers in the map yet (data through 14 Oct 2026). Builds on 5 of its 25 references that are in the map. First posted on arXiv 6 Apr 2021.

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5 of 25 references.

References · 5

  1. 2014Adam: A Method for Stochastic Optimizationcited by 37,240
  2. 2013Auto-Encoding Variational Bayescited by 4,053
  3. 2014Variational Recurrent Auto-Encoderscited by 53
  4. 2014An Autoencoder Approach to Learning Bilingual Word Representationscited by 7
  5. 2018A Variational Prosody Model for Mapping the Context-Sensitive Variation of Functional Prosodic Prototypescited by 1

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