Common Voice dataset vs. BigID
A side-by-side comparison based on G2 review data.
| Metric | Common Voice dataset | BigID |
|---|---|---|
| Overall rating | 4.5 | 4.3 |
| Review count | 11 | 16 |
| Ease of use | 8.4 | 8.1 |
| Ease of setup | 8.6 | 8.2 |
| Quality of support | 8.3 | 7.9 |
| Meets requirements | 8.3 | 8.3 |
| NPS | 63.636364 | 68.75 |
| Small Business | 63.6% | 43.8% |
| Mid-Market | 27.3% | 31.3% |
| Enterprise | 9.1% | 25.0% |
| Total page views | 16 | 807 |
| Total LLM citations | 11 | 20,153 |
Common Voice dataset
Each entry in the dataset consists of a unique MP3 and corresponding text file. Many of the 1,368 recorded hours in the dataset also include demographic metadata like age, sex, and accent that can help train the accuracy of speech recognition engines. The dataset currently consists of 1,087 validated hours in 18 languages, but we're always adding more voices and languages.
BigID
BigID’s data intelligence platform enables organizations to know their enterprise data and take action for privacy, protection, and perspective. Customers deploy BigID to proactively discover, manage, protect, and get more value from their regulated, sensitive, and personal data across their data landscape. By applying advanced machine learning and deep data insight, BigID transforms data discovery and data intelligence to address data privacy, data security, and data governance challenges across all types of data, at petabyte-scale, on-prem and in the cloud.
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