I

I built a web DAW for lyricists and indie songwriters

Hacker News

I built a web DAW for lyricists and indie songwriters

Hey y'all. First HN post, so... I built a web DAW using Typescript, Faust, Web Audio Modules, and WASM. (fourtrack.fm) I spent a year building this, and about 4 months of that doing a from-scratch rewrite. It features virtual instruments and effects, sampling, re-sampling, audio recording, MIDI input. There is a piano roll for writing rhythms and melodies. There is a chart that allows you to write lyrics and arrange songs, and each part on the chart is tied to its music (e.g. verse, chorus, bridge) The DAW and all the current instruments and effects are totally free to use. You can save and import projects offline too. Cloud save through google drive works, but it's not yet verified so I wouldn't use it yet. In the future I may have sample packs, some other effects and instruments for sale as add-ons. No subscriptions, because that is anathema to creative culture. Basically, in fourtrack you can write songs on the "Chart" with your lyrics, and all the MIDI and audio clips will be associated with that part on the chart. As a songwriter, I always got annoyed that I was left with a 'notes' section in most DAWs or my email or notepad open next to it to write lyrics while writing a song. The aim of this software is to make this experience of songwriting, lyrics and music, more integrated. Furthermore, even though I could have gone the route of a more traditional waveform view multi-track recorder, I wanted to encapsulate the feeling of using a four track tape recorder. Sometimes limits give us freedom, especially in the creative realm. I hope that this tool reaches people interested in writing songs and trying to focus on the essence of what makes a song memorable - lyrics, melodies, rhythms. There are many superior tools for sound design and full fledged production. This is more along the lines of a musical sketchpad. I hope you enjoy and, sorry for all the bugs (: Thanks

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Actual performance

4points
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Launch Intel predictions

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Indie HackersFits the IH revenue-focused audience · Strong signals: songs · Missing: supports, reddit linkedin, podcasting
97%97% predicted probability of success on Indie Hackers, based on ML models trained on real launch data.
best fitHighest predicted score across all platforms for this description.
Product HuntOn track for Day 1 leaderboard · Strong signals: google, email, using · Missing: mac, agents, macos
88%88% predicted probability of success on Product Hunt, based on ML models trained on real launch data.
Hacker NewsStrong engagement from HN community · Strong signals: io · Missing: https docs, excited, just released
64%64% predicted probability of success on Hacker News, based on ML models trained on real launch data.
nativeThis product was originally launched on this platform.
AppSumoStrong fit for a featured deal · Missing: plus, platform, intuitive
56%56% predicted probability of success on AppSumo, based on ML models trained on real launch data.
TrustMRRLess likely to generate early MRR · Strong signals: month, google, way · Missing: mobile apps, ios, personal
46%46% predicted probability of success on TrustMRR, based on ML models trained on real launch data.
Acquire.comPre-revenue stage for this audience · Strong signals: arr, subscription · Missing: mrr, revenue, profit
14%14% predicted probability of success on Acquire.com, based on ML models trained on real launch data.
BetaListMay not resonate with beta-testers · Strong signals: audio · Missing: web3, chat, crypto
0%0% predicted probability of success on BetaList, based on ML models trained on real launch data.

Incorrect prediction on native model

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