The article delves into different approaches for music discovery, such as relying on experts’ recommendations, leveraging machine learning algorithms and utilizing APIs from platforms like Spotify and Last.fm. Additionally, it explores the possibility of building one’s own Shazam-like algorithm or song recognition system in Ubuntu 18.04.

music discovery

find music by combining choices of experts

build recommendation engine using spotify api

use machine learning to predict and recommend music

similar song matching using last.fm or spotify

netease 网易云听歌识曲

demo

self-hosted

shazam algorithm

blog: create your on shazam

findit another shazam clone

audiotag.info

portify recognize local music and add them to spotify playlist

wav_to_info.py

audio identifier

nowspinning get song info and cover art

shazam

shazamio reverse engineered shazam api with many supported functions

audiorec shazam client for linux, with cli support

midomi houndify soundhound

to get track info from soundhound (no cookie):

https://www.midomi.com/api/track?trackID=100282107076607645

the houndify music recognition api:

wss://houndify.midomi.com/

some lib for midomi found over here

it can also bridge yandex music recognition api

houndify also have api for that, but requires credit

free credits per day: 100

soundhound now requires 1 credit

soundhound python sdk

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