WellSaid Labs & Oxford Languages
Giving content creators more control over their voiceover preferences
To embed a respelling feature within its text-to-speech product (an industry first), WellSaid Labs’ deep learning model required a trusted resource for phonetic pronunciation.
Its respelling mechanism had to be powered by accurate, up-to-date pronunciation datasets that would give users more control over phonetic preferences, including consonant and vowel sounds, and syllabic delivery. Likewise, it was important for the datasets to be updated regularly to include new words as they are added to the English language.
For the software to reflect the diversity of its customer base, WellSaid Labs wanted to expand its respelling feature into the various accents and dialects offered on its platform. However, finding high-quality data that catered to the level of variations that the AI model required proved challenging.
"Working with the Oxford Languages team has been a huge asset for us. We didn’t just want a data export; we wanted a relationship - and that’s exactly what we have. Their dataset pronunciations are succinct, straight to the point, and have the right balance of contextual, historical, and alternative metadata for each entry."
— Rhyan Johnson, Machine Learning Product Manager, WellSaid Labs