Abstract: Systems for facilitating acquisition of a language by a user receive initial user input representing a phrase in a first language. The phrase is translated to a second language then parsed to generate constituent data indicative of one or more groups of related words within the phrase. The constituents may constitute comprehensible linguistic inputs for communication to a user when the initial phrase is not a comprehensible input. Output data is generated to output the constituents to the user. Based on the relationships between the words, the characteristics of the second language, or user data indicative of the user's previous comprehension of constituents, the amplitude, frequency, output rate, or other audible characteristic of output may be modified to emphasize or deemphasize portions of the constituents.

Abstract: There is provided a system including a microphone configured to receive an input speech, an analog to digital (A/D) converter configured to convert the input speech to a digital form and generate a digitized speech including a plurality of segments having acoustic features, a memory storing an executable code, and a processor executing the executable code to extract a plurality of acoustic feature vectors from a first segment of the digitized speech, determine, based on the plurality of acoustic feature vectors, a plurality of probability distribution vectors corresponding to the probabilities that the first segment includes each of a first keyword, a second keyword, both the first keyword and the second keyword, a background, and a social speech, and assign a first classification label to the first segment based on an analysis of the plurality of probability distribution vectors of one or more segments preceding the first segment and the probability distribution vectors of the first segment.

Abstract: There is provided a system including a microphone configured to receive an input speech, an analog to digital (A/D) converter configured to convert the input speech to a digital form and generate a digitized speech including a plurality of segments having acoustic features, a memory storing an executable code, and a processor executing the executable code to extract a plurality of acoustic feature vectors from a first segment of the digitized speech, determine, based on the plurality of acoustic feature vectors, a plurality of probability distribution vectors corresponding to the probabilities that the first segment includes each of a first keyword, a second keyword, both the first keyword and the second keyword, a background, and a social speech, and assign a first classification label to the first segment based on an analysis of the plurality of probability distribution vectors of one or more segments preceding the first segment and the probability distribution vectors of the first segment.