Systems and methods to facilitate intent determination of a command by grouping terms based on context

A system configured to utilize a term grouping model to determine intent of a command with a new spoken term, the system comprising:

• one or more processors configured by machine-readable instructions to:
• obtain a transcript automatically generated from audio dictation of a user, wherein the transcript resulted from automatic speech recognition, the transcript including instances of transcribed terms automatically derived from the audio dictation as textual representations of spoken terms in the audio dictation, the transcribed terms including an instance of a new transcribed term;
• facilitate communication with the term grouping model, the term grouping model configured to group terms based on a particular context;
• generate, via the term grouping model, a set of vectors that numerically represent text of the transcribed terms included in the transcript and contexts of the instances of the transcribed terms in the transcript, the set of vectors including a first vector that numerically represents text of the new transcribed term and context of the instance of the new transcribed term;
• obtain, from the term grouping model, a first space, wherein the first space is included in a vector space, wherein the first space represents text of transcribed terms that are in the contexts of the instances, the first space including the set of vectors except the first vector and including a second vector that represents text of an alternative term to the new transcribed term in the contexts of the instances of the transcribed terms included in the transcript;
• compare the set of the vectors to the first space to determine whether the first vector is related to the first space and whether the first vector correlates to one of the vectors in the first space, such that the first vector is determined to be related to the first space and a correlation between the first vector and the second vector is determined, wherein the correlation indicates equivalency;
• store the correlation between the first vector and the second vector;
• and
• utilize, based on the correlation, the text of the alternative term by replacing the instance of the new transcribed term with the text of the alterative term.

A method configured to group terms based on context, the method comprising:

• obtaining a set of writings within a particular knowledge domain, wherein individual ones of the writings within the set of writings include terms, wherein the terms include (i) transcribed terms that are textual representations of spoken terms in audio dictations, and/or (ii) published terms of literatures of the particular knowledge domain, wherein the audio dictations represent various speech from a user, and wherein the transcribed terms are automatically derived from automatic speech recognition of the audio dictations, wherein the terms are part of a lexicon of the particular knowledge domain, the terms including individual instances of a first term;
• obtaining a vector generation model that generates vectors for instances of individual ones of the terms that are included in the set of writings and that are part of the lexicon of the particular knowledge domain, the vectors numerically representing text of the individual terms and contexts of the instances of the individual terms;
• using the vector generation model to generate the vectors, wherein the terms include individual instances of other terms that are not the first term, such that:
• a first set of vectors are generated that represent the individual instances of the first term, wherein individual vectors in the first set numerically represent (i) the text of the first term, and (ii) individual contexts that the individual instances of the first term are used in, the first set of vectors including a first vector that numerically represents the text of the first term and a first context of a first instance that the first term is used in, wherein the instances of the first term include the first instance, and
• other vectors are generated that represent the individual instances of the other terms that are a part of the lexicon of the knowledge domain and included in the set of writings, such vectors numerically representing text of individual ones of the other terms and contexts that the individual instances of the individual other terms are used in, wherein the vectors include the first set and the other vectors;
• and
• training the vector generation model to group the vectors into spaces of a vector space based on similar contexts that the individual vectors were generated based on, such that the first vector and some of the other vectors are grouped into a first space of the vector space.

A method configured to utilize a term grouping model to determine intent of a command with a new spoken term, the method comprising:

• obtaining a transcript automatically generated from audio dictation of a user, wherein the transcript resulted from automatic speech recognition, the transcript including instances of transcribed terms automatically derived from the audio dictation as textual representations of spoken terms in the audio dictation, the transcribed terms including an instance of a new transcribed term;
• facilitating communication with the term grouping model, the term grouping model configured to group terms based on a particular context;
• generating, via the term grouping model, a set of vectors that numerically represent text of the transcribed terms included in the transcript and contexts of the instances of the transcribed terms in the transcript, the set of vectors including a first vector that numerically represents text of the new transcribed term and context of the instance of the new transcribed term;
• obtaining, from the term grouping model, a first space, wherein the first space is included in a vector space, wherein the first space represents text of transcribed terms that are in the contexts of the instances, the first space including the set of vectors except the first vector and including a second vector that represents text of an alternative term to the new transcribed term in the contexts of the instances of the transcribed terms included in the transcript;
• comparing the set of the vectors to the first space to determine whether the first vector is related to the first space and whether the first vector correlates to one of the vectors in the first space, such that the first vector is determined to be related to the first space and a correlation between the first vector and the second vector is determined, wherein the correlation indicates equivalency;
• storing the correlation between the first vector and the second vector;
• and
• utilizing, based on the correlation, the text of the alternative term by replacing the instance of the new transcribed term with the text of the alternative term.