Abstract: A content server generates media playlists for social events. The content server receives a seed value describing desired characteristics of media to present during a social event, and event parameters describing conditions for selecting media items to generate a media playlist for the social event. The content server selects media items based on the event parameters and the seed value, and uses the selected media items to generate the media playlist for the social event. The media items in the playlist are retrieved from a media database and provided to a media player for presentation at the social event.

Abstract: A content server generates media playlists for social events. The content server receives a seed value describing desired characteristics of media to present during a social event, and event parameters describing conditions for selecting media items to generate a media playlist for the social event. The content server selects media items based on the event parameters and the seed value, and uses the selected media items to generate the media playlist for the social event. The media items in the playlist are retrieved from a media database and provided to a media player for presentation at the social event.

Abstract: A content server generates media playlists for social events. The content server receives a seed value describing desired characteristics of media to present during a social event, and event parameters describing conditions for selecting media items to generate a media playlist for the social event. The content server selects media items based on the event parameters and the seed value, and uses the selected media items to generate the media playlist for the social event. The media items in the playlist are retrieved from a media database and provided to a media player for presentation at the social event.

Abstract: A content server generates sponsored audio including procedurally generated background music. The content server obtains reference music features describing musicological characteristics of reference songs as well as sponsored audio information received from a third-party. The content server determines music generation parameters based on the sponsored audio information and based on a music model mapping the reference music features to music generation parameters. The music model may incorporate machine learning techniques to improve the mapping. The content server generates background music by using the determined music generation parameters as input to a procedural music algorithm, and generates sponsored audio by combining the generated background music concurrently with an audio voiceover obtained from the sponsored audio information. The sponsored audio is provided to a client device, which presents the sponsored audio to a user.

Abstract: A content server generates sponsored audio including procedurally generated background music. The content server obtains reference music features describing musicological characteristics of reference songs as well as sponsored audio information received from a third-party. The content server determines music generation parameters based on the sponsored audio information and based on a music model mapping the reference music features to music generation parameters. The music model may incorporate machine learning techniques to improve the mapping. The content server generates background music by using the determined music generation parameters as input to a procedural music algorithm, and generates sponsored audio by combining the generated background music concurrently with an audio voiceover obtained from the sponsored audio information. The sponsored audio is provided to a client device, which presents the sponsored audio to a user.

Abstract: A sound processing device includes a separation unit configured to separate at least a music signal and a speech signal from a recorded audio signal, a noise suppression unit, a music feature value estimation unit, a speech recognition unit, a noise-processing confidence calculation unit, a music feature value estimation confidence calculation unit, a speech recognition confidence calculation unit, and a control unit configured to calculate at least one behavioral decision function of a speech behavioral decision function associated with speech and a music behavioral decision function associated with music based on a noise-processing confidence value, a music feature value estimation confidence value, and a speech recognition confidence value and to determine behavior corresponding to the calculated behavioral decision function.

Abstract: A sound processing device includes a separation unit configured to separate at least a music signal and a speech signal from a recorded audio signal, a noise suppression unit, a music feature value estimation unit, a speech recognition unit, a noise-processing confidence calculation unit, a music feature value estimation confidence calculation unit, a speech recognition confidence calculation unit, and a control unit configured to calculate at least one behavioral decision function of a speech behavioral decision function associated with speech and a music behavioral decision function associated with music based on a noise-processing confidence value, a music feature value estimation confidence value, and a speech recognition confidence value and to determine behavior corresponding to the calculated behavioral decision function.