Bengali Speech Validation Data from Common Voice

A validation subset of the Common Voice dataset containing preprocessed audio recordings and transcripts in the Bengali language. The dataset was created by contributor Lancelot53 and last updated on the Hugging Face platform in July 2022. It is part of the Common Voice project, a Mozilla initiative for open-source speech technology.

Use Cases

• Benchmark ASR model accuracy by evaluating word error rate on the validation `audio` clips and their corresponding `transcript` text.
• Fine-tune a speech-to-text model using the preprocessed `audio` features and aligned `sentence` labels.
• Analyze speaker demographics or recording conditions using metadata fields like `age`, `gender`, or `accent` if available in the tabular data.
• Perform data augmentation by synthesizing variations from the clean, validated `audio` samples to improve model robustness.

Strengths

• Dataset is preprocessed, indicating cleaned and formatted audio-text pairs ready for model input.
• Sourced from the Common Voice project, which uses a public contribution framework for data collection.
• Specifically curated for the Bengali language, supporting an under-resourced language in speech technology.

Limitations

• Exact size (row count) and detailed column schema are unknown, limiting reproducibility assessment.
• Potential class imbalance in speaker demographics or accent coverage common in crowd-sourced collections.
• Data is from 2022 or earlier, which may not reflect latest speech patterns or vocabulary.

Provenance

Source

Mozilla Common Voice project.

Collection Method

Crowd-sourced audio recordings and transcriptions via an open online platform.

Freshness

Last updated in July 2022; static validation snapshot.

Geography

Contributions from Bengali speakers, likely with a focus on Bangladesh and India.