Search audio for topics and sentiments.. Quickly sort through recordings of podcasts, meetings, or other content you have.

Useful for anyone who building software that interacts with audio data. Add better visibility into that data in minutes.


Steamship Packages are cloud-hosted AI libraries you can use from any programming environment.

Packages manage their own data & infrastructure in the cloud. Each instance gets its own private scope.


Download a Jupyter Demo

> npx try-steamship audio-analytics

From Python

from steamship import Steamship

# See GitHub README for Config requirements
instance = Steamship.use("audio-analytics", config={})

# See GitHub README for available methods
resp = instance.invoke('method', arg1=val1, arg2=val2)
Pulled from the GitHub repository.
# Audio Analytics Package

This project contains a Steamship Package that creates a search endpoint over audio files capable of filtering through
transcript, entities, and sentiments.

## Usage

from steamship import Steamship, Tag

instance = Steamship.use("audio-analytics", "my-workspace-name")

url = ""
analyze_task = instance.invoke("analyze_url", url=url).data

# Wait for completion
# See: examples/audio-analytics-python-client-demo.ipynb to see hows

# Query audio contents
# Note: more examples in examples/audio-analytics-python-client.demo.ipynb
query_tags = Tag.query(
    instance.client, 'kind "entity" and overlaps { kind "sentiment" and name "NEGATIVE" }'
unique_entities = { for tag in query_tags}
    f"There are {len(unique_entities)} people who have been referenced in a negative context:"
print(" * " + "\n * ".join([ for tag in query_tags]))

## Developing

Development instructions are located in [](

## Testing

Testing instructions are located in [](

## Deploying

Deployment instructions are located in [](

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