| Autor: |
Schanke, Scott, Wang, Yaqiong, Liu, Zongxi, Zhao, Huimin |
| Rok vydání: |
2023 |
| Předmět: |
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| DOI: |
10.17605/osf.io/5x9th |
| Popis: |
In this work, we seek to evaluate how someone's voice features correlate to their music preferences. These voice features are evaluated by using a neural network embedding to reduce the voice features down to a matrix of numbers. This embedding will be used in subsequent regressions and Machine Learning algorithms to evaluate their similarity to other subjects within the subject pool. While this may have immediate impacts to music streaming, this also has bigger policy-based implications. If biometric data can be used as a means of personalization, firms may start using this as a means to personalize their services. Further discussion about the ethics and practice of biometrics is very important point of discourse, especially as there are no laws to date about this topic. |
| Databáze: |
OpenAIRE |
| Externí odkaz: |
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