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Audio search engine

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Types of audio search
– Audio search from text: User enters text into search bar, compared to database, matching results with descriptions and options to download.
– Audio search from image: Query by Example (QBE) system uses content-based image retrieval (CBIR), generates keywords from image, searches for audio files based on keywords and user preferences.
– Audio search from audio: User plays audio of a song, sound pattern derived from waveform and frequency representation, matched with patterns of sound files in database, displayed as search results.

Design and algorithms
– Audio search uses keywords found in media titles, attached text, and linked web pages.
– Some search engines can search recorded speech using phonetic search algorithms or text transcriptions.
– Applications like Munax and Shazam use ranking algorithms, acoustic fingerprinting, and databases to identify and match audio.

Notable audio search engines
– Deep audio search: Picsearch Audio Search powers image, video, and audio search for over 100 search engines.
– For smartphones: SoundHound (formerly Midomi) offers audio-based AI services and song identification capabilities. Shazam identifies songs by creating an acoustic fingerprint and comparing it to a central database.
– Doreso identifies songs by humming, singing, or direct input, providing information and options to purchase.
– Munax, a defunct company, released a multimedia search engine in 2005, allowing search for images, video, and audio in one place.
Z39.50 is a protocol used for searching and retrieving information from databases.

Additional information on audio search
– Audio search has evolved slowly and uses various search formats, all relying on keywords.
– Some search engines can search recorded speech, while others use phonetic algorithms or full audio transcription.
– Shazam uses an audio fingerprinting technique called spectrogram to identify songs from various sources.
– Munax shut down after releasing their multimedia search engine.
– Citation needed for some information.

Notable features and capabilities of audio search engines
– Picsearch Audio Search powers image, video, and audio search for over 100 search engines.
– SoundHound (formerly Midomi) offers audio-based AI services and song identification capabilities.
– Shazam identifies songs by creating an acoustic fingerprint and comparing it to a central database.
– Doreso identifies songs by humming, singing, or direct input, providing information and options to purchase.
Z39.50 is a protocol used for searching and retrieving information from databases.

An audio search engine is a web-based search engine which crawls the web for audio content. The information can consist of web pages, images, audio files, or another type of document. Various techniques exist for research on these engines.

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