Content moderation on audio files with Python

In this tutorial, we learn how to use Python and state-of-the-art AI models for content moderation of audio files. We set up the environment by installing Python and the assemblyai package, then transcribe an audio file with content moderation enabled using aai.Transcriber object. The resulting transcript contains information about any potentially sensitive segments in the file. We print the content moderation results to identify sections of audio that are considered sensitive according to some internal criterion. Finally, we summarize the overall findings of the Content Moderation model and get a finer-grained breakdown of these issues by accessing severity score summary.

Use this post, company, and trend context to find content marketing opportunities, perform competitive analysis, or address product feature gaps via the Plushcap MCP server or the Plushcap API.