Lukas

Lukas

@lukaesch.bsky.social

Making audio knowledge searchable http://audioscrape.com 🎙️🔮

14 followers8 following20 posts

PR pros: Want to try a powerful new tool to spot podcast trends before they hit headlines? We’re giving away 5 of our €129/mo plan for free in exchange for feedback. DM if you’re in - or tag a friend who should see this! #PR #MediaMonitoring #Podcast #PublicRelations

🔍 Exciting updates to Audioscrape Search! We've just shipped three major improvements to make podcast discovery even better: 1️⃣ Publication dates now visible with search results - know exactly when content was released! 2️⃣ Sort by date (newest first) or relevance - your choice

3️⃣ Optimized performance for massive searches - no more crashing on iOS Safari, even with 5000+ results! Search across transcriptions, podcast titles, episode titles, descriptions, and even speakers - all in one seamless experience.

1.19EUR/TB feels like you can store the entire internet now. @hetzner Object Storage is very inexpensive compared to AWS S3 or Azure Blob Storage. You can mount the Object Storage (S3 API) as a folder in your cloud instance and store large amounts of data efficiently.

Just added a GitHub-style activity tracker for podcasters on Audioscrape.com Fun fact: Most top podcasts publish nearly daily. The are just a few successful ones with an irregular posting schedule. The activity tracker makes it easy to grasp.

Anyone interested in the following topics? - Rust / Python - AI/Machine Learning - Audio transcriptions - Speaker diarization - Speaker detection - Speaker embeddings - Podcasts - Startups - Indiehacking

✨ New on Audioscrape: Intelligent Search Suggestions! 💡 Type less, discover more 🎯 Get instant topic suggestions 🎙️ Find specific podcasts faster 🤝 Community-driven suggestions Search through hundreds of thousands of podcast moments on Audioscrape in seconds!

How to build a simple search engine for podcast content: 1. Find and download podcast information (title, description, episodes, audio files, etc) 2. Transcribe audio files to get spoken text 3. Detect speakers using ML 4. Create a search index 5. Build user interface Example: audioscrape.com

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