Non-Verbal Vocalisations and their Challenges: Emotion, Privacy, Sparseness, and Real Life
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Abstract (arXiv)
Non-Verbal Vocalisations (NVVs) are short `non-word' utterances without proper linguistic (semantic) meaning but conveying connotations -- be this emotions/affects or other paralinguistic information. We start this contribution with a historic sketch: how they were addressed in psychology and linguistics in the last two centuries, how they were neglected later on, and how they came to the fore with the advent of emotion research. We then give an overview of types of NVVs (formal aspects) and functions of NVVs, exemplified with the typical NVV textitah. Interesting as they are, NVVs come, however, with a bunch of challenges that should be accounted for: Privacy and general ethical considerations prevent them of being recorded in real-life (private) scenarios to a sufficient extent. Isolated, prompted (acted) exemplars do not necessarily model NVVs in context; yet, this is the preferred strategy so far when modelling NVVs, especially in AI. To overcome these problems, we argue in favour of corpus-based approaches. This guarantees a more realistic modelling; however, we are still faced with privacy and sparse data problems.
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References · 10
- 2022Robust Speech Recognition via Large-Scale Weak Supervisioncited by 4,057
- 2020wav2vec 2.0: A Framework for Self-Supervised Learning of Speech Representationscited by 3,905
- 2021HuBERT: Self-Supervised Speech Representation Learning by Masked Prediction of Hidden Unitscited by 2,342
- 2021WavLM: Large-Scale Self-Supervised Pre-Training for Full Stack Speech Processingcited by 1,657
- 2023Self-Consuming Generative Models Go MADcited by 250
- 2022Audio-based AI classifiers show no evidence of improved COVID-19 screening over simple symptoms checkerscited by 12
- 2024ExHuBERT: Enhancing HuBERT Through Block Extension and Fine-Tuning on 37 Emotion Datasetscited by 11
- 2025voc2vec: A Foundation Model for Non-Verbal Vocalizationcited by 5
- 2019On Laughter and Speech-Laugh, Based on Observations of Child-Robot Interactioncited by 1
- 2023EmoGator: A New Open Source Vocal Burst Dataset with Baseline Machine Learning Classification Methodologiescited by 1
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