Samsung Electronics Co., Ltd.

Melvin Lobo

Anil Sunder Yadav

Chutian Wang

Suhel Jaber

Allan Jay Schwade

Sukrat Gupta

An electronic device includes an audio sensor, a memory, and at least one processor coupled to the audio sensor and the memory. The at least one processor is configured to receive, via the audio sensor an audio input. The at least one processor is further configured to perform, using an automatic speech recognition (ASR) model and an entity prediction model, out-of-vocabulary prediction of an entity. The at least one processor is further configured to receive an ASR hypothesis including the predicted entity. The at least one processor is further configured to output text including the predicted entity.

System and method for out-of-vocabulary phrase support in automatic speech recognition

A system and method for creating organized intent clusters or scenes using machine learning algorithms is provided. A method of creating organized intent clusters or scenes comprises extracting intent features related to the plurality of request inputs. The method also includes creating a plurality of groups comprising the extracted intent features. The method includes identifying a cluster based on co-occurring extracted intent features, the co-occurring extracted intent features belonging to a plurality of domains. The method further includes generating a proto-scene based in part by ranking the extracted intent features within the cluster.

System and method for a scene builder

A system and method for dynamic cluster personalization is provided. A method of dynamic cluster personalization comprises acquiring information from a user, creating a usage log based on the acquired user information including language information and generating user features based on the usage log. The method further comprises determining a clustering feature from the user features, creating a user cluster based on the clustering feature, determining a personalization feature within the user cluster from the user features, generating a personalization for the user cluster based on the personalization feature and applying the personalization to the users in the user cluster.

System and method for dynamic cluster personalization

A method includes extracting a keyword and a slot from a natural language input, where the slot includes information. The method includes determining whether the keyword corresponds to one of a plurality of formation groups. In response to determining that the keyword corresponds to a specific formation group, the method includes updating metadata of the specific formation group with the information of the slot. In response to determining that the keyword does not correspond to any of the formation groups, the method includes determining whether the keyword corresponds to one of a plurality of clusters. In response to determining that the keyword corresponds to a specific cluster, the method includes updating the specific cluster with the information of the slot. In response to determining that the keyword does not correspond to any of the clusters, the method includes creating an additional formation group that includes the keyword and the slot.

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Fremont, CA, United States of America

Melvin Lobo