The IMS Toucan System for the Blizzard Challenge 2023
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Abstract (arXiv)
For our contribution to the Blizzard Challenge 2023, we improved on the system we submitted to the Blizzard Challenge 2021. Our approach entails a rule-based text-to-phoneme processing system that includes rule-based disambiguation of homographs in the French language. It then transforms the phonemes to spectrograms as intermediate representations using a fast and efficient non-autoregressive synthesis architecture based on Conformer and Glow. A GAN based neural vocoder that combines recent state-of-the-art approaches converts the spectrogram to the final wave. We carefully designed the data processing, training, and inference procedures for the challenge data. Our system identifier is G. Open source code and demo are available.
Key facts. Cited by 6 papers in the map (data through 7 Oct 2026). Builds on 27 of its 44 references that are in the map. First posted on arXiv 26 Oct 2023.
Builds on
27 of 44 references.
References · 27
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15 more
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Built on by
Citing papers per year: 2024: 4; 2025: 2.
6 papers.
- 2024Meta Learning Text-to-Speech Synthesis in over 7000 Languagescited by 9
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- 2024NTU-NPU System for Voice Privacy 2024 Challengecited by 6
- 2024Probing the Feasibility of Multilingual Speaker Anonymizationcited by 5
- 2025Investigating Stochastic Methods for Prosody Modeling in Speech Synthesiscited by 2
- 2025Perceptual implications of automatic anonymization in pathological speechcited by 0
- 2025Investigating Stochastic Methods for Prosody Modeling in Speech Synthesis30 Jun 2025
- 2025Perceptual implications of automatic anonymization in pathological speech1 May 2025
- 2024NTU-NPU System for Voice Privacy 2024 Challenge3 Oct 2024
- 2024Probing the Feasibility of Multilingual Speaker Anonymization3 Jul 2024
- 2024Controlling Emotion in Text-to-Speech with Natural Language Prompts10 Jun 2024
- 2024Meta Learning Text-to-Speech Synthesis in over 7000 Languages10 Jun 2024