The audio embedding pipeline converts an input audio into a dense vector which can be used to represent the audio clip's semantics. Each vector represents for an audio clip with a fixed length of around 0.9s. This operator is built on top of VGGish with Pytorch.
## Code Example
- Create audio embedding pipeline with the default configuration.
```python
from towhee import AutoPipes
p = AutoPipes.pipeline('audio-embedding')
res = p('test.wav')
res.get()
```
## **Interface**
**AudioEmbeddingConfig**
> You can find some parameters in [audio_decode.ffmpeg](https://towhee.io/audio-decode/ffmpeg) and [audio_embedding.vggish](https://towhee.io/audio-embedding/vggish) operators.
***weights_path:*** str
The path to model weights. If None, it will load default model weights.
***framework:*** str
The framework of model implementation. Default value is "pytorch" since the model is implemented in Pytorch.
***device***: int
The number of GPU device, defaults to -1, which means using CPU.
- [Exploring Multimodal Embeddings with FiftyOne and Milvus - Zilliz blog](https://zilliz.com/blog/exploring-multimodal-embeddings-with-fiftyone-and-milvus): This post explored how multimodal embeddings work with Voxel51 and Milvus.
- [About Towhee team | Zilliz](https://zilliz.com/authors/Towhee_team): Towhee is an open-source machine learning pipeline
that helps you encode your unstructured data into embeddings.
- [How to Get the Right Vector Embeddings - Zilliz blog](https://zilliz.com/blog/how-to-get-the-right-vector-embeddings): A comprehensive introduction to vector embeddings and how to generate them with popular open-source models.
- [The guide to clip-vit-base-patch32 | OpenAI](https://zilliz.com/ai-models/clip-vit-base-patch32): clip-vit-base-patch32: a CLIP multimodal model variant by OpenAI for image and text embedding.
- [Audio Retrieval Based on Milvus - Zilliz blog](https://zilliz.com/blog/audio-retrieval-based-on-milvus): Create an audio retrieval system using Milvus, an open-source vector database. Classify and analyze sound data in real time.
- [Vector Database Use Case: Audio Similarity Search - Zilliz](https://zilliz.com/vector-database-use-cases/audio-similarity-search): Building agile and reliable audio similarity search with Zilliz vector database (fully managed Milvus).
- [Making Machine Learning More Accessible for Developers - Zilliz blog](https://zilliz.com/learn/making-machine-learning-more-accessible-for-application-developers): Learn how Towhee, an open-source embedding pipeline, supercharges the app development that requires embeddings and other ML tasks.
- [An Introduction to Vector Embeddings: What They Are and How to Use Them - Zilliz blog](https://zilliz.com/learn/everything-you-should-know-about-vector-embeddings): In this blog post, we will understand the concept of vector embeddings and explore its applications, best practices, and tools for working with embeddings."
