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# Triple Threat: The Power of Transcription, Summary, and Translation

**[Collabora Blog](https://daily.dev/sources/collabora)** · 4 min read · 0 upvotes · 0 comments

## Summary

Collabora built an open-source AI pipeline combining transcription, summarization, and translation to automate meeting workflows. The pipeline uses OpenAI's Whisper (fine-tuned on internal meetings for domain-specific terminology) for audio transcription, LangChain with Falcon-40B-Instruct for summarization, and outputs HTML pages with transcription, speaker diarization, and summaries. A Chrome/Firefox browser extension enables live transcriptions for web-conferencing and video platforms. The transcription server can run on a CPU instance for under $50/month.

## Full article

daily.dev links to this article rather than hosting it. Read it at the original source: <https://www.collabora.com/news-and-blog/blog/2023/08/03/triple-threat-the-power-of-transcription,-summary,-and-translation>

## Questions this post answers

### How much does it cost to run a Whisper transcription server on a CPU instance?

A Whisper transcription server can be deployed on a DataCrunch CPU instance for less than $50 per month, serving multiple users. The Whisper small model is resource-efficient enough to run on CPU without falling behind a live audio stream, making it a cost-effective option for real-time transcription.

_Teams evaluating self-hosted transcription costs find deployment comparisons like this on daily.dev._

### How do I use LangChain with Falcon-40B-Instruct to summarize meeting transcripts in Python?

Load the transcript with RecursiveCharacterTextSplitter (chunk_size=2000, chunk_overlap=100), then load Falcon-40B-Instruct via HuggingFace AutoModelForCausalLM with 8-bit quantization and device_map='auto'. Wrap it in a HuggingFacePipeline and use LangChain's load_summarize_chain with chain_type='map_reduce'. LangChain's abstraction makes it straightforward to swap Falcon for ChatGPT, Claude, or Instruct-GPT-J without major code changes.

_Developers building LLM summarization pipelines track LangChain and model swap patterns on daily.dev._

## Similar posts on daily.dev

- [Whisper transcribed a two-hour meeting on my laptop in four minutes, and none of it left the room](https://daily.dev/posts/whisper-transcribed-a-two-hour-meeting-on-my-laptop-in-four-minutes-and-none-of-it-left-the-room-jxk0grpcc) · XDA Developers · 1 upvotes · 0 comments
- [Practical Ways I Use AI Transcripts in Client-Facing Delivery Work](https://daily.dev/posts/practical-ways-i-use-ai-transcripts-in-client-facing-delivery-work-647u5hcqn) · Atomic Spin · 0 upvotes · 0 comments
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---

Tags: [#python](https://daily.dev/tags/python), [#llm](https://daily.dev/tags/llm), [#langchain](https://daily.dev/tags/langchain), [#speech-recognition](https://daily.dev/tags/speech-recognition), [#whisper](https://daily.dev/tags/whisper)

[View this post on daily.dev](https://daily.dev/posts/triple-threat-the-power-of-transcription-summary-and-translation-q08qnjste)

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