Build custom speech recognition models from large-scale datasets.
Capture large-scale datasets to model user accents.
Build new text-to-speech engines and utterance types.
Build large voice and text datasets for use to model emotions.
Collect voice data as part of an existing IRB protocol to classify various diseases.
Reduce time to collect labeled voice data from years to minutes.
Create better experiences for individuals who contribute voice data.
Build machine learning models and publish in peer-reviewed journals.
Easily extract raw audio responses for modeling.
Have participants label their own voice responses.
Reduce the time to model voice data from months to days.
Better experiences for contributors and data scientists.