Product improvements

We have just released a major real-time update!

Developers will now be able to use the word_boost parameter in requests to the real-time API, allowing you to introduce your own custom vocabulary to the model for that given session! This custom vocabulary will lead to improved accuracy for the provided words.

General Improvements

We will now be limiting one websocket connection per real-time session to ensure the integrity of a customer's transcription and prevent multiple users/clients from using the websocket same session.

Note: Developers can still have multiple real-time sessions open in parallel, up to the Concurrency Limit on the account. For example, if an account has a Concurrency Limit of 32, that account could have up to 32 concurrent real-time sessions open.

We have just released a major real-time update!

Developers will now be able to use the word_boost parameter in requests to the real-time API, allowing you to introduce your own custom vocabulary to the model for that given session! This custom vocabulary will lead to improved accuracy for the provided words.

General Improvements

We will now be limiting one websocket connection per real-time session to ensure the integrity of a customer's transcription and prevent multiple users/clients from using the websocket same session.

Note: Developers can still have multiple real-time sessions open in parallel, up to the Concurrency Limit on the account. For example, if an account has a Concurrency Limit of 32, that account could have up to 32 concurrent real-time sessions open.

Today we have released v2 of our Topic Detection Model. This new model will predict multiple topics for each paragraph of text, whereas v1 was limited to predicting a single. For example, given the text:

"Elon Musk just released a new Tesla that drives itself!"

v1:

• Automotive>AutoType>DriverlessCars: 1

v2:

• Automotive>AutoType>DriverlessCars: 1
• PopCulture : 0.84
• PopCulture>CelebrityStyle: 0.56

This improvement will result in the visual output looking significantly better, and containing more informative responses for developers!

Today we have released v2 of our Topic Detection Model. This new model will predict multiple topics for each paragraph of text, whereas v1 was limited to predicting a single. For example, given the text:

"Elon Musk just released a new Tesla that drives itself!"

v1:

• Automotive>AutoType>DriverlessCars: 1

v2:

• Automotive>AutoType>DriverlessCars: 1
• PopCulture : 0.84
• PopCulture>CelebrityStyle: 0.56

This improvement will result in the visual output looking significantly better, and containing more informative responses for developers!

In this minor improvement, we have increased the number of topics the model can return in the summary key of the JSON response from 10 to 20.