Less Is More: A Unified Architecture for Device-Directed Speech Detection with Multiple Invocation Types
Suppressing unintended invocation of the device because of the speech that sounds like wake-word, or accidental button presses, is critical for a good user experience, and is referred to as False-Trigger-Mitigation (FTM). In case of multiple invocation options, the traditional approach to FTM is to use invocation-specific models, or a single model for all invocations. Both approaches are sub-optimal: the memory cost for the former approach grows linearly with the number of invocation options, which is prohibitive for on-device deployment, and does not take advantage of shared training data;…
Today, we’re announcing inline payload support for Amazon SageMaker AI Async Inference. Customers can now send inference payloads directly in the request body of the InvokeEndpointAsync API, removing the need to upload input data to Amazon Simple Storage Service (Amazon S3) before each invocation. For payloads up to 128,000 bytes,…