Abstract: System and method for generating disambiguated terms in automatically generated transcripts and employing the system are disclosed. Exemplary implementations may: obtain a set of transcripts representing various speech from users; obtain indications of correlated correct and incorrect transcripts of spoken terms; use a vector generation model to generate vectors for individual instances of the correctly transcribed terms and individual instances the incorrectly transcribed terms based on text and contexts of the individual transcribed terms; and train the vector generation model to reduce spatial separation of the vectors generated for the spoken terms in the correlated correct transcripts and the incorrect transcripts.

Abstract: Systems and methods to group terms based on context to facilitate determining intent of a command are disclosed. Exemplary implementations to train a model: obtain a set of writings within a particular knowledge domain; obtain a vector generation model that generates vectors for individual instances of the terms in the set of writings; generate a first set of vectors that represent the instances of a first term and other vectors that represent instances of the other terms of the set of writings; train the vector generation model to group the vectors of a similar context in a space of a vector space; obtain a transcript include a new term generated from user audio dictation; generate a new vector that represent the instance of the new term; obtain the space; compare the new vector with the space; utilize the new term as the first term.

Abstract: System and method for generating disambiguated terms in automatically generated transcriptions including instructions within a knowledge domain and employing the system are disclosed.

Abstract: System and method for generating disambiguated terms in automatically generated transcriptions including instructions within a knowledge domain and employing the system are disclosed.

Abstract: Systems and methods to group terms based on context to facilitate determining intent of a command are disclosed. Exemplary implementations to train a model: obtain a set of writings within a particular knowledge domain; obtain a vector generation model that generates vectors for individual instances of the terms in the set of writings; generate a first set of vectors that represent the instances of a first term and other vectors that represent instances of the other terms of the set of writings; train the vector generation model to group the vectors of a similar context in a space of a vector space; obtain a transcript include a new term generated from user audio dictation; generate a new vector that represent the instance of the new term; obtain the space; compare the new vector with the space; utilize the new term as the first term.

Abstract: Systems and methods to group terms based on context to facilitate determining intent of a command are disclosed. Exemplary implementations to train a model: obtain a set of writings within a particular knowledge domain; obtain a vector generation model that generates vectors for individual instances of the terms in the set of writings; generate a first set of vectors that represent the instances of a first term and other vectors that represent instances of the other terms of the set of writings; train the vector generation model to group the vectors of a similar context in a space of a vector space; obtain a transcript include a new term generated from user audio dictation; generate a new vector that represent the instance of the new term; obtain the space; compare the new vector with the space; utilize the new term as the first term.

Abstract: System and method for generating disambiguated terms in automatically generated transcriptions including instructions within a knowledge domain and employing the system are disclosed.

Abstract: System and method for generating disambiguated terms in automatically generated transcriptions including instructions within a knowledge domain and employing the system are disclosed.