Lahjoita puhetta -- a large-scale corpus of spoken Finnish with some benchmarks
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Abstract (arXiv)
The Donate Speech campaign has so far succeeded in gathering approximately 3600 hours of ordinary, colloquial Finnish speech into the Lahjoita puhetta (Donate Speech) corpus. The corpus includes over twenty thousand speakers from all the regions of Finland and from all age brackets. The primary goals of the collection were to create a representative, large-scale resource to study spontaneous spoken Finnish and to accelerate the development of language technology and speech-based services. In this paper, we present the collection process and the collected corpus, and showcase its versatility through multiple use cases. The evaluated use cases include: automatic speech recognition of spontaneous speech, detection of age, gender, dialect and topic and metadata analysis. We provide benchmarks for the use cases, as well down loadable, trained baseline systems with open-source code for reproducibility. One further use case is to verify the metadata and transcripts given in this corpus itself, and to suggest artificial metadata and transcripts for the part of the corpus where it is missing.
Key facts. Cited by 6 papers in the map (data through 7 Oct 2026). Builds on 15 of its 41 references that are in the map. First posted on arXiv 24 Mar 2022.
Builds on
15 of 41 references.
References · 15
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Citing papers per year: 2022: 2; 2023: 1; 2024: 1; 2025: 1; 2026: 1.
6 papers.
- 2024Speech Analysis of Language Varieties in Italycited by 3
- 2022Comparison and Analysis of New Curriculum Criteria for End-to-End ASRcited by 2
- 2022Finnish Parliament ASR corpus - Analysis, benchmarks and statisticscited by 1
- 2025Investigating Affect Mining Techniques for Annotation Sample Selection in the Creation of Finnish Affective Speech Corpuscited by 1
- 2023Topic Identification For Spontaneous Speech: Enriching Audio Features With Embedded Linguistic Informationcited by 0
- 2026Looking for Affect in Spontaneous Finnish Speech through Linguistic Interpretabilitycited by 0
- 2026Looking for Affect in Spontaneous Finnish Speech through Linguistic Interpretability27 Jul 2026
- 2025Investigating Affect Mining Techniques for Annotation Sample Selection in the Creation of Finnish Affective Speech Corpus23 May 2025
- 2024Speech Analysis of Language Varieties in Italy22 Jun 2024
- 2023Topic Identification For Spontaneous Speech: Enriching Audio Features With Embedded Linguistic Information21 Jul 2023
- 2022Comparison and Analysis of New Curriculum Criteria for End-to-End ASR10 Aug 2022
- 2022Finnish Parliament ASR corpus - Analysis, benchmarks and statistics28 Mar 2022