Systems and methods for searching communications may include receiving a selection from a user of at least one of an acoustic characteristic, a language characteristic, or a category, accessing a database comprising a plurality of communications, the plurality of communications labeled with acoustic characteristics, language characteristics, and categories, restricting the plurality of communications to a subset of the plurality of communications including the user's selection of the at least one acoustic characteristic, language characteristic, or category, generating at least one of a word cloud or a tree for presenting a plurality of topics identified in the subset of the plurality of communications, and receiving a selection of one of the plurality of topics, the receiving causing a display of a further subset of the subset of the plurality of communications, the further subset having the selected topic.

An electronic notebook system is described comprising a housing, a computing device, wireless interfaces, antennas, sensors, a touch display configured to receive input via a stylus and/or human digit input, the stylus comprising a pressure and/or an inclination sensor, a microphone, camera, the system configured to provide a user condition interface, receive a user selection of a first user condition, provide an interface configured to receive user details, receive audible user details via the microphone, convert the audible user details received via the microphone to text, perform natural language processing to identify text keywords utilizing sentence segmentation, part-of-speech tagging, paraphrase recognition, and/or co-reference resolution, identify a condition based at least in part on the identified one or more keywords, dynamically generate an alert based at least in part on the identified condition, wirelessly transmit the alert to one or more destinations via at least a first wireless interface and antenna.

An electronic notebook system is described comprising a housing, a computing device, wireless interfaces, antennas, sensors, a touch display configured to receive input via a stylus and/or human digit input, the stylus comprising a pressure and/or an inclination sensor, a microphone, camera, the system configured to provide a user condition interface, receive a user selection of a first user condition, provide an interface configured to receive user details, receive audible user details via the microphone, convert the audible user details received via the microphone to text, perform natural language processing to identify text keywords utilizing sentence segmentation, part-of-speech tagging, paraphrase recognition, and/or co-reference resolution, identify a condition based at least in part on the identified one or more keywords, dynamically generate an alert based at least in part on the identified condition, wirelessly transmit the alert to one or more destinations via at least a first wireless interface and antenna.

Innovations in phase quantization during speech encoding and phase reconstruction during speech decoding are described. For example, to encode a set of phase values, a speech encoder omits higher-frequency phase values and/or represents at least some of the phase values as a weighted sum of basis functions. Or, as another example, to decode a set of phase values, a speech decoder reconstructs at least some of the phase values using a weighted sum of basis functions and/or reconstructs lower-frequency phase values then uses at least some of the lower-frequency phase values to synthesize higher-frequency phase values. In many cases, the innovations improve the performance of a speech codec in low bitrate scenarios, even when encoded data is delivered over a network that suffers from insufficient bandwidth or transmission quality problems.

Innovations in phase quantization during speech encoding and phase reconstruction during speech decoding are described. For example, to encode a set of phase values, a speech encoder omits higher-frequency phase values and/or represents at least some of the phase values as a weighted sum of basis functions. Or, as another example, to decode a set of phase values, a speech decoder reconstructs at least some of the phase values using a weighted sum of basis functions and/or reconstructs lower-frequency phase values then uses at least some of the lower-frequency phase values to synthesize higher-frequency phase values. In many cases, the innovations improve the performance of a speech codec in low bitrate scenarios, even when encoded data is delivered over a network that suffers from insufficient bandwidth or transmission quality problems.

A method, computer system, and a computer program product for discussion relevance feedback associated with an electronic meeting is provided. The method may include determining a meeting topic associated with the electronic meeting and receiving audio data recording the vocal interactions of one or more meeting attendees. The method may further include generating a textual representation of the received audio data and then identifying a current discussion topic based on the generated textual representation. The method may further include determining a semantic distance between the identified current discussion topic and the determined meeting topic and generating discussion relevance feedback based on the determined semantic distance.

A method, computer system, and a computer program product for discussion relevance feedback associated with an electronic meeting is provided. The method may include determining a meeting topic associated with the electronic meeting and receiving audio data recording the vocal interactions of one or more meeting attendees. The method may further include generating a textual representation of the received audio data and then identifying a current discussion topic based on the generated textual representation. The method may further include determining a semantic distance between the identified current discussion topic and the determined meeting topic and generating discussion relevance feedback based on the determined semantic distance.

Embodiments herein generally relate to an electronic system, electronic device and/or a method of using the same to improve human activities in a business, a home or an educational environment. The electronic system, electronic device, and method allows for anonymous feedback from users to alert another user that the sound levels being maintained in a certain region are unacceptable. The method includes inputting one or more sound preferences into one or more electronic devices, receiving, at a first electronic device of the one or more electronic devices, local environment data, determining whether the local environmental data is associated with a first user, exchanging the local environment data with the one or more electronic devices, and generating an alert on the first electronic device. The method and electronic system allows users in the office environment to provide anonymous feedback to users that do not maintain an appropriate sound level.

Systems and methods are disclosed for customizing, distributing and processing audio signature data. Examples disclosed herein include waking a portable device from an inactive state in response to an activation signal. Disclosed examples also include generating a first signature based on audio from a microphone of the portable device during a period of time specified by the activation signal. Disclosed examples further include comparing the first signature with a second signature obtained from the activation signal to determine a match score, and communicating a match result based on the match score to a server via a network.

Systems and methods are disclosed for customizing, distributing and processing audio signature data. Examples disclosed herein include waking a portable device from an inactive state in response to an activation signal. Disclosed examples also include generating a first signature based on audio from a microphone of the portable device during a period of time specified by the activation signal. Disclosed examples further include comparing the first signature with a second signature obtained from the activation signal to determine a match score, and communicating a match result based on the match score to a server via a network.