mlsanityData to 13 Oct 2026

LuxEmo: Expressive Text-to-Speech Corpus for Luxembourgish

arXiv 2606.31947 ↗First posted 30 Jun 2026cs.CLcited by 0

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Abstract (arXiv)

State-of-the-art speech datasets predominantly focus on widely spoken languages, often overlooking low-resource languages such as Luxembourgish, which remain underrepresented in speech technology research. In this work, we introduce LuxEmo, a 21-hour conversational expressive speech corpus for Luxembourgish with 4 emotion categories. LuxEmo is derived from Radio T'el'evision Luxembourg (RTL) youth broadcasts, using automated detection followed by human validation. We propose a semi-automatic curation workflow combining voice activity detection, denoising, language identification, LuxASR-based segmentation, automatic emotion prediction, lexical cues, and targeted human review. Additionally, we benchmark five expressive TTS systems covering German-based cross-lingual transfer, multilingual Luxembourgish support, Luxembourgish adaptation, and non-parametric prosody transfer. Performance is evaluated using both objective metrics and human evaluation.

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References · 16

  1. 2022Robust Speech Recognition via Large-Scale Weak Supervisioncited by 4,004
  2. 2021SpeechBrain: A General-Purpose Speech Toolkitcited by 404
  3. 2023Scaling Speech Technology to 1,000+ Languagescited by 402
  4. 2020DNSMOS: A Non-Intrusive Perceptual Objective Speech Quality metric to evaluate Noise Suppressorscited by 239
  5. 2021NISQA: A Deep CNN-Self-Attention Model for Multidimensional Speech Quality Prediction with Crowdsourced Datasetscited by 191
  6. 2022HiFi++: a Unified Framework for Bandwidth Extension and Speech Enhancementcited by 49
  7. 2021DeepFilterNet: A Low Complexity Speech Enhancement Framework for Full-Band Audio based on Deep Filteringcited by 38
  8. 2021Deep Learning Based Assessment of Synthetic Speech Naturalnesscited by 35
  9. 2019End-to-end Text-to-speech for Low-resource Languages by Cross-Lingual Transfer Learningcited by 30
  10. 2020Low-resource expressive text-to-speech using data augmentationcited by 26
  11. 2025EmergentTTS-Eval: Evaluating TTS Models on Complex Prosodic, Expressiveness, and Linguistic Challenges Using Model-as-a-Judgecited by 24
  12. 2019Exploring Transfer Learning for Low Resource Emotional TTScited by 21
4 more
  1. 2018Effect of data reduction on sequence-to-sequence neural TTScited by 16
  2. 2020Controllable Neural Prosody Synthesiscited by 10
  3. 2023Letz Translate: Low-Resource Machine Translation for Luxembourgishcited by 5
  4. 2024Enhancing Emotional Text-to-Speech Controllability with Natural Language Guidance through Contrastive Learning and Diffusion Modelscited by 3

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