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Build With AssemblyAI's Integrations
Make the most of your audio data by using AssemblyAI with top platforms and tools. Discover our wide range of integrations to improve your speech AI workflows with these use cases:
- LangChain: Develop applications that analyze and understand audio dialogues using AssemblyAI’s speech-to-text capabilities in your LLM projects.
- LlamaIndex: Build searchable audio archives by combining speech-to-text with LlamaIndex's indexing capabilities, making vast amounts of audio content accessible.
- Twilio: Enhance call transcription and analysis to improve customer interactions and service insights.
- Haystack: Implement transcription, summarization, and speaker diarization in your large language model workflows for detailed audio analysis.
- AWS: Scale your audio analysis projects by integrating AssemblyAI’s speech-to-text services into your AWS infrastructure for efficient processing.
Fresh From Our Blog
Summarize audio with LLMs in Node.js: Automatically summarize audio with Node.js and the AssemblyAI speech-to-text API. Read more>>
Filter profanity from audio files using Node.js: Filter profanity from audio files using Node.js and the AssemblyAI's Speech-to-text API. Read more>>
Content moderation on audio files with Python: Use AssemblyAI's API to automatically detect sensitive topics in speech data for content moderation. Read more>>
Our Trending YouTube Tutorials
Coding an AI Voice Bot from Scratch: Real-Time Conversation with Python: Build a real-time AI voice assistant using Python that can handle incoming calls, transcribe speech, generate responses, and provide a human-like conversational experience.
How to use @postman to test LLMs with audio data (Transcribe and Understand): Learn how to transcribe audio and video files using AssemblyAI and also how to use LeMUR, AssemblyAI's framework for using Large Language Models on spoken data without having to code at all.
Build A Talking AI with LLAMA 3 (Python tutorial): This tutorial shows you how to build a talking AI using real-time transcription with AssemblyAI, using LLAMA 3 as the language model with Ollama, and ElevenLabs for text-to-speech.
