Common Voice dataset vs. Collate
A side-by-side comparison based on G2 review data.
| Metric | Common Voice dataset | Collate |
|---|---|---|
| Overall rating | 4.5 | 4.6 |
| Review count | 11 | 10 |
| Ease of use | 8.4 | 9.4 |
| Ease of setup | 8.6 | 9.2 |
| Quality of support | 8.3 | 10.0 |
| Meets requirements | 8.3 | 9.3 |
| NPS | 63.636364 | 80 |
| Small Business | 63.6% | 10.0% |
| Mid-Market | 27.3% | 50.0% |
| Enterprise | 9.1% | 40.0% |
| Total page views | 16 | 57 |
| Total LLM citations | 11 | 28 |
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.
Collate
Collate is the AI-for-Data platform and the company behind OpenMetadata, the open context layer for AI. It gives data teams and AI agents the context, business meaning, and organizational memory needed to understand and use enterprise data consistently. Collate automates the recurring work required to keep data documented, tested, and governed, while grounding AI in the context needed to produce more accurate answers with fewer tokens. More than 4,000 organizations worldwide, including OpenAI, Yelp, Experian, and Airbus, run their production data and AI workloads on Collate and OpenMetadata.