Abstract: Implement one or both of processing of computer queries using machine learning models and/or generation of machine learning models in a computer system. A computer processor generates a plurality of stored machine learning models. A computer processor extracts a plurality of updated parameters sets from the plurality of stored machine learning models. A computer processor creates a new machine learning model based on the respective distribution of each parameter included in the plurality of updated parameters sets. A computer processor processes at least one new query using the new machine learning model.

Abstract: Techniques are described to determine whether an input utterance is unrelated to a set of skill bots associated with a master bot. In some embodiments, a system described herein includes a training system and a master bot. The training system trains a classifier of the master bot. The training includes accessing training utterances associated with the skill bots and generating training feature vectors from the training utterances. The training further includes generating multiple set representations of the training feature vectors, where each set representation corresponds to a subset of the training feature vectors, and configuring the classifier with the set representations. The master bot accesses an input utterance and generates an input feature vector. The master bot uses the classifier to compare the input feature vector to the multiple set representations so as to determine whether the input feature falls outside and, thus, cannot be handled by the skill bots.

Abstract: There is disclosed a method and system for processing a user spoken utterance, the method comprising: receiving, from a user, an indication of the user spoken utterance; generating, a text representation hypothesis based on the user spoken utterance; processing, using a first trained scenario model and a second trained scenario model, the text representation hypothesis to generate a first scenario hypothesis and a second scenario hypothesis, respectively; the first trained scenario model and the second trained scenario model having been trained using at least partially different corpus of texts; analyzing, using a Machine Learning Algorithm (MLA), the first scenario hypothesis and the second scenario hypothesis to determine a winning scenario having a higher confidence score; based on the winning scenario, determining by an associated one of the first trained scenario model and the second trained scenario model, an action to be executed by the electronic device; executing the action.

Abstract: Systems and method of diarization of audio files use an acoustic voiceprint model. A plurality of audio files are analyzed to arrive at an acoustic voiceprint model associated to an identified speaker. Metadata associate with an audio file is used to select an acoustic voiceprint model. The selected acoustic voiceprint model is applied in a diarization to identify audio data of the identified speaker.

Abstract: A method for speech recognition is implemented in the specific form of computer processes that function in a computer processor. That is, one or more computer processes: process a speech input to produce a sequence of representative speech vectors and perform multiple recognition passes to determine a recognition output corresponding to the speech input. At least one generic recognition pass is based on a generic speech recognition arrangement using generic modeling of a broad general class of input speech. And at least one adapted recognition pass is based on a speech adapted arrangement using pre-adapted modeling of a specific sub-class of the general class of input speech.

Abstract: Provided is a system of voice recognition that adapts and stores a voice of a speaker for each feature to each of a basic voice model and new independent multi models and provides stable real-time voice recognition through voice recognition using a multi adaptive model.

Abstract: A computer-implemented method, system and/or program product update voice prints over time. A receiving computer receives an initial voice print. A determining period of time is calculated for that initial voice print. This determining period of time is a length of time during which an expected degree of change in subsequent voice prints, in comparison to the initial voice print, is predicted to occur. A new voice print is received after the determining period of time has passed, and the new voice print is compared with the initial voice print. In response to a change to the new voice print falling within the expected degree of change in comparison to the initial voice print, a voice print store is updated with the new voice print.

Abstract: The present invention discloses a solution for conserving computing resources when implementing transformation based adaptation techniques. The disclosed solution limits the amount of speech data used by real-time adaptation algorithms to compute a transformation, which results in substantial computational savings. Appreciably, application of a transform is a relatively low memory and computationally cheap process compared to memory and resource requirements for computing the transform to be applied.

Abstract: Systems and methods for processing a user speech input to determine whether the user has correctly read a target sentence string are provided. One disclosed method may include receiving a sentence array including component words of the target sentence string and processing the sentence array to generate a symbolic representation of the target sentence string. The symbolic representation may include a subset of words selected from the component words of the target sentence string, having fewer words than the sentence array. The method may include processing user speech input to recognize in the user speech input each of the words in the subset of words in the symbolic representation of the target sentence string. The method may further include, upon recognizing the subset of words, making a determination that the user has correctly read the target sentence string.

Abstract: The present invention provides for speech processing apparatus arranged for the input or output of a speech data signal and including a function generating means arranged for producing a representation of a vocal-tract potential function representative of a speech source and as an example, a speaker identification process can comprise means to capture an incoming voice signal, for example from a microphone or telephone line; means to process the signal electronically to generate a time varying series of binary vocal-tract potentials and associated non-vowel binary parameters; means to refine the signal to revoke the speaker-independent speech components; and means to compare the residual signal with a database of such residual features of known individuals.