Generating custom audio content for an exercise session
System, apparatuses, and methods can provide customized exercise sessions and customized videos corresponding to the exercise session. Audio clips can be dynamically selected to make custom audio content for an exercise session. The audio clips and metadata can be obtained, where the audio clips correspond to categories. The exercise session can include one or more components. A destination timeline for a component can include one or more first segments that require audio, and one or more second segments that can optionally have audio. Audio clips can be selected for the various segments, where a segment can be designated for a particular category of audio clips. Identification information for the selected audio clips can be saved and used to generate the custom audio content.
1. A method of generating a customized exercise video for a user, the method being implemented using (a) a computer system comprising one or more processors and (b) a sensor device comprising one or more sensors, the method comprising:
displaying a first exercise video to the user, wherein the first exercise video comprises video content of an exercise session comprising one or more components, the one or more components corresponding to one or more physical exercises and meeting one or more criteria with respect to one or more user ranks of the user;
receiving sensor data of the user from the sensor device, wherein the sensor data of the user are generated by the one or more sensors when the sensor device is attached to the user and the user is performing one or more of the one or more components, and wherein the sensor data of the user or data derived therefrom are indicative of the user's physical or physiological condition;
modifying, based on the sensor data of the user and by the one or more processors, at least one user rank of the one or more user ranks;
identifying, by the one or more processors, at least one new component meeting a criterion with respect to the at least one modified user rank; and
generating, by the one or more processors, a second exercise video comprising content of a physical exercise corresponding to the at least one new component.
2. A computer program product comprising a non-transitory computer readable medium storing a plurality of instructions that when executed control a computer system comprising one or more processors to customize an exercise video for a user, the instructions comprising:
displaying a first exercise video to the user, wherein the first exercise video comprises video content of an exercise session comprising one or more components, the one or more components corresponding to one or more physical exercises and meeting one or more criteria with respect to one or more user ranks of the user;
receiving sensor data of the user from a sensor device comprising one or more sensors, wherein the sensor data of the user are generated by the one or more sensors when the sensor device is attached to the user and the user is performing one or more of the one or more components, and wherein the sensor data of the user or data derived therefrom are indicative of the user's physical or physiological condition;
modifying, based on the sensor data of the user and by the one or more processors, at least one user rank of the one or more user ranks;
identifying, by the one or more processors, at least one new component meeting a criterion with respect to the at least one modified user rank; and
generating, by the one or more processors, a second exercise video comprising content of a physical exercise corresponding to the at least one new component.
3. A system for generating a customized exercise video for a user, the system comprises:
a sensor device comprising one or more sensors,
a computer system comprising one or more processors, the one or more processors being configured to:
(a) receive sensor data of the user from the sensor device, wherein
the sensor data of the user are generated by the one or more sensors when the sensor device is attached to the user and the user is following a first exercise video,
the first exercise video comprises video content of an exercise session comprising one or more components, the one or more components corresponding to one or more physical exercises and meeting one or more criteria with respect to one or more user ranks of the user, and
the sensor data of the user or data derived therefrom are indicative of the user's physical or physiological condition;
(b) modify, based on the sensor data of the user, at least one user rank of the one or more user ranks;
(c) identify at least one new component meeting a criterion with respect to the at least one modified user rank; and
(d) generate a second exercise video comprising content of a physical exercise corresponding to the at least one new component.
4. The method of claim 1 , wherein the sensor data indicate that the user was failing or tiring at a particular point while performing a particular component, and wherein modifying the at least one user rank comprises decreasing the at least one user rank.
5. The method of claim 1 , wherein the sensor data indicate that the user's performance meets a criterion, and wherein modifying the at least one user rank comprises increasing or decreasing the at least one user rank.
6. The method of claim 1 , wherein the one or more components of the first exercise video have an average component rank that is within a threshold of a target rank.
7. The method of claim 1 , wherein the at least one new component has a component rank in a range of the at least one modified user rank.
8. The method of claim 1 , wherein the one or more components of the first exercise video were selected by an optimization process that assigns a score to a plurality of possible sessions, each possible session including different components.
9. The method of claim 1 , wherein the one or more components of the first exercise video belong to one or more categories of exercises, and wherein the one or more categories of exercises were selected based on one or more of: categories of one or more previous exercise sessions, a constraint rule that specifies a preference to include two categories in a common session, or a constraint rule that excludes a category.
10. The method of claim 1 , wherein the one or more components of the first exercise video belong to one or more categories of exercises, and wherein the one or more categories of exercises comprise a cardio category.
11. The method of claim 1 , wherein the sensor device comprises a wearable sensor device.
12. The method of claim 1 , wherein the sensor device is supported by the user.
13. The method of claim 1 , wherein the sensor data of the user are indicative of the user's movements.
14. The computer program product of claim 2 , wherein the sensor data indicate that the user was failing or tiring at a particular point while performing a particular component, wherein modifying the at least one user rank comprises decreasing the at least one user rank.
15. The computer program product of claim 2 , wherein the sensor data indicate that the user's performance meets a criterion, and wherein modifying the at least one user rank comprises increasing or decreasing the at least one user rank.
16. The computer program product of claim 2 , wherein the one or more components of the first exercise video have an average component rank that is within a threshold of a target rank.
17. The computer program product of claim 2 , wherein the at least one new component has a component rank in a range of the at least one modified user rank.
18. The computer program product of claim 2 , wherein the one or more components of the first exercise video were selected by an optimization process that assigns a score to a plurality of possible sessions, each possible session including different components.
19. The computer program product of claim 2 , wherein the one or more components of the first exercise video belong to one or more categories of exercises, and wherein the one or more categories of exercises comprise a cardio.
20. The method of claim 6 , wherein the target rank is a rank of the user.
21. The method of claim 6 , wherein the target rank is offset from a rank of the user.
22. The computer program product of claim 16 , wherein the target rank is a rank of the user.
23. The computer program product of claim 16 , wherein the target rank is offset from a rank of the user.