Identifying activity in an area even during periods of poor visibility using a video camera and an audio sensor are disclosed. The video camera is used to identify visible events of interest and the audio sensor is used to capture audio occurring temporally with the identified visible events of interest. A sound profile is determined for each of the identified visible events of interest based on sounds captured by the audio sensor during the corresponding identified visible event of interest. Then, during a time of poor visibility, a subsequent sound event is identified in a subsequent audio stream captured by the audio sensor. One or more sound characteristics of the subsequent sound event are compared with the sound profiles associated with each of the identified visible events of interest, and if there is a match, one or more matching sound profiles are filtered out from the subsequent audio stream.

A computer-implemented method of remotely influencing a performer at a live event via a customer mobile device is disclosed herein. The method includes: displaying a graphical user interface configured to receive user inputs; receiving a first user input including a user request for the performer at the live event; presenting predetermined terms and conditions associated with the user request; receiving a second user input including a user acceptance of the terms and conditions associated with the user request; transmitting the user request to a host server upon receiving the user acceptance of the terms and conditions associated with the user request; receiving a confirmation of the terms and conditions associated with the user request from the host server; and transmitting the user request for receipt by a performer mobile device of the performer during the live event.

A system for performing industrial automation control may include an audio device that receives audio data from an element in an industrial automation system. The audio device may determine orientation data based on the audio data. In addition, the audio device may determine an automation command to control a machine in the industrial automation system based on the audio data and the orientation data. After determining the automation command, the audio device may implement a first control action for the machine based at least in part on the automation command, where the first control action causes the machine to adjust an operation.

Example techniques related to a sub-index of a media index. An example implementation may involve maintaining, on a mobile device, a first index of audio tracks associated with a particular user profile, the audio tracks indexed in the first index consisting of a particular subset of audio tracks that are indexed in a second index. Based on the receiving the input data indicating the search query, the mobile device searches, within the first index, for audio tracks corresponding to the search query. If the audio tracks corresponding to the search query are not found in the first index, the mobile device sends to one or more servers of the cloud service, a request to search the second index for audio tracks corresponding to the search query.

A method of recommending video content using a computer-based system, the method including providing an initial set including a plurality of videos; extracting a digital audio signal from each of the plurality of videos; determining at least one temporal sequence of low-level audio features for each digital audio signal of the plurality of videos by analyzing the digital audio signals; calculating an audio similarity index between each of the plurality of videos by comparing their respective at least one temporal sequence of low-level audio features; receiving a query Q comprising reference to a seed video; the seed video being one of the plurality of videos; determining, for the seed video, a ranking of the rest of the initial set of videos based on their audio similarity index with respect to the seed video; and returning, as a reply to the query Q, an ordered set of video references according to the ranking.

An unidentified media content item may be received by a processing device. A set of features of the unidentified media content item may be determined. Metadata associated with the unidentified media content item may be determined. A first similarity between the metadata associated with the unidentified media content item and additional metadata associated with a known media content item from a media content repository may be determined. A second similarity between the set of features of the unidentified media content item and an additional set of features associated with the known media content item may be determined. The unidentified media content item may be identified as a cover of the known media content item based on the first similarity and the second similarity by the processing device.

Systems, methods, and computer program products for associating a media content clip(s) with other media content clip(s) having a different modality by determining first embedding vectors of media content items of a first modality, receiving a media content clip of a second modality, determining a second embedding vector of the media content clip of the second modality, ranking the first embedding vectors based on a distance between the embedding vectors and the second embedding vector, and selecting one or more of the media content items of the first modality based on the ranking, thereby pairing media content clips based on emotion.

A melody information processing method is described. A piece of Musical Instrument Digital Interface (MIDI) data corresponding to a song is received, a song identifier of the song is obtained, first melody information is generated according to the MIDI data, and the first melody information is stored in association with the song identifier in a melody database. Moreover, a user unaccompanied-singing audio data set that is uploaded from a user terminal is received, second melody information corresponding to the song identifier is extracted according to the user unaccompanied-singing audio data set, and the second melody information is stored in association with the song identifier in the melody database.

A method for categorizing streamed music based on a sample set of RTP scores for predetermined tracks. High-level acoustic attributes for tracks are determined by an analyzed extraction of low-level data from the tracks. The high-level acoustic attributes are used to develop computer-derived RTP scores for the tracks based on the sample set, which includes RTPs score for a plurality of possible combinations of a rhythm score (R), a texture score (T), and a pitch score (P) respectively from a R range, a T range, and a P range. At least some of the RTP scores correspond to human-determined RTP scores for predetermined tracks among a plurality of predetermined tracks. Each RTP score corresponds to a category among a plurality of categories. The computer-derived RTP scores are used to determine a category for each track among the plurality of categories. Playlists of the tracks are based on one or more of the categories.

The present invention relates to a method of representing wave oscillations uniquely into machine readable data structure, and search technique using Symphonic quality of audio content as compared to lexicality of the audio content. An automatic computer processing acoustic search method for converting an input audio encoding of an utterance into an output that rhythmically harmonizes with a target song is disclosed.