A system and method may identify a fraud ring based on call or interaction data by analyzing by a computer processor interaction data including audio recordings to identify clusters of interactions which are suspected of involving fraud each cluster including the same speaker; analyzing by the computer processor the clusters, in combination with metadata associated with the interaction data, to identify fraud rings, each fraud ring describing a plurality of different speakers, each fraud ring defined by a set of speakers and a set of metadata corresponding to interactions including that speaker; and for each fraud ring, creating a relevance value defining the relative relevance of the fraud ring.

A device for estimating Direction of Arrival (DOA) of sound from Q≥1 sound sources is provided. The device is configured to obtain a phase difference matrix, which includes measured phase difference values, each of the measured phase difference values being a measured value of a phase difference between two microphone units for a frequency bin in a range of frequencies of the sound. The device is further configured to generate a replicated phase difference matrix by replicating the measured phase difference values to other potential sinusoidal periods, calculate a DOA value for each phase difference value in the replicated phase difference matrix, and determine, as Q DOA results, the Q most prominent peak values in a histogram generated based on the calculated DOA values.

A device for estimating Direction of Arrival (DOA) of sound from Q≥1 sound sources is provided. The device is configured to obtain a phase difference matrix, which includes measured phase difference values, each of the measured phase difference values being a measured value of a phase difference between two microphone units for a frequency bin in a range of frequencies of the sound. The device is further configured to generate a replicated phase difference matrix by replicating the measured phase difference values to other potential sinusoidal periods, calculate a DOA value for each phase difference value in the replicated phase difference matrix, and determine, as Q DOA results, the Q most prominent peak values in a histogram generated based on the calculated DOA values.

A speech-based system utilizes a speech interface device located in the home of a user. The system may interact with different users based on different user profiles. The system may include messaging services that generate and/or provide messages to the user through the speech interface device. The speech interface device may have indicators that are capable of being illuminated in different colors. To notify a user regarding the currently active user profile, each user profile is associated with a different color and the color of the active profile is displayed on the speech interface device when the user is interacting with the system. To notify the user regarding awaiting messages, different types of messages are associated with different colors and the colors of the message types of waiting messages are displayed on the speech interface whenever the user is not interacting with the system.

An electronic device is disclosed. In addition, various embodiments identified through the specification are possible. The electronic device includes a display, a processor, and a memory storing instructions that, when executed by the processor, cause the processor to display, when a video supporting a plurality of orientation regions is played, a screen of a first orientation region among the plurality of orientation regions and a first text corresponding to a voice of a first speaker in the screen, and display, in response to a user input of selecting a voice of a second speaker located in a second orientation region, a screen of the second orientation region.

Disclosed are various approaches for authenticating a user through a voice assistant device and creating an association between the device and a user account. The request is associated with a network or federated service. The user is prompted to use a client device, such as a smartphone, to facilitate an authentication flow. A soundwave is played through the client device that contains a secret key, which is then sent to a service that validates the secret key. An association between the user account and the voice assistant device can then be created so that access to third party services can occur.

Disclosed are various approaches for authenticating a user through a voice assistant device and creating an association between the device and a user account. The request is associated with a network or federated service. The user is prompted to use a client device, such as a smartphone, to facilitate an authentication flow. A soundwave is played through the client device that contains a secret key, which is then sent to a service that validates the secret key. An association between the user account and the voice assistant device can then be created so that access to third party services can occur.

Systems and methods for providing dialog data, from an initially invoked automated assistant to a subsequently invoked automated assistant. A first automated assistant may be invoked by a user utterance, followed by a dialog with the user that is processed by the first automated assistant. During the dialog, a request to transfer dialog data to a second automated assistant is received. The request may originate with the user, by the first automated assistant, and/or by the second automated assistant. Once authorized, the first automated assistant provides the previous dialog data to the second automated assistant. The second automated assistant performs one or more actions based on the dialog data.

Methods, systems, and apparatus, including computer programs encoded on a computer storage medium, for implementing hotword recognition and passive assistance are disclosed. In one aspect, a method includes the actions of receiving, by a computing device that is operating in a low-power mode and that includes a display that displays a graphical interface while the computing device is in the low-power mode and that is configured to exit the low-power mode in response to detecting a first hotword, audio data corresponding to an utterance. The method further includes determining that the audio data includes a second, different hotword. The method further includes obtaining a transcription of the utterance by performing speech recognition on the audio data. The method further includes generating an additional user interface. The method further includes providing, for output on the display, the additional graphical interface.

A speech recognition method includes segmenting captured voice information to obtain a plurality of voice segments, and extracting voiceprint information of the voice segments; matching the voiceprint information of the voice segments with a first stored voiceprint information to determine a set of filtered voice segments having voiceprint information that successfully matches the first stored voiceprint information; combining the set of filtered voice segments to obtain combined voice information, and determining combined semantic information of the combined voice information; and using the combined semantic information as a speech recognition result when the combined semantic information satisfies a preset rule.