Systems and methods described herein relate to adapting a language model for automatic speech recognition (ASR) for a new set of words. Instead of retraining the ASR models, language models and grammar models, the system only modifies one grammar model and ensures its compatibility with the existing models in the ASR system.

Speech processing techniques are disclosed that enable determining a text representation of named entities in captured audio data. Various implementations include determining the location of a carrier phrase in a word lattice representation of the captured audio data, where the carrier phrase provides an indication of a named entity. Additional or alternative implementations include matching a candidate named entity with the portion of the word lattice, and augmenting the word lattice with the matched candidate named entity.

Systems and methods for performing ASR in the presence of heterographs are provided. Verbal input is received from the user that includes a plurality of utterances. A first of the plurality of utterances is matched to a first word. It is determined that a second utterance in the plurality of utterances matches a plurality of words that is in a same heterograph set. It is identified which one of the plurality of words is associated with a context of the first word. A function is performed based on the first word and the identified one of the plurality of words.

Systems and methods for performing ASR in the presence of heterographs are provided. Verbal input is received from the user that includes a plurality of utterances. A first of the plurality of utterances is matched to a first word. It is determined that a second utterance in the plurality of utterances matches a plurality of words that is in a same heterograph set. It is identified which one of the plurality of words is associated with a context of the first word. A function is performed based on the first word and the identified one of the plurality of words.

A method for generating a suggested phrase having a similar meaning to a supplied phrase in an analytics system includes: receiving, on a computer system comprising a processor and memory storing instructions, the supplied phrase, the supplied phrase including one or more terms; identifying, on the computer system, a term of the phrase belonging to a semantic group; generating the suggested phrase using the supplied phrase and the semantic group; and returning the suggested phrase.

A system, article, and method of automatic speech recognition using parallel processing for weighted finite state transducer-based speech decoding.

A system, article, and method of automatic speech recognition using parallel processing for weighted finite state transducer-based speech decoding.

Speech processing techniques are disclosed that enable determining a text representation of named entities in captured audio data. Various implementations include determining the location of a carrier phrase in a word lattice representation of the captured audio data, where the carrier phrase provides an indication of a named entity. Additional or alternative implementations include matching a candidate named entity with the portion of the word lattice, and augmenting the word lattice with the matched candidate named entity.

Systems and techniques for generating natural language understanding (NLU) models are described. A developer of an NLU model may provide data representing runtime NLU functionality. For example, a developer may provide one or more sample natural language user inputs. The NLU model generation system may expand data, provided by the developer, to result in a more robust NLU model for use at runtime. For example, the NLU model generation system may expand sample natural language user inputs, may translate sample natural language user inputs into other languages, etc. The present disclosure also provides a mechanism for transitioning between using NLU models of a first NLU model generation system and NLU models of a second NLU model generation system.

Systems and techniques for generating natural language understanding (NLU) models are described. A developer of an NLU model may provide data representing runtime NLU functionality. For example, a developer may provide one or more sample natural language user inputs. The NLU model generation system may expand data, provided by the developer, to result in a more robust NLU model for use at runtime. For example, the NLU model generation system may expand sample natural language user inputs, may translate sample natural language user inputs into other languages, etc. The present disclosure also provides a mechanism for transitioning between using NLU models of a first NLU model generation system and NLU models of a second NLU model generation system.