Abstract: Examples described herein involve detecting known environmental conditions of using a neural network. An example implementation involves a playback device receiving data indicating a response of a listening environment to audio output of one or more playback devices as captured by a microphone and determining an input vector for a neural network. The playback device provides the determined input vector to the neural network, which includes an output layer comprising neurons that correspond to respective environmental conditions. The playback device detects that the input vector caused one or more neurons of the neural network to fire such that the neural network indicates that one or more particular environmental conditions are present in the listening environment. The playback device adjusts audio output of the one or more playback devices to at least partially offset the one or more particular environmental conditions.

Abstract: Data analysis, filter, and presentation techniques are described for an example call management system. An example method for a data management system includes receiving, from a user device, an account identifier of a first person, receiving, from the user device, a first message related to a topic of conversation to be discussed during a telephone call with the first person, determining, based on the account identifier and within a pre-determined time period, a presence of a set of data that describes conversation(s) from prior telephone call(s)/chat(s) with the first person, and sending, to a computer, at least some data from the set of data and a second message that indicates that the telephone call is mapped to a second person, where the computer is configured to display on a screen the second message and a presentation option that presents the at least some data via the computer.

Abstract: In an information processing system, a storage unit stores data related to a voice of a user for each item of user identification information that identifies the user during transmission or reception of a call. An acquisition unit acquires the user identification information on a calling side and data related to the voice of the user on the calling side after a call is started. A determination unit determines whether the data related to the voice of the user on the calling side and the data related to the voice stored by the storage unit in the user identification information acquired by the acquisition unit are based on the voice of the same person during the call.

Abstract: The invention provides a method, system, and a software program product for assisting a user and/or managing tasks of the user, by a mobile secretary cloud application configured to operate in a mobile client device and cloud server network. The mobile secretary cloud application reads data from another software application and operates at least one of another application and a third application based on the read data. Further, Artificial intelligence is utilized by the mobile secretary cloud application for operating another application and the third application.

Abstract: Systems and methods are disclosed for online data-linked telecommunications decisioning and distribution. One method includes receiving call data relating to a telephone call from a telephone device of a user to an interactive voice response (“IVR”) system; accessing a database storing correlated call data and user data; retrieving correlated call data and user data based on the telephone number of the call data; determining a confidence score defining a confidence that the received call data relates to the retrieved correlated call data and user data; correlating the received call data with retrieved call data and user data when the confidence score is greater than a threshold value; determining an IVR response to present to the user via the IVR system; and transmitting the determined IVR response to the IVR system for presentation to the telephone device of the user.

Abstract: Telephone numbers that are associated with robocalls or scam calls can be automatically identified by a telephone network operator. The identified telephone numbers may be blocked from placing phone calls on the telephone network.

Abstract: A method for distributing audio signals among a plurality of communication devices includes, during an audio connection between a first user and a remote person, receiving a first outbound signal that encodes audio being transmitted to a remote communication device of the remote person from a first communication device corresponding to the first user. The method includes receiving a first inbound signal that encodes audio being transmitted to the first communication device from the remote communication device, receiving a set of outbound signals from at least one of the plurality of communication devices other than the first communication device, and generating a first combined signal by combining the set of outbound signals with the first inbound signal. The first combined signal excludes inbound signals transmitted to the plurality of communication devices other than the first communication device. The method includes transmitting the first combined signal to the first communication device.

Abstract: System and method for detecting and identifying noises in a sound signal occurring during a call on a mobile device and selectively filtering and suppressing the noises in the sound signal are provided. In the mobile device, a processor is configured to receive a sound signal, detect noises in the received sound signal, identify the noises in the received sound signal, display the identified noises in a user interface (UI), receive a selection of the displayed identified noises from the UI, and filter the received selection of the displayed identified noises from the received sound signal. The processor may use a machine learning module with a neural network to detect and identify the noises in the received sound signal.

Abstract: Systems and methods for generating labelled audio data and onboard validation of the labelled audio data utilizing an autonomous driving vehicle (ADV) while the ADV is operating within a driving environment are disclosed. The method includes recording a sound emitted by an object within the driving environment of the ADV, and converting the recorded sound into audio samples. The method further includes labelling the audio samples, and refining the labelled audio samples to produce refined labelled audio data. The refined labelled audio data is utilized to subsequently train a machine learning algorithm to recognize a sound source during autonomous driving of the ADV. The method further includes generating a performance profile of the refined labelled audio data based at least on the audio samples, a position of the object, and a relative direction of the object. The position of the object and the relative direction of the object are determined by a perception system of the ADV.

Abstract: Systems and methods are provided for coordinated video streaming and messaging using a wrist-wearable device and a head-worn wearable device. The method includes receiving an instruction to use a camera of a head-worn wearable device to capture video data. The method further includes, after receiving the instruction to use the camera of the head-worn wearable device to capture the video data, receiving, at a wrist-wearable device that is in communication with the head-worn wearable device, electronic messages from a viewer of the video stream and monitoring sensor data indicating one or both of a position of the head-worn wearable device and (ii) a position of the wrist-wearable device to determine when to display the electronic messages. The method also includes, in accordance with a determination that the sensor data indicates that a message-viewing precondition is present, displaying the electronic messages from the viewer of the video stream.

Abstract: A method of quick set up of PSTN modem connection is proposed.

Abstract: Methods for generating an object based audio program which is renderable in a personalizable manner, e.g., to provide an immersive, perception of audio content of the program. Other embodiments include steps of delivering (e.g., broadcasting), decoding, and/or rendering such a program. Rendering of audio objects indicated by the program may provide an immersive experience. The audio content of the program may be indicative of multiple object channels (e.g., object channels indicative of user-selectable and user-configurable objects, and typically also a default set of objects which will be rendered in the absence of a selection by a user) and a bed of speaker channels. Another aspect is an audio processing unit (e.g., encoder or decoder) configured to perform, or which includes a buffer memory which stores at least one frame (or other segment) of an object based audio program (or bitstream thereof) generated in accordance with, any embodiment of the method.

Abstract: The invention concerns a mobile terminal with at least two transducers (LSm, LSs1, LSS2) used simultaneously as loudspeakers for stereophonic effect. According to the invention, one of said transducers is a main transducer (LSm) with a main working frequency band (Bm) corresponding to at least the phone frequency band, while the other transducer is a secondary transducer (LSs1; LSs2) with a secondary working frequency band (Bs1; Bs2) band different from said main frequency band, the lowest frequencies of said secondary working frequency band (Bs1; Bs2) being greater than the lowest frequencies of said main working frequency band.

Abstract: A method for managing an incoming call in a communication terminal is described, the incoming call having an associated call identifier. The method can comprise checking the routing of an outgoing call to the call identifier associated with the incoming call, and classifying the incoming call on the basis of the result of the checking of the routing, the incoming call being classified as a malicious incoming call if the checking of the routing reveals that the outgoing call is not able to be routed. The method can be used, for example, to detect malicious calls or spam.

Abstract: A server can receive a plurality of records at a databases such that each record is associated with a phone call and includes at least one request generated based on a transcript of the phone call. The server can generate a training dataset based on the plurality of records. The server can further train a binary classification model using the training dataset. Next, the server can receive a live transcript of a phone call in progress. The server can generate at least one live request based on the live transcript using a natural language processing module of the server. The server can provide the at least one live request to the binary classification model as input to generate a prediction. Lastly, the server can transmit the prediction to an entity receiving the phone call in progress. The prediction can cause a transfer of the call to a chatbot.

Abstract: A system may provide for the generation of spatial audio for audiovisual conferences, video conferences, etc. (referred to herein simply as “conferences”). Spatial audio may include audio encoding and/or decoding techniques in which a sound source may be specified at a location, such as on a two-dimensional plane and/or within a three-dimensional field, and/or in which a direction or target for a given sound source may be specified. A conference participant's position within a conference user interface (“UI”) may be set as the source of sound associated with the conference participant, such that different conference participants may be associated with different sound source positions within the conference UI.

Abstract: Video-assisted presence detection is used to enhance a user experience in telephony communications. Image data, video data, or both, from a camera are used to determine whether a user is present at their device before a call is transferred to him or her. The video-assisted presence detection can be implemented based on a privacy setting. For example, one implementation allows a system to have partial access to the camera to perform a scan to detect that there is a human present without capturing facial information, and without identifying that person. Another implementation allows the system to have partial access to the camera to scan the a face of a user, but not have access to the video feed of the camera. Another implementation allows the system to have full access to the camera.

Abstract: In one embodiment, a device obtains audio data from one or more past conferences. A prediction model that predicts when participants of a conference will speak is generated based on the audio data from the one or more past conferences. The device uses the prediction model to predict a speech distribution for participants of a particular conference. Then, the device proactively optimizes audio parameters of the particular conference based on its predicted speech distribution.

Abstract: Presentation of a recommendation to a user for individual processing of audio tracks in a digital audio workstation. Training audio tracks are provided to a human sound mixer and responsive to the training audio tracks individually processed training audio tracks are received from the human sound mixer. The training audio tracks and the individually processed training audio tracks are input to a machine to train the machine. Audio processing operations are output from the trained machine and stored in a record of a database.

Abstract: Some disclosed teleconferencing methods may involve detecting a howl state during a teleconference. The teleconference may involve two or more teleconference client locations and a teleconference server. The teleconference server may be configured for providing full-duplex audio connectivity between the teleconference client locations. The howl state may be a state of acoustic feedback involving two or more teleconference devices in a teleconference client location. Detecting the howl state may involve an analysis of both spectral and temporal characteristics of teleconference audio data. Some disclosed teleconferencing methods may involve determining which client location is causing the howl state. Some such methods may involve mitigating the howl state and/or sending a howl state detection message.