journal-digital 2025.6.4

Transcriptions from the Swedish newsreel archive Journal Digital

Journal Digital Corpus

The Journal Digital Corpus is a curated, timestamped transcription corpus derived from Swedish historical newsreels. It combines speech-to-text transcriptions and intertitle OCR to enable scalable and searchable analysis of early-to-mid 20th-century audiovisual media.

The SF Veckorevy newsreels—-screened weekly across Sweden for over five decades—-form one of the most extensive audiovisual records of 20th-century Swedish life. Yet their research potential has remained largely untapped due to barriers to access and analysis. The Journal Digital Corpus offers the first comprehensive transcription of both speech and intertitles from this material.

This corpus is the result of two purpose-built libraries:

• SweScribe – an ASR pipeline developed for transcription of speech in historical Swedish newsreels.
• stum – an OCR tool for detecting and transcribing intertitles in silent film footage.

The corpus consists of 2,229,854 words transcribed from 204 hours of speech across 2,553 videos and 302,342 words from 49,119 intertitles from 4,333 videos.

The primary files used for this project are publicly available on Filmarkivet.se, a web resource containing curated parts of Swedish film archives.

Installation

Git clone repository, cd in to the directory and run: python -m pip install -e .

python -m pip install journal_digital

2025-06-04

Created with SweScribe==v0.1.0 and stum==v.0.2.0 on 2025-06-04 without manual editing.

Files

• /name_year.tsv: Pairings of filename and publication year, based on metadata from The Swedish Media Database (SMDB).

/corpus
├── /intertitle
│   ├── /collection_1
│   ├── /collection_2
│   └── /collection_3
│       ├── /1920
│       │   ├── video_1.srt
│       │   ├── video_2.srt
│       │   └── video_3.srt
│       ├── /1921
│       │   ├── video_1.srt
│       │   ├── video_2.srt
│       │   └── video_3.srt
│       └── /1922
│           ├── video_1.srt
│           ├── video_2.srt
│           └── video_3.srt
├── /speech
│   ├── /collection_1
│   ├── /collection_2
│   └── /collection_3
│       ├── /1920
│       │   ├── video_1.srt
│       │   ├── video_2.srt
│       │   └── video_3.srt
│       ├── /1921
│       │   ├── video_1.srt
│       │   ├── video_2.srt
│       │   └── video_3.srt
│       └── /1922
│           ├── video_1.srt
│           ├── video_2.srt
│           └── video_3.srt

Development Setup

python -m pip install '.[dev]' pre-commit install

Add your path to videos got JOURNAL_DIGITALROOT in .env.

Research Context and Licensing

Modern Times 1936

The Journal Digital Corpus was developed for the Modern Times 1936 research project at Lund University, Sweden. The project investigates what software "sees," "hears," and "perceives" when pattern recognition technologies such as 'AI' are applied to media historical sources. The project is funded by Riksbankens Jubileumsfond.

License

The Journal Digital Corpus is licensed under the CC-BY-NC 4.0 International license.

References

@article{bain2022whisperx,
  title={WhisperX: Time-Accurate Speech Transcription of Long-Form Audio},
  author={Bain, Max and Huh, Jaesung and Han, Tengda and Zisserman, Andrew},
  journal={INTERSPEECH 2023},
  year={2023}
}

@inproceedings{malmsten2022hearing,
  title={Hearing voices at the national library : a speech corpus and acoustic model for the Swedish language},
  author={Malmsten, Martin and Haffenden, Chris and B{\"o}rjeson, Love},
  booktitle={Proceeding of Fonetik 2022 : Speech, Music and Hearing Quarterly Progress and Status Report, TMH-QPSR},
  volume={3},
  year={2022}
}

@inproceedings{zhou2017east,
  title={East: an efficient and accurate scene text detector},
  author={Zhou, Xinyu and Yao, Cong and Wen, He and Wang, Yuzhi and Zhou, Shuchang and He, Weiran and Liang, Jiajun},
  booktitle={Proceedings of the IEEE conference on Computer Vision and Pattern Recognition},
  pages={5551--5560},
  year={2017}
}