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LeMUR examples

Learn about different use cases for LeMUR with these examples.

Question and answer

Answer any questions about your audio.
"Identify any patterns or trends based on the transcript"

Quote or Citation

Extract quotes or citations from the transcript.
"List the timestamp X topic was discussed, provide specific citations"

Closed-ended questions

Answer simple yes or no questions.
"Did the customer express a positive sentiment in the phone call?"

Sentiment analysis

Assess the emotional sentiment of a conversation.
"What was the emotional sentiment of the phone call?"


Generate summaries for your audio data.
"Summarize key decisions and important points from the phone call transcript"

Summarize audio segments

Generate summaries for each segment or chapter of your audio data.
"Summarize the key events of each chapter"

Generate titles and descriptions

Generate metadata information about your audio, such as title and description.
"Generate an attention-grabbing YouTube title based on the video transcript"

Generate tags

Generate tags to organize and categorize your audio data.
"Generate keywords that can be used to describe the key themes of the conversation"

Action items

Extract action items from the meeting transcript and assign them to the corresponding speaker.
"What action items were assigned to each participant?"

Generate content

Generate long-form or short-form written content using your audio data.
"Generate a blog post with key information presented in bullet points from the transcript"


Rephrase parts of the transcript.
"Rephrase X segment from the transcript in a different way"

You can find more ideas and code examples in the AssemblyAI Cookbook repo on Github.