Nord-Parl-TTS: Finnish and Swedish TTS Dataset from Parliament Speech

Text-to-speech (TTS) development is limited by scarcity of high-quality, publicly available speech data for most languages outside a few high-resource languages. We present Nord-Parl-TTS, an open TTS dataset for Finnish and Swedish based on speech found in the wild. Using recordings of Nordic parliamentary proceedings, we extract 900 hours of Finnish and 5090 hours of Swedish speech suitable for TTS training. The dataset is built using an adapted version of the Emilia data processing pipeline and includes unified evaluation sets to support model development and benchmarking. By offering open, large-scale data for Finnish and Swedish, Nord-Parl-TTS narrows the resource gap in TTS between high- and lower-resourced languages.

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Publication Details

Published
2026-04-21
DOI
https://doi.org/10.1109/icassp55912.2026.11465122
Primary Topic
Natural Language Processing Techniques
Type
article
Field-Weighted Citation Impact
0.00

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article

Nord-Parl-TTS: Finnish and Swedish TTS Dataset from Parliament Speech

Zirui Li, Mikko Kurimo, Jens Edlund, Nhan Phan et al.
Natural Language Processing Techniques
article

Nord-Parl-TTS: Finnish and Swedish TTS Dataset from Parliament Speech

Zirui Li, Mikko Kurimo, Jens Edlund, Nhan Phan, Lauri Juvela, Yan Gu
article en

Abstract

Text-to-speech (TTS) development is limited by scarcity of high-quality, publicly available speech data for most languages outside a few high-resource languages. We present Nord-Parl-TTS, an open TTS dataset for Finnish and Swedish based on speech found in the wild. Using recordings of Nordic parliamentary proceedings, we extract 900 hours of Finnish and 5090 hours of Swedish speech suitable for TTS training. The dataset is built using an adapted version of the Emilia data processing pipeline and includes unified evaluation sets to support model development and benchmarking. By offering open, large-scale data for Finnish and Swedish, Nord-Parl-TTS narrows the resource gap in TTS between high- and lower-resourced languages.

Chinese University of Hong Kong, Shenzhen (CN), KTH Royal Institute of Technology (SE), Aalto University (FI)
Ministry of Education
Openalex Percentile: Top 99%
Natural Language Processing Techniques
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