Este hub reúne los mejores flujos para identificar canciones: tarareo en navegador, búsqueda por letra y apps móviles de reconocimiento. Compara herramientas por caso de uso y abre rápidamente las páginas oficiales en escritorio y móvil.
Descubre plataformas online eficaces para identificar canciones tarareando, cantando o silbando directamente en el navegador, sin instalar aplicaciones.
Midomi is one of the classic web-based song finder tools that lets users hum, sing, or whistle directly into a browser microphone to identify tracks. It works best when you can reproduce the chorus with steady pitch for 8 to 15 seconds. Use Midomi when you want fast, no-install melody matching on desktop or mobile web.
Google Hum to Search uses machine learning to match your hummed melody against large music catalogs in seconds. It is especially useful when you cannot remember the artist name or exact lyrics. This tool is ideal for quick “what is this song” moments and often returns multiple likely matches you can verify immediately.
AHA Music focuses on browser-based song recognition and is convenient for identifying music heard in online videos, streams, and web pages. The Chrome extension workflow is straightforward and requires minimal setup. Choose AHA Music when your main use case is detecting songs playing in your current tab rather than humming into a phone app.
ACRCloud provides enterprise-grade audio fingerprinting and music recognition APIs that power many consumer applications behind the scenes. It supports robust matching in noisy environments and offers metadata enrichment for identified tracks. Use ACRCloud when you need scalable recognition infrastructure or want to integrate hum and audio identification features into your own product.
WatZatSong is a community-powered song identification platform where users upload clips, hum recordings, or partial audio and get help from other music fans. It works well when algorithmic tools fail, especially for rare tracks, remixes, or low-quality recordings. Use it as a fallback channel for difficult cases where human pattern recognition can outperform automated matching.
Explora el ecosistema de Google para buscar canciones: Google Hum, consultas con Google Assistant y flujos de identificación desde la app.
This official Google guide explains how Hum to Search works and why melody contours can be matched even without perfect vocals. It is the best starting point for understanding feature behavior, expected confidence levels, and result interpretation. Read this first if you want to use Google’s humming recognition more effectively and set realistic expectations.
Google Assistant can identify songs by voice command, making hands-free music discovery simple on phones and smart devices. In practice, users can ask what song is playing and then compare candidate matches instantly. Use this option when audio is playing in your environment and you want the fastest voice-first identification flow.
The Google app provides a direct path to song identification through built-in search and microphone entry points, including convenient widget access on many Android devices. It is useful for users who want one-tap music recognition without opening multiple apps. Prefer this route for everyday, mobile-first song discovery with low friction.
Si no recuerdas la melodía, la búsqueda por letra y texto puede ayudarte a identificar canciones usando frases parciales y contexto.
Genius is a leading lyrics platform with extensive annotations, artist metadata, and strong full-text lyric search coverage. It is especially effective when you only remember a phrase and want contextual clues to confirm the exact track. Use Genius when you need both lyric matching and deeper interpretation around song meaning, references, and verified song pages.
Musixmatch combines synchronized lyrics, multilingual catalogs, and practical search tools for identifying songs from remembered lines. It performs well across mainstream and international tracks, making it useful for global audiences. Choose Musixmatch when lyric snippets are your main signal and you also want playback-aligned lyrics after identifying the song.
Lyrics.com offers broad lyric indexing and quick text-based lookup for songs, artists, and albums. It is a straightforward option when you need a simple search box and fast result scanning without extra product layers. Use it for quick lyric snippet matching and for cross-checking uncertain phrases found in other lyric search platforms.
Google remains highly effective for lyric-based discovery when you search with quotation marks around exact phrases and add context like artist, language, or genre. This method helps disambiguate common lyric lines that appear in multiple songs. Use this approach when dedicated lyric tools return too many candidates or cannot resolve partial wording.
Shazam’s lyric view is useful after initial recognition because it lets you validate whether the returned track truly matches the lines you remember. The synchronized lyric experience can help confirm chorus structure and timing. Use this tool when you have a probable match and want a second verification layer through lyric alignment.
SoundHound supports both melody and lyric-centric workflows, making it flexible for uncertain song memory scenarios. You can move between humming input and text input depending on what signal you remember best. Use SoundHound when your recall is mixed, such as partial lyrics plus a rough tune, and you need one tool to handle both paths.
Compara apps móviles de reconocimiento musical, desde opciones globales hasta alternativas regionales para mejorar la velocidad de coincidencia.
Shazam is one of the most widely used music recognition apps, optimized for instant identification from ambient audio. It typically delivers fast matches with artist, track title, and playback options, making it a reliable first stop for unknown songs. Choose Shazam when you need quick recognition in everyday situations like shops, cafes, radio, or short social clips.
QQ Music’s built-in song identification feature is popular among Chinese-speaking users and performs well for regional catalogs and mainstream releases. It combines recognition with immediate in-app playback and recommendation flows. Use QQ Music Song ID when your audience or personal listening habits focus on Chinese and East Asian music ecosystems.
SoundHound stands out by supporting both direct audio recognition and humming-based search in a single app experience. This dual-input flexibility makes it practical when you are unsure whether to use melody or environmental sound. Use SoundHound when you want one mobile tool for voice, humming, and lyric-assisted identification workflows.
NetEase Cloud Music offers integrated song identification tied to its recommendation engine and large streaming catalog. It is especially useful for users already in the NetEase ecosystem, where discovery and playback happen in one place. Use this option when you want seamless handoff from recognition to playlisting, comments, and personalized music suggestions.
The Musixmatch app is strong for users who value lyrics-first identification, synchronized captions, and multilingual support across devices. It helps bridge song recognition and lyric comprehension, especially when discovering music in unfamiliar languages. Choose Musixmatch when identifying the song is only part of your goal and lyric accessibility is equally important.
Respuestas rápidas sobre búsqueda por tarareo, identificación con Google y precisión de coincidencias.
Sí. Abre la app de Google, toca el micrófono y entra al modo de búsqueda de canciones para tararear la melodía. Para mejores resultados, tararea de 8 a 15 segundos en un entorno silencioso y compara las coincidencias principales.
Google Hum to Search, SoundHound y Midomi son opciones gratuitas sólidas. La mejor depende de tu dispositivo, región y tipo de música. Si la confianza es baja, prueba al menos dos herramientas para confirmar resultados.
Suele ser alta para canciones populares con melodía clara, pero puede bajar en temas de nicho, remixes o audio ruidoso. Mejorar la estabilidad del tono, usar fragmentos más largos y empezar por el estribillo aumenta la precisión.