Apply Large Language Models to spoken data. A Large Language Model (LLM) is a machine learning model that uses natural language processing (NLP) to generate text. LeMUR is a framework that lets you apply LLMs to audio transcripts, for example to ask questions about a call, or to summarize a meeting.
Process Audio Files with LLMs Using LeMUR
Use LeMUR Specialized Endpoints
🆕 Receive AI coaching from LeMUR's Task Endpoint
🆕 Generate Action Items using LeMUR's Task Endpoint
🆕 Ask questions about a transcript using LeMUR's Task Endpoint
Calculating LeMUR Costs by Counting Input Tokens
Processing Speaker Labels with LeMUR's Custom Text Input Parameter
Use LeMUR for Speaker Identification
Extract Dialogue Data with LeMUR and JSON
Extract Citations from a Transcript with Semantic Search
Extract Quotes from a Transcript with LeMUR's Custom Text Input Parameter
🆕 Create Transcript Citations using OpenAI embeddings
| Model/Feature | Use with LeMUR |
|---|---|
| Sentiment Analysis | Leverage LeMUR for Customer Call Sentiment Analysis |
| Custom Vocabulary | Boost Transcription Accuracy with LeMUR |
| Auto Chapters | Creating Chapter Summaries with LeMUR's Custom Text Input Parameter |
| Summarization | Create Custom Summaries using LeMUR's Task Endpoint |
| Topic Detection | 🆕 Create Custom Topic Tags |
Implement a Sales Playbook Using LeMUR
How to Pass Context from Previous LeMUR Requests
Generate Action Items from a Meeting with LeMUR
Phone Call Segmentation Using LeMUR
🆕 SOAP Note Generation