Audio Similarity Search
Powering your audio similarity search system with Zilliz Cloud (the fully managed version of Milvus)
High-Performant Audio Search with Unparalleled Precision
Experience a 10x performance boost on Zilliz Cloud with advanced indexing algorithms, ensuring millisecond-level latency. Benefit from unparalleled precision using hybrid vector search with scalar filtering and range search capability.
Efficiently Managing Your Spiking Audio Data
Experience horizontal and independent scaling for computing and storage, aligning perfectly with your budget and evolving needs. Manage billions of vectors within hours with efficient bulk inserts.
Real-Time Responses for Optimized User Experience
Zilliz Cloud guarantees consistently up-to-date search results through real-time data insertion, deletion, and seamless data flows, significantly optimizing the user experience.
Always On, Always Reliable
Zilliz Cloud builds resilient audio search systems, ensuring uninterrupted services even in unexpected events through multiple replicas, component isolation, and robust backup and sync capabilities.
Simple Start, Amplified Productivity
Effortlessly deploys a large-scale similarity search service in minutes with user-friendly SDKs in multiple languages and streamlined data operations, ensuring an intuitive experience.
How Zilliz Cloud Powers Audio Similarity Search
A Zilliz-powered audio similarity search system works in the following ways:
- Audio clips are transformed into vector embeddings using an embedding model.
- Audio embeddings are ingested and stored in Zilliz Cloud.
- Users request audio clips similar to their queried ones.
- The audio query is transformed into vector embeddings using an embedding model.
- The query embeddings are sent to Zilliz Cloud for a similarity search.
- Zilliz Cloud performs ANN searches and retrieves the Top-K most relevant results.
- Zilliz Cloud returns the Top-K results to the user.