Abstract: A data processing device includes: a digital signal processor; at least one processor; and at least one memory device configured to store a plurality of instructions, which when executed by the at least one processor, cause the at least one processor to operate to: output a first determination result relating to a scene of content through use of sound data; select processing for the sound data by a first selection method based on the first determination result; determine an attribute of the content from among a plurality of attribute candidates; and select the processing by a second selection method, which is different from the first selection method, based on a determination result of the attribute, wherein the digital signal processor is configured to execute the processing selected by the at least one processor on the sound data.

Abstract: Provided is a technology of learning an acoustic model with a certain degree of accuracy of sound recognition within a short calculation period.

Abstract: Detecting a replay attack on a voice biometrics system comprises receiving a speech signal; forming an autocorrelation of at least a part of the speech signal; and identifying that the received speech signal may result from a replay attack based on said autocorrelation. Identifying that the received speech signal may result from a replay attack may be achieved by: comparing the autocorrelation with a reference value; and identifying that the received speech signal may result from a replay attack based on a result of the comparison of the autocorrelation with the reference value, or by: supplying the autocorrelation to a neural network trained to distinguish autocorrelations formed from speech signals resulting from replay attacks from autocorrelations formed from speech signals not resulting from replay attacks.

Abstract: A computer-implemented method for training a neural end-to-end aspect based sentiment analysis (ABSA) system includes: inputting a batch of samples of a dataset into the neural end-to-end ABSA system, where the neural end-to-end ABSA system includes: a contextual language encoder configured to embed tokens with context; a first self-attention network configured to, based on an output of the contextual language encoder, detect an aspect term and provide a first output corresponding to the aspect term; and a second self-attention network configured to, based on the output of the contextual language encoder, detect the aspect term and provide a second output corresponding to the aspect term; and based on the inputted batch of samples and a consistency loss function, selectively adjusting weights of the neural end-to-end ABSA system based on consistent aspect term detection by the first self-attention network and the second self-attention network.

Abstract: Systems and methods for identifying a name are disclosed herein. In some embodiments, an apparatus may determine an attribute and/or attribute cluster. In some embodiments, an apparatus may determine a component word set as a function of an attribute and/or attribute cluster. In some embodiments, an apparatus may determine a candidate name by combining component words. In some embodiments, an apparatus may determine an intelligibility rating and/or an appeal rating for a candidate name.

Abstract: Methods and systems for videoconferencing include generating work quality metrics based on emotion recognition of an individual such as a call center agent. The work quality metrics allow for workforce optimization. One example method includes the steps of receiving a video including a sequence of images, detecting an individual in one or more of the images, locating feature reference points of the individual, aligning a virtual face mesh to the individual in one or more of the images based at least in part on the feature reference points, dynamically determining over the sequence of images at least one deformation of the virtual face mesh, determining that the at least one deformation refers to at least one facial emotion selected from a plurality of reference facial emotions, and generating quality metrics including at least one work quality parameter associated with the individual based on the at least one facial emotion.

Abstract: Example embodiments relate to methods and systems for playback of adaptive music corresponding to an athletic activity. A user input is received from a user selecting an existing song for audible playback to the user, the song comprising a plurality of audio layers including at least a first layer, a second layer, and a third layer. Augmented playback of the existing song to the user is initiated by audibly providing the first layer but not the second layer. Physical activity information derived from a sensor corresponding to a real-time physical activity level of a user is received. If the physical activity level of the user is above a first activity level threshold, the augmented playback of the existing song is continued by audibly providing the first layer and the second layer to the user.

Abstract: Systems and methods for podcast playback in a system including a playback device and a mobile device as a system controller are disclosed. In one embodiment, a playback system comprising a first playback device and a mobile device, the mobile device comprising computer-readable medium having stored thereon instructions executable to perform a method comprising capturing user input selecting an alarm function, capturing user input selecting a time for playing an alarm on the first playback device, capturing user input selecting a podcast channel, updating the graphical user interface to reflect the selected podcast channel, capturing user input specifying what order to play podcast episodes from the selected podcast channel, and starting playback of a first podcast episode on the first playback device according to the specified order to play podcast episodes by the previous user input and the selected time for playing an alarm.

Abstract: The present disclosure proposes a speech conversion scheme for non-parallel corpus training, to get rid of dependence on parallel text and resolve a technical problem that it is difficult to achieve speech conversion under conditions that resources and equipment are limited. A voice conversion system and a training method therefor are included. Compared with the prior art, according to the embodiments of the present disclosure: a trained speaker-independent automatic speech recognition model can be used for any source speaker, that is, the speaker is independent; and bottleneck features of audio are more abstract as compared with phonetic posteriorGram features, can reflect decoupling of spoken content and timbre of the speaker, and meanwhile are not closely bound with a phoneme class, and are not in a clear one-to-one correspondence relationship. In this way, a problem of inaccurate pronunciation caused by a recognition error in ASR is relieved to some extent.

Abstract: An audio system presents enhanced audio content to a user of a headset. The audio system detects sounds from the local area, at least a portion of which originate from a human sound source. The audio system obtains a voice profile of an identifies human sound source that generates at least the portion of the detected sounds. Based in part on the voice profile, the audio system enhances the portion of the detected sounds that are generated by the human sound source to obtain enhanced audio. The audio system presents the enhanced audio to the user.

Abstract: Techniques for providing and implementing a single skill associated with custom functionality and system-provided functionality are described. The skill may be used to invoke functionality in response to a user input without requiring a user remember exact formulations to cause the functionality to be performed. The skill may be associated with more than one domain. For example, the skill may be associated with custom sample user inputs (corresponding to the custom functionality) that correspond to a custom domain while the skill may also be associated with system-provided sample user inputs (corresponding to the system-provided functionality) associated with a non-custom domain.

Abstract: A system and method for extracting data from a piece of content using spatial information about the piece of content. The system and method may use a conditional random fields process or a bidirectional long short term memory and conditional random fields process to extract structured data using the spatial information.

Abstract: Methods and apparatus for decoding a compressed Higher Order Ambisonics (HOA) representation of a sound or soundfield. The method may include receiving a bit stream containing the compressed HOA representation and decoding, based on a determination that there are multiple layers, the compressed HOA representation from the bitstream to obtain a sequence of decoded HOA representations. A first subset of the sequence of decoded HOA representations is determined based only on corresponding ambient HOA components. A second subset of the sequence of decoded HOA representations is determined based on corresponding ambient HOA components and corresponding predominant sound components.

Abstract: An example implementation may involve a computing system receiving, from a media playback system, a request to initiate playback of a cloud queue. The cloud queue may currently have a first access status that authorizes a first set of queue operations, which may include playback of the cloud queue. After receiving the request to initiate playback, the computing system may cause audio tracks of the cloud queue to be queued in a local queue of the media playback system such that the media playback system may playback audio tracks of the cloud queue via the local queue. The computing system may modify the access status of the cloud queue to a second access status. This second access status may authorize a second set of queue operations on the cloud queue. The computing system may cause access to the local queue to be restricted to the second set of queue operations.

Abstract: Disclosed in the embodiments of the present disclosure are a method and apparatus used for generating a video, and an electronic device. The method comprises: while displaying an original video, acquiring audio material by means of background music of the original video, and acquiring image material, determining music points of the audio material, the music points being used for dividing the audio material into a plurality of audio clips; using the image material to generate a video clip for each music clip in the audio material so as to obtain a plurality of video clips, corresponding music clips and video clips having the same duration; and according to the times at which the music clips corresponding to the plurality of video clips appear in the audio material, splicing the plurality of video clips together, and adding the audio material as a video audio track to obtain a synthesized video.

Abstract: A gaming headset receives a plurality of audio channels comprising game audio channels and a chat audio channel during play of a particular game. The gaming headset monitors the received audio channels for predefined words that are associated with particular sounds in a data structure, and in response to detecting predefined words, filters out at least a portion of the detected predefined words from the received plurality of audio channels. The monitoring compares sounds on the received audio channels with the particular sounds in the data structure and also performs signal analysis on the audio channels during game play to detect the occurrence of the predefined words. The filtering mutes one or more of the plurality of audio channels so that the detected occurrence of the one of the predefined words is not output via speakers of the gaming headset.

Abstract: Techniques are provided for a playback device to play a media item using an audio setting corresponding to the media item and characteristics of the playback device. An example implementation involves a first playback device transmitting, to a first computing device, information indicating one or more characteristics of the first playback device and queue information indicating one or more media items in a playback queue to be played by the first playback device. The example implementation may further involve receiving, from the first computing device, one or more audio settings associated with the one or more media items, the one or more audio settings corresponding to the one or more media items and the one or more characteristics of the first playback device and playing a first media item of the one or more media items according to a first audio setting of the one or more audio settings.

Abstract: In general, techniques are described for obtaining audio rendering information from a bitstream. A method of rendering audio data includes receiving, at an interface of a device, an encoded audio bitstream, storing, to a memory of the device, encoded audio data of the encoded audio bitstream, parsing, by one or more processors of the device, a portion of the encoded audio data stored to the memory to select a renderer for the encoded audio data, the selected renderer comprising one of an object-based renderer or an ambisonic renderer, rendering, by the one or more processors of the device, the encoded audio data using the selected renderer to generate one or more rendered speaker feeds, and outputting, by one or more loudspeakers of the device, the one or more rendered speaker feeds.

Abstract: In an example implementation, a method may involve, while a first zone and a second zone of a media playback system are playing back respective media, receiving data indicating the occurrence of a first trigger condition. The method may also involve, based on the received data, modifying respective volume limits of the first zone and the second zone, wherein modifying the volume limit causes first volume levels that exceed the second limit to be reduced to respective second volume levels that are at or below the second limit. The method may also involve receiving data indicating the occurrence of a second trigger condition. The method may further involve, based on the received data, modifying the respective volume limits of the first zone and the second zone from the second limit to the first limit.

Abstract: An embodiment sets forth a technique for configuring one or more audio parameters. The technique includes presenting a first plurality of setting options associated with an audio parameter, wherein the first plurality of setting options comprises a first option having a same value as a first setting of the audio parameter and a second option having a first value different than the first setting; receiving a selection of one of the first option and the second option; based on the selection, presenting a second plurality of setting options associated with the audio parameter, wherein the second plurality of setting options comprises a third option having a same value as a second setting of the audio parameter and a fourth option having a second value different than the second setting; and setting the audio parameter based on a selection of at least one of the second plurality of setting options.