System and Method for Biometrics-Based Music Recommendation

• US 20150186780A1
• Filed: 12/27/2013
• Published: 07/02/2015
• Est. Priority Date: 12/27/2013
• Status: Active Grant

• Current Assignee: Futurewei Technologies Incorporated (Huawei Investment & Holding Co., Ltd.)
• Original Assignee: Futurewei Technologies Incorporated (Huawei Investment & Holding Co., Ltd.)
• Inventors: Zhang, Jianyu, Chong, Chia Chin
• Granted Patent: US 10,078,691 B2
• Time in Patent Office: Days
• US Class Current: 1/1
• CPC Class Codes: G06F 16/636 by using biological or physiological data
• CPC Class Codes: G06F 16/686 using information manually generated, e.g. tags, keywords, comments, title or artist information, time, location or usage information, user ratings
• CPC Class Codes: G06F 17/30752 using information manually generated, e.g. tags, keywords, comments, title or artist information, time, location or usage information, user ratings
• CPC Class Codes: G06F 18/00 Pattern recognition
• CPC Class Codes: G06N 20/00 Machine learning
• CPC Class Codes: G06N 5/04 Inference or reasoning models
• CPC Class Codes: G06N 99/005 Learning machines, i.e. computer in which a programme is changed according to experience gained by the machine itself during a complete run neural networks G06N3/02; knowledge based models G06N5/00; fuzzy logic systems G06N7/02; adaptive control systems G05B13/00
• CPC Class Codes: G06V 40/10 Human or animal bodies, e.g. vehicle occupants or pedestrians; Body parts, e.g. hands
• CPC Class Codes: G06V 40/70 Multimodal biometrics, e.g. combining information from different biometric modalities

Abstract

Embodiments are provided herein for providing biometrics-based music recommendations to users. The biometric-based music recommendations take into account the changing music preferences of users from time to time as their biometrics change, such as due to users wellness states, being in different moods, engagement in different activities, and/or entering different environments. The schemes herein are implemented on user devices equipped or coupled to wearable devices capable of collecting biometrics data from users, such as heart rate, perspiration, and skin temperature data. The biometrics data of a user are collected and then processed into biometrics information. The biometrics information is then classified into a current wellness state of the user. A music recommendation is then provided to the user according to the biometrics information and the current wellness state of the user.

Claims

1. A method by a user device for providing biometrics based music recommendation to a user, the method comprising:

determining biometrics information according to biometrics data of the user;

classifying the biometrics information into a current wellness state of the user; and

providing a music recommendation to the user according to the biometrics information and the current wellness state of the user.

2. The method of claim 1 further comprising collecting the biometrics data using a biometric sensor embedded in the user device.

3. The method of claim 1 further comprising receiving, at the user device, the biometrics data from a separate device comprising a biometric sensor via a connection between the user device and the separate device.

4. The method of claim 1, wherein classifying the biometrics information into the current wellness state of the user includes selecting a biometric identifier representing the current wellness state of the user from a plurality of biometric identifiers representing a plurality of corresponding predefined wellness states of the user.

5. The method of claim 4, wherein providing the music recommendation to the user according to the biometrics information and the current wellness state of the user includes mapping the biometric identifier to a music recommender from a plurality of music recommenders representing a plurality of corresponding predefined music recommendation categories.

6. The method of claim 1 further comprising:

determining a user mood according to current or recent user music selection; and

determining the music recommendation according to a mapping between the biometrics information and the user mood.

7. The method of claim 6, wherein determining the music recommendation according to the mapping between the biometrics information and the user mood includes mapping a biometric identifier representing the current wellness state of the user to a mood classifier from a plurality of mood classifiers representing a plurality of corresponding predefined user moods.

8. The method of claim 6 further comprising learning the mapping between the biometrics information and the user mood according to music selection feedback and behavior of the user.

9. The method of claim 6, wherein the provided music recommendation to the user changes from time to time according to changes in at least one of user mood and biometric data.

10. A method by a user device for providing biometrics based music recommendation to a user, the method comprising:

receiving a biometric identifier representing a current wellness state of the user;

receiving a mood classifier representing a current mood of the user;

determining a music recommendation according to a predefined mapping between the biometric identifier and the mood classifier; and

indicating the music recommendation to the user.

11. The method of claim 10 further comprising establishing the predefined mapping between the biometric identifier and the mood classifier in accordance with music preferences and learning a music selection behavior of the user.

12. The method of claim 10 further comprising:

receiving biometrics data collected from one or more biometric sensor devices;

determining biometrics information of the user according to the biometrics data; and

classifying the biometrics information into the biometric identifier representing the current wellness state of the user.

13. The method of claim 10 further comprising:

collecting music files from one or more user storages; and

classifying, using audio analysis, the music files into a mood classifier representing the current mood of the user.

14. A user device for providing biometrics based music recommendation to a user, the user device comprising:

at least one processor; and

a non-transitory computer readable storage medium storing programming for execution by the at least one processor, the programming including instructions to;

determine biometrics information according to biometrics data of the user;

classify the biometrics information into a current wellness state of the user; and

provide a music recommendation to the user according to the biometrics information and the current wellness state of the user.

15. The user device of claim 14, wherein the user device further comprises an embedded biometric sensor, and wherein the programming includes further instructions to collect the biometrics data using the embedded biometric sensor.

16. The user device of claim 15, wherein the embedded biometric sensor is one of a temperature sensor, a heart rate sensor, and a sweat sensor.

17. The user device of claim 14, wherein the user device is connected to a separated device with biometric sensing capability, and wherein the programming includes further instructions to receive the biometrics data from the separate device.

18. The user device of claim 14, wherein the programming includes further instructions to:

determine a user mood according to current or recent user music selection; and

determine the music recommendation according to a mapping between the biometrics information and the user mood.

19. The user device of claim 18, wherein the programming includes further instructions to learn the mapping between the biometrics information and the user mood according to music selection feedback and behavior of the user.

20. The user device of claim 19, wherein the instructions to determine the user mood according to current or recent user music selection includes instruction to:

collect music files from one or more user storages; and

classify, using audio analysis, the music files into a mood classifier representing the user mood.