I see this in https://everynoise.com/#updates > 2024-01-05 status update: With my layoff from Spotify on 2023-12-04, I lost the internal data-access required for ongoing updates to many parts of this site. Most of this, as a result, is now a static snapshot of what, for now, will be the final state from the site's 10-year history and evolution, hosted on my own server. Some pieces may get disabled and reenabled... - Source: Hacker News / 2 months ago

Anyone aware of a similar feature for foobar2000? I have an extensive library mostly tagged from Discogs, including release IDs. In theory, this should be sufficient to cluster music by genres, pull similar releases from Discogs "similar" feature and correlate data from https://everynoise.com. Obviously, in case of album mixed genres things will mix up, but I'm not sure there's a model that can correlate existing... - Source: Hacker News / 3 months ago

The article mentions Glenn McDonald's musical genre page (https://everynoise.com/, no longer refreshing with new Spotify data) as an example of a flexible graph-like exploration format, without being burdened by explicit connections. The author also has a thorough description of pros and cons of the general concept. - Source: Hacker News / 6 months ago

This is from Glenn McDonald's blog, founder of "Every Noise at Once". He was laid off from Spotify (discussed here briefly [0]) --- https://everynoise.com/ is now in "archival copy" mode [1][2]. Super sad to read / see this. [0] https://news.ycombinator.com/item?id=38650917 [2] https://twitter.com/EveryNoise/status/1736086849339244935. - Source: Hacker News / 7 months ago

Data exported using: https://benjaminbenben.com/lastfm-to-csv/ Album art compiled using: https://www.neverendingchartrendering.org/ Genre data compiled using: http://organizeyourmusic.playlistmachinery.com/# https://everynoise.com/ https://www.tunemymusic.com/transfer Gender, year and country of origin information manually compiled using Last.fm and wikipedia. Data analysis done in excel and image created in GIMP. Source: 7 months ago

Some good transcription solutions: https://zapier.com/blog/best-text-dictation-software/#windowsspeech https://otter.ai/ (Haven't actually tried Otter, but it gets a LOT of good reviews.). - Source: Hacker News / about 1 month ago

Of course, there are many existing solutions like Otter.ai or Fathom in the market. But in case you want to build a tool yourself and customize the output of it, then you are on the same page as me. To develop this application, we will use Unbody to convert input video transcriptions into intelligence/generative content and Appsmith to make it easy to design and build the UI of our app without extensive front-end... - Source: dev.to / 7 months ago

This is weird but I wonder if you could use something like https://otter.ai/. Record your notes as you are going. That should give you at least text of all of your welds. You’d still have to punch it later. Seems like there’s got to be a better way to do this. Stopping every time to break your flow sounds like a huge pain in the ass. Curious what you come up with. Source: 7 months ago

Is there any app from otter.ai that you run on personal machine? How does otter.ai process 4 different audio streams? Source: 7 months ago

Job laptop -> 3.5mm aux (this turns into speaker output) -> 3.5mm mic/audio splitter (this turns into microphone input) -> 3.5mm to usb-c adapter (cause my macbook only has 1 3.5mm aux) --> now the personal macbook has a new "mic input" from the job laptop. Which you can use to pipe audio into otter.ai to transcribe audio. You have to manually name them, but they learn in subsequent meetings. Source: 7 months ago