Identify music streaming service
using AI
Below is a free classifier to identify music streaming service. Just input your text, and our AI will predict what music genre a user is likely to enjoy - in just seconds.
API Access
import nyckel
credentials = nyckel.Credentials("YOUR_CLIENT_ID", "YOUR_CLIENT_SECRET")
nyckel.invoke("music-streaming-service", "your_text_here", credentials)
fetch('https://www.nyckel.com/v1/functions/music-streaming-service/invoke', {
method: 'POST',
headers: {
'Authorization': 'Bearer ' + 'YOUR_BEARER_TOKEN',
'Content-Type': 'application/json',
},
body: JSON.stringify(
{"data": "your_text_here"}
)
})
.then(response => response.json())
.then(data => console.log(data));
curl -X POST \
-H "Content-Type: application/json" \
-H "Authorization: Bearer YOUR_BEARER_TOKEN" \
-d '{"data": "your_text_here"}' \
https://www.nyckel.com/v1/functions/music-streaming-service/invoke
How this classifier works
To start, input the text that you'd like analyzed. Our AI tool will then predict what music genre a user is likely to enjoy.
This pretrained text model uses a Nyckel-created dataset and has 20 labels, including Amazon Music, Anghami, Apple Music, Bandcamp, Deezer, Fubotv, Google Play Music, Iheartradio, Itunes and Joox.
We'll also show a confidence score (the higher the number, the more confident the AI model is around what music genre a user is likely to enjoy).
Whether you're just curious or building music streaming service detection into your application, we hope our classifier proves helpful.
Need to identify music streaming service at scale?
Get API or Zapier access to this classifier for free. It's perfect for:
- User Content Filtering: This use case involves leveraging the false text classification function to identify inappropriate user-generated content in forums or comments sections. By filtering out offensive or misleading text, the music streaming service can maintain a safe and welcoming environment for all users.
- Metadata Correction: The function can be utilized to automatically classify incorrect song metadata submissions. By identifying texts that do not align with existing catalog information, the service can ensure that user-uploaded data remains accurate and up-to-date, improving the overall user experience.
- Playlist Recommendation Accuracy: Integrating the classifier can enhance the accuracy of playlist recommendations by filtering out irrelevant or contextually inappropriate song descriptions. This ensures that users receive smart, tailored recommendations that align with their listening habits.
- Social Media Monitoring: The music streaming service can use the false text classification function to monitor social media mentions related to its brand. By identifying and categorizing online conversations, the business can respond promptly to trends, feedback, or potential PR issues, ultimately boosting brand reputation.
- Ad Targeting Optimization: The classification function can aid in improving ad targeting efforts by identifying false or misleading text in advertisements. Better categorization of promotional content can enhance user engagement by ensuring that ads are relevant and accurately represented to the intended audience.
- Genre Classification Enhancement: The function can support genre classification efforts by filtering out erroneous or non-genre-specific text associated with music tracks. This can streamline the process of tagging songs, helping users discover new music that truly matches their tastes.
- Community Guidelines Enforcement: By implementing this text classification tool, the music streaming service can automate the enforcement of community guidelines. The ability to recognize and classify texts that contradict platform policies enables quicker moderation responses, creating a more harmonious online space.