Abstract: Embodiments disclosed herein extending an audio track by joining similar portions. Audio features (e.g., spectral features, modulation features) may be extracted from the audio track. The audio track may be segmented, e.g., based on the audio features, and each segment may be slid through the audio track using a timestep. In each timestep, the sliding segment may be compared to the underlying portion of the audio track and a similarity score (e.g., a cross-correlation) may be generated. A self-similarity matrix may be generated based on the comparisons involving all the segments. The self-similarity matrix may be analyzed for peak values and segments corresponding to the peak values may be joined to extend the audio track. The embodiments may be applied to any kind of audio including music, ambient noise, speech, etc.

Abstract: Embodiments disclosed herein extending an audio track by joining similar portions. Audio features (e.g., spectral features, modulation features) may be extracted from the audio track. The audio track may be segmented, e.g., based on the audio features, and each segment may be slid through the audio track using a timestep. In each timestep, the sliding segment may be compared to the underlying portion of the audio track and a similarity score (e.g., a cross-correlation) may be generated. A self-similarity matrix may be generated based on the comparisons involving all the segments. The self-similarity matrix may be analyzed for peak values and segments corresponding to the peak values may be joined to extend the audio track. The embodiments may be applied to any kind of audio including music, ambient noise, speech, etc.

Abstract: Disclosed systems and methods include determining a desired trajectory within a multi-dimensional mental state space based on a path from an initial position within the multi-dimensional mental state space to a target position within the multi-dimensional mental state space, where the initial position corresponds to an initial mental state of the user, and where the target position corresponds to a target mental state of the user. Some embodiments include selecting a first media item that has an expected trajectory within the multi-dimensional mental state space that approximates the desired trajectory, and causing playback of the first media item.

Abstract: Embodiments disclosed herein extending an audio track by joining similar portions. Audio features (e.g., spectral features, modulation features) may be extracted from the audio track. The audio track may be segmented, e.g., based on the audio features, and each segment may be slid through the audio track using a timestep. In each timestep, the sliding segment may be compared to the underlying portion of the audio track and a similarity score (e.g., a cross-correlation) may be generated. A self-similarity matrix may be generated based on the comparisons involving all the segments. The self-similarity matrix may be analyzed for peak values and segments corresponding to the peak values may be joined to extend the audio track. The embodiments may be applied to any kind of audio including music, ambient noise, speech, etc.

Abstract: Embodiments disclosed herein extending an audio track by joining similar portions. Audio features (e.g., spectral features, modulation features) may be extracted from the audio track. The audio track may be segmented, e.g., based on the audio features, and each segment may be slid through the audio track using a timestep. In each timestep, the sliding segment may be compared to the underlying portion of the audio track and a similarity score (e.g., a cross-correlation) may be generated. A self-similarity matrix may be generated based on the comparisons involving all the segments. The self-similarity matrix may be analyzed for peak values and segments corresponding to the peak values may be joined to extend the audio track. The embodiments may be applied to any kind of audio including music, ambient noise, speech, etc.