Alternatives
Products that do what Australian Acoustic Observatory Search does
The Australian Acoustic Observatory (https://acousticobservatory.org/) has 360 microphones across the continent, and over 2 million hours of audio. However, none of it is labeled: We want to make this enormous repository useful to researchers. We have found that researchers are often looking for 'hard' signals - specific call-types, birds with very little available training data, and so on. So we built an acoustic-similarity search tool, allowing researchers to provide an example of what they're looking for, which we then match against embeddings from the A2O dataset. Here's…
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Hey HN! I just shipped a project I’ve been working on called Maroofy: https://maroofy.com You can search for any song, and it’ll use the song’s audio to find other similar-sounding music. Demo: https://twitter.com/subby_tech/status/1621293770779287554 How does it work? I’ve indexed ~120M+ songs from the iTunes catalog with a custom AI audio model that I built for understanding music. My model analyzes raw music audio as input and produces embedding vectors as output. I then store the embedding vectors for all songs into a vector database, and use semantic…
2023 · maroofy.com
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I am excited to announce a new tool for music producers and audio enthusiasts - a music audio search engine. With just a simple description of the groove you're looking for, our semantic search engine will output the most similar audio in seconds. I used the Freesound.org API to upload over 3,000 grooves to MongoDB, and combined all the relevant data such as tags, title, description, BPM, etc. into OpenAI's Text-Davinci to generate a unique description of each sound. I then embedded these descriptions using the Ada Embeddings Model and inserted them into Pinecone DB vector database, making…
2023 · muzic-sage.vercel.app
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2022 · github.com
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Fast, accurate STT for production-grade voice agents
May 2026 · ringg.ai
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In 2020, Magenta released DDSP [1], a machine learning algorithm / python library which made it possible to generate good sounding instrument synthesizers from about 6-10 minutes of data. While working with DDSP for a project, we realised how it was actually quite hard to find 6-10 minute of clean recordings of monophonic instruments. In this project, we have combined the DDSP architecture with a domain adaptation technique from speech synthesis [2]. This domain adaptation technique works by pre-training our model on many different recordings from the Solos dataset [3] first and then…
2022 · erlj.notion.site
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I built a podcast search engine that performs a semantic search within thousands of podcasts transcriptions. Technologies used are: OpenAI Whisper for transcriptions, BERT embeddings and FAISS as a vector database
2022 · voilib.com
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2023 · lama.nbnl.uk
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Our goal with this project is to build a completely open source, state of the art turn detection model that can be used in any voice AI application. I've been experimenting with LLM voice conversations since GPT-4 was first released. (There's a previous front page Show HN about Pipecat, the open source voice AI orchestration framework I work on. [1]) It's been almost two years, and for most of that time, I've been expecting that someone would "solve" turn detection. We all built initial, pretty good 80/20 versions of turn detection on top of VAD (voice activity detection) models. And…
2025 · github.com
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Hey HN! Mike & Warren here from HyperDX (now part of ClickHouse)! We’ve been building ClickStack, an open source observability stack that helps you collect, centralize, search/viz/alert on your telemetry (logs, metrics, traces) in just a few minutes - all powered by ClickHouse (Apache2) for storage, HyperDX (MIT) for visualization and OpenTelemetry (Apache2) for ingestion. You can check out the quick start for spinning things up in the repo here: https://github.com/hyperdxio/hyperdx ClickStack makes it really easy to instrument your application so you can go…
2025 · github.com
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2023 · webfft.net
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