Product improvements

Today we've released a major improvement to our ITN (Inverse Text Normalization) model. This results in better formatting for entities within the transcription, such as phone numbers, money amounts, and dates.

For example:

Money:

• Spoken: "Hey, do you have five dollars?"
• Model output with ITN: "Hey, do you have $5?"

Years:

• Spoken: "Yes, I believe it was back in two thousand eight"
• Model output with ITN: "Yes, I believe it was back in 2008."

Today we've released an updated Automatic Punctuation and Casing Restoration model (Punctuation v2.5)! This update results in improved capitalization of proper nouns in transcripts, reduces over-capitalization issues where some words like were being incorrectly capitalized, and improves some edge cases around words with commas around them. For example:

• "....in the Us" now becomes "....in the US."
• "whatsapp," now becomes "WhatsApp,"

Today we've released an updated Automatic Punctuation and Casing Restoration model (Punctuation v2.5)! This update results in improved capitalization of proper nouns in transcripts, reduces over-capitalization issues where some words like were being incorrectly capitalized, and improves some edge cases around words with commas around them. For example:

• "....in the Us" now becomes "....in the US."
• "whatsapp," now becomes "WhatsApp,"

We have released an updated Content Safety Model - v7! Performance for 10 out of all 19 Content Safety labels has been improved, with the biggest improvements being for the Profanity and Natural Disasters labels.

We have released an updated Content Safety Model - v7! Performance for 10 out of all 19 Content Safety labels has been improved, with the biggest improvements being for the Profanity and Natural Disasters labels.