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metadata
task_categories:
  - automatic-speech-recognition
language:
  - kg
  - ln
  - sw
pretty_name: c
size_categories:
  - 1K<n<10K

Speech Recognition Datasets for Congolese Languages

Dataset Details

Dataset Description

This dataset contains two new benchmark corpora designed for low-resource languages spoken in the Democratic Republic of the Congo: The Lingala Read Speech Corpus LRSC, with 4.3 hours of labelled audio, and the Congolese Speech Radio Corpus CSRC, which offers 741 hours of unlabeled audio spanning four significant low-resource languages of the region (Lingala, Tshiluba, Kikongo and Congolese Swahili). Collecting speech and audio for this dataset involved two sets of processes: (1) for LRSC, 32 Congolese adult participants were instructed to sit in a relaxed manner within centimetres of an audio recording device or smartphone and read from the text utterances; (2) for CSRC, recording from the archives of a broadcast station were pre-processed and curated. Congolese languages tend to fall into the “low-resource” category, which, in contrast to “high-resource” languages, has fewer datasets accessible, limiting the development of Conversational Artificial Intelligence. This results in creating the speech recognition datasets for low-resource Congolese languages. The proposed dataset contains two sections. The first section involves training a supervised speech recognition module, while the second involves pre-training a self-supervised model. Both sections feature a wide variety of speech and audio taken in various environments, with the first section featuring a speech having its corresponding transcription and the second featuring a collection of pre-processed raw audio data.

  • Curated by: [More Information Needed]
  • Funded by [optional]: [More Information Needed]
  • Shared by: Ussen Kimanuka, Ciira wa Maina ,Osman Büyük
  • Language(s) (NLP): Kikongo, Lingala, Swahili
  • License: [More Information Needed]

Dataset Sources [optional]

  • Repository:
  • Paper [optional]: [More Information Needed]
  • Demo [optional]: [More Information Needed]