mlsanityData to 7 Oct 2026

Lahjoita puhetta -- a large-scale corpus of spoken Finnish with some benchmarks

arXiv 2203.12906 ↗First posted 24 Mar 2022cs.CL eess.AScited by 6

Not on the map. Why?

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

  1. 2014Adam: A Method for Stochastic Optimizationcited by 36,960
  2. 2020wav2vec 2.0: A Framework for Self-Supervised Learning of Speech Representationscited by 3,853
  3. 2013Speech Recognition with Deep Recurrent Neural Networkscited by 666
  4. 2015Listen, Attend and Spellcited by 542
  5. 2021VoxPopuli: A Large-Scale Multilingual Speech Corpus for Representation Learning, Semi-Supervised Learning and Interpretationcited by 455
  6. 2021SpeechBrain: A General-Purpose Speech Toolkitcited by 404
  7. 2016Joint CTC-Attention based End-to-End Speech Recognition using Multi-task Learningcited by 254
  8. 2018Reducing Gender Bias in Abusive Language Detectioncited by 152
  9. 2015End-to-End Attention-based Large Vocabulary Speech Recognitioncited by 148
  10. 2019Multilingual is not enough: BERT for Finnishcited by 118
  11. 2019Recognizing long-form speech using streaming end-to-end modelscited by 77
  12. 2019A comparison of end-to-end models for long-form speech recognitioncited by 42
3 more
  1. 2021Finnish Dialect Identification: The Effect of Audio and Textcited by 8
  2. 2017Automatic Speech Recognition with Very Large Conversational Finnish and Estonian Vocabulariescited by 5
  3. 2020Attentional Speech Recognition Models Misbehave on Out-of-domain Utterancescited by 3

Built on by

Cited by year (2026 to 7 Oct)

Citing papers per year: 2022: 2; 2023: 1; 2024: 1; 2025: 1; 2026: 1.

6 papers.