Naija-ASR-Corpus: Nigerian Pidgin Speech Recognition Dataset

Naija-ASR-Corpus v1.0 (NAC-v1.0) is a foundational speech dataset for Nigerian Pidgin (Naija, PCM). It was created by the NAC Team, who processed long-form recordings from the Universal Dependencies Naija Spoken Corpus into sentence-level audio-text pairs suitable for ASR training. The dataset was last updated on March 16, 2026.

Use Cases

• Train automatic speech recognition models based on the aligned audio-text pairs.
• Benchmark ASR model performance for Nigerian Pidgin based on the foundational corpus.
• Fine-tune multilingual speech models for the Nigerian Pidgin language.
• Conduct linguistic research on Nigerian Pidgin phonetics and syntax using the transcribed speech data.

Strengths

• Derived from the established Universal Dependencies Naija Spoken Corpus (UD_Naija-NSC).
• Processed into sentence-level clips with aligned transcriptions, making it suitable for ASR training.
• Explicitly designed as a foundational corpus for the Nigerian Pidgin language.

Limitations

• Column-level documentation is absent; field semantics must be inferred after download.
• Row count, file formats, and dataset size are unknown, which may limit suitability assessment.
• License information is unknown, which could restrict commercial or research use.

Provenance

Source

Universal Dependencies Naija Spoken Corpus (UD_Naija-NSC).

Collection Method

Original long-form recordings were segmented into sentence-level clips and transcribed/aligned by the NAC Team.

Time Range

null

Freshness

Last updated 2026-03-16 11:56:32; freshness should be verified.

Geography

Nigeria (inferred from focus on Nigerian Pidgin).