Peoples Speech ASR Clean: Filtered Audio Samples for Speech Recognition

OpenSpeechHub provides a filtered dataset for automatic speech recognition. The dataset has been processed to remove samples with fewer than three words, repetitive tokens, or chat token leaks. It was last updated on March 31, 2026.

Use Cases

• Training speech-to-text models based on filtered audio samples.
• Benchmarking ASR model performance on a dataset with removed short utterances.
• Fine-tuning language models for speech tasks using data cleaned of repetitive tokens.

Strengths

• Data has been filtered to remove samples with fewer than three words.
• Repetitive tokens and chat token leaks have been removed from the samples.

Limitations

• Description metadata is limited; actual data quality requires manual inspection after download.
• Column-level documentation is absent; field semantics must be inferred after download.
• Row count is unknown, which may limit suitability assessment.

Provenance

Source

OpenSpeechHub

Collection Method

Filtered from a larger ASR dataset; specific source and collection method are unknown.

Freshness

Last updated 2026-03-31 17:33:23; freshness should be verified.