This model dramatically improves the Topic Detection feature's ability to accurately detect topics based on context.
For example, in the following text, the model was able to accurately predict "Rugby" without the mention of the sport directly, due to the mention of "Ed Robinson" (a Rugby coach).
PII Redaction has been improved to better identify (and redact) phone numbers even when they are not explicitly referred to as a phone number.
Released a fix for PII Redaction that corrects an issue where the model would sometimes detect phone numbers as credit card numbers or social security numbers.
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v3 Topic Detection Model, PII Redaction Bug Fixes
Released our v3 Topic Detection model.
This model dramatically improves the Topic Detection feature's ability to accurately detect topics based on context.
For example, in the following text, the model was able to accurately predict "Rugby" without the mention of the sport directly, due to the mention of "Ed Robinson" (a Rugby coach).
PII Redaction has been improved to better identify (and redact) phone numbers even when they are not explicitly referred to as a phone number.
Released a fix for PII Redaction that corrects an issue where the model would sometimes detect phone numbers as credit card numbers or social security numbers.
1
Severity Scores for Content Safety
The API now returns a severity score along with the confidence and label keys when using the Content Safety feature.
The severity score measures how intense a detected Content Safety label is on a scale of 0 to 1.
For example, a natural disaster that leads to mass casualties will have a score of 1.0, while a small storm that breaks a mailbox will only be 0.1.
Fixed an edge case where a small number of transcripts with Automatic Transcript Highlights turned on were not returning any results.
1
Severity Scores for Content Safety
The API now returns a severity score along with the confidence and label keys when using the Content Safety feature.
The severity score measures how intense a detected Content Safety label is on a scale of 0 to 1.
For example, a natural disaster that leads to mass casualties will have a score of 1.0, while a small storm that breaks a mailbox will only be 0.1.
Fixed an edge case where a small number of transcripts with Automatic Transcript Highlights turned on were not returning any results.
1
Real-time Transcription and Streaming Fixes
Fixed an edge case where higher sample rates would occasionally trigger a Client sent audio too fast error from the Real-Time Streaming WebSocket API.
Fixed an edge case where some streams from Real-Time Streaming WebSocket API were held open after a customer idled their session.
Fixed an edge case in the /v2/stream endpoint, where large periods of silence would occasionally cause automatic punctuation to fail.
Improved error handling when non-JSON input is sent to the /v2/transcript endpoint.
