One variation of a method for autonomously training an animal includes: loading an autonomous training protocol for the animal onto a training apparatus configured to dispense units of a primary reinforcer responsive to behaviors performed by the animal; during an autonomous training session for the animal, accessing a video feed of a working field near the training apparatus, detecting the animal in the video feed, and executing the first autonomous training protocol; calculating a training score for the autonomous training session based on behaviors performed by the animal during the autonomous training session; selecting a manual training protocol, from a set of manual training protocols, based on the training score; generating a prompt to execute the first manual training protocol with the animal during a first manual training session; and transmitting the prompt to a user associated with the animal.

Methods and systems for processing audio signals containing speech data are disclosed. Biometric data associated with at least one speaker are extracted from an audio input. A correspondence is determined between the extracted biometric data and stored biometric data associated with a consenting user profile, where a consenting user profile is a user profile indicates consent to store biometric data. If no correspondence is determined, the speech data is discarded, optionally after having been processed.

Sound effect recommendations for visual input are generated by training machine learning models that learn coarse-grained and fine-grained audio-visual correlations from a reference image, a positive audio signals, and a negative audio signal. A positive audio embedding related to the reference image is generated from the positive audio signal and a negative audio embedding is generated from a negative audio signal. A machine learning algorithm uses the reference image, the positive audio embedding and the negative audio embedding as inputs to train a visual-to-audio correlation neural network to output a smaller distance between the positive audio embedding and the reference image than the negative audio embedding and the reference image.

In the field of media editing, in one embodiment, a computer-implemented method may include steps for receiving a video at a user device, generating a reversed video portion based on a selected portion of the video, and generating a media file by combining at least a first portion of the video and a second portion of the reversed video portion. In some embodiments, the method further include receiving a user input at the user device, the user input indicative of playback of the selected portion of the video in a forward direction and in a reverse direction; updating the reversed video portion based on the user input to yield an updated reversed video portion; and combining the selected portion and the updated reversed video portion to produce the media file.

In the field of media editing, in one embodiment, a computer-implemented method may include steps for receiving a video at a user device, generating a reversed video portion based on a selected portion of the video, and generating a media file by combining at least a first portion of the video and a second portion of the reversed video portion. In some embodiments, the method further include receiving a user input at the user device, the user input indicative of playback of the selected portion of the video in a forward direction and in a reverse direction; updating the reversed video portion based on the user input to yield an updated reversed video portion; and combining the selected portion and the updated reversed video portion to produce the media file.

Attributes of electronic content from a meeting are identified and evaluated to determine whether sub-portions of the electronic content should or should not be attributed to a user profile. Upon determining that the sub-portion should be attributed to a user profile, attributes of the sub-portion of electronic content are compared to attributes of stored user profiles. A probability that the sub-portion corresponds to at least one stored user profile is calculated. Based on the calculated probability, the sub-portion is attributed to a stored user profile or a guest user profile.

Attributes of electronic content from a meeting are identified and evaluated to determine whether sub-portions of the electronic content should or should not be attributed to a user profile. Upon determining that the sub-portion should be attributed to a user profile, attributes of the sub-portion of electronic content are compared to attributes of stored user profiles. A probability that the sub-portion corresponds to at least one stored user profile is calculated. Based on the calculated probability, the sub-portion is attributed to a stored user profile or a guest user profile.

Methods, apparatuses, and computer-readable products for selecting tracks. A plurality of request parameters are received from a client device. Based on those request parameters, plurality of bans, history track attributes, and artist identifiers are loaded from a database. A most recent discovery track is calculated based on the plurality of histories and the plurality of artist identifiers. An artist identifier is repeatedly selected from the plurality of artist identifiers along with a track type from a set of track types until a predetermined number of artist identifier and track type pairs have been selected. A plurality of candidate tracks for each selected artist identifier are loaded from a database. One track of the plurality of candidate tracks is repeatedly selected for each artist identifier and track type pair until one track has been selected for each pair of the predetermined number of artist identifier and track type pairs. The predetermined number of tracks that have been selected are returned to the client device.

Methods, apparatuses, and computer-readable products for selecting tracks. A plurality of request parameters are received from a client device. Based on those request parameters, plurality of bans, history track attributes, and artist identifiers are loaded from a database. A most recent discovery track is calculated based on the plurality of histories and the plurality of artist identifiers. An artist identifier is repeatedly selected from the plurality of artist identifiers along with a track type from a set of track types until a predetermined number of artist identifier and track type pairs have been selected. A plurality of candidate tracks for each selected artist identifier are loaded from a database. One track of the plurality of candidate tracks is repeatedly selected for each artist identifier and track type pair until one track has been selected for each pair of the predetermined number of artist identifier and track type pairs. The predetermined number of tracks that have been selected are returned to the client device.

Methods, systems, and computer programs for generating a playlist of media content items without explicit content. A vector space is created that represents explicit and non-explicit tracks in the same playlists created by other users and then tracks are filtered based on cosine distance between the “seed tracks” and all the tracks in the aforementioned playlist. The explicit tracks are filtered out, and tracks are sorted based on the affinity of the user to the artist.