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Based on our record, Every Noice at Once seems to be a lot more popular than Amazon Polly. While we know about 422 links to Every Noice at Once, we've tracked only 42 mentions of Amazon Polly. We are tracking product recommendations and mentions on various public social media platforms and blogs. They can help you identify which product is more popular and what people think of it.
Create a new AWS IAM user and give it access to Amazon Polly. Get the AWS Access Key and AWS Secret Key. - Source: dev.to / 8 months ago
Amazon Polly it’s the most realistic text to speech I heard so far. Source: about 1 year ago
This was a long time ago, so I used Ivona voices and the program TextAloud (though I admit I pirated them because they were/are expensive). Looking into it Ivona was bought by Amazon and replaced by Amazon Polly which looks like it will fulfill your needs pretty well! Source: about 1 year ago
I was inspired by a post from Ran Isenberg last week. He created an automation to take his blog posts, run them through Amazon Polly, and create a spoken form of his content. His automation emails him a copy of the output so he can save it on his site and enable readers to listen to the post. This is great for consumers who are in the car or have accessibility needs. - Source: dev.to / about 1 year ago
Because the “AI software” is likely offered at an API and not everyone is skilled with programming to utilise it meaningfully. See https://aws.amazon.com/polly/. Source: about 1 year ago
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
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