Abstract:
Extracting, from user activity data, quantitative attributes and qualitative attributes collected for users having user profiles. The quantitative attributes and the qualitative attributes are extracted during a specified time period determined before the user activity data is collected. Values for the quantitative attributes and the qualitative attributes are plotted, and subsets of the user profiles are clustered into separate group of users based on the plotted values. Delivering a product related content to the groups of users based on the clustering.
Abstract:
Devices, systems, methods, media, and programs for detecting an emotional state change in an audio signal are provided. A plurality of segments of the audio signal is received, with the plurality of segments being sequential. Each segment of the plurality of segments is analyzed, and, for each segment, an emotional state and a confidence score of the emotional state are determined. The emotional state and the confidence score of each segment are sequentially analyzed, and a current emotional state of the audio signal is tracked throughout each of the plurality of segments. For each segment, it is determined whether the current emotional state of the audio signal changes to another emotional state based on the emotional state and the confidence score of the segment.
Abstract:
Devices, systems, methods, media, and programs for detecting an emotional state change in an audio signal are provided. A plurality of segments of the audio signal is received, with the plurality of segments being sequential. Each segment of the plurality of segments is analyzed, and, for each segment, an emotional state and a confidence score of the emotional state are determined. The emotional state and the confidence score of each segment are sequentially analyzed, and a current emotional state of the audio signal is tracked throughout each of the plurality of segments. For each segment, it is determined whether the current emotional state of the audio signal changes to another emotional state based on the emotional state and the confidence score of the segment.
Abstract:
Disclosed herein are systems, methods, and non-transitory computer-readable storage media for approximating responses to a user speech query in voice-enabled search based on metadata that include demographic features of the speaker. A system practicing the method recognizes received speech from a speaker to generate recognized speech, identifies metadata about the speaker from the received speech, and feeds the recognized speech and the metadata to a question-answering engine. Identifying the metadata about the speaker is based on voice characteristics of the received speech. The demographic features can include age, gender, socio-economic group, nationality, and/or region. The metadata identified about the speaker from the received speech can be combined with or override self-reported speaker demographic information.
Abstract:
Systems, methods, and computer-readable storage devices for receiving an utterance from a user and analyzing the utterance to identify the demographics of the user. The system then analyzes the utterance to determine the prosody of the utterance, and retrieves from the Internet data associated with the determined demographics. Using the retrieved data, the system retrieves, also from the Internet, recorded speech matching the identified prosody. The recorded speech, which is based on the demographic data of the utterance and has a prosody matching the utterance, is then saved to a database for future use in generating speech specific to the user.
Abstract:
Systems, methods, and computer-readable storage devices for generating speech using a presentation style specific to a user, and in particular the user's social group. Systems configured according to this disclosure can then use the resulting, personalized, text and/or speech in a spoken dialogue or presentation system to communicate with the user. For example, a system practicing the disclosed method can receive speech from a user, identify the user, and respond to the received speech by applying a personalized natural language generation model. The personalized natural language generation model provides communications which can be specific to the identified user.
Abstract:
Systems, methods, and computer-readable storage devices for receiving an utterance from a user and analyzing the utterance to identify the demographics of the user. The system then analyzes the utterance to determine the prosody of the utterance, and retrieves from the Internet data associated with the determined demographics. Using the retrieved data, the system retrieves, also from the Internet, recorded speech matching the identified prosody. The recorded speech, which is based on the demographic data of the utterance and has a prosody matching the utterance, is then saved to a database for future use in generating speech specific to the user.
Abstract:
Systems, methods, and computer-readable storage devices for receiving an utterance from a user and analyzing the utterance to identify the demographics of the user. The system then analyzes the utterance to determine the prosody of the utterance, and retrieves from the Internet data associated with the determined demographics. Using the retrieved data, the system retrieves, also from the Internet, recorded speech matching the identified prosody. The recorded speech, which is based on the demographic data of the utterance and has a prosody matching the utterance, is then saved to a database for future use in generating speech specific to the user.
Abstract:
Systems, methods, and computer-readable storage devices for generating speech using a presentation style specific to a user, and in particular the user's social group. Systems configured according to this disclosure can then use the resulting, personalized, text and/or speech in a spoken dialogue or presentation system to communicate with the user. For example, a system practicing the disclosed method can receive speech from a user, identify the user, and respond to the received speech by applying a personalized natural language generation model. The personalized natural language generation model provides communications which can be specific to the identified user.