This link has been bookmarked by 14 people . It was first bookmarked on 28 Jan 2008, by Trent Adams.
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16 Mar 08
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25 Feb 08
Jeff GiddensThe Echo Nest is a music technology company founded by two MIT Media Lab PhDs. The Echo Nest’s proprietary music analyzer API automatically analyzes audio (e.g. aif, wav, mp3, m4a), and generates an XML file that describes the musical and structural con
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23 Feb 08
Thomas Edmonds Jr.The Echo Nest is a music technology company founded by two MIT Media Lab PhDs. The Echo Nest’s proprietary music analyzer API automatically analyzes audio (e.g. aif, wav, mp3, m4a), and generates an XML file that describes the musical and structural con
audio music analysis api xml visualization mp3 beat generator
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21 Feb 08
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19 Feb 08
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03 Feb 08
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02 Feb 08
Bruno MartinsThe Echo Nest is a music technology company founded by two MIT Media Lab PhDs. The Echo Nest’s proprietary music analyzer API automatically analyzes audio (e.g. aif, wav, mp3, m4a), and generates an XML file that describes the musical and structural con
analysis api audio generator lab media metadata mir mit mp3 music processing service technology visualization webservice webservices xml
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31 Jan 08
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28 Jan 08
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The Echo Nest is a music technology company founded by two MIT Media Lab PhDs. The Echo Nest’s proprietary music analyzer API automatically analyzes audio (e.g., aif, wav, mp3, m4a), and generates an XML file describing the musical and structural content of the music. Computation takes about 1/50th of the duration of the track and the text output is about 1/20th of the size of its corresponding mp3.
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Unlike other automatic methods of acoustic feature extraction, which progress strictly on raw audio signal, our technology was inspired by how people perceive music. As a result, developers are able to automatically extract and use a wide array of time-based musical attributes for any song, including: timbre, pitch, rhythm, loudness, onsets, beats, tempo, sections, time signature, key, etc.
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27 Jan 08
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The Echo Nest is a music technology company founded by two MIT Media Lab PhDs. The Echo Nest’s proprietary music analyzer API automatically analyzes audio (e.g., aif, wav, mp3, m4a), and generates an XML file describing the musical and structural content of the music. Computation takes about 1/50th of the duration of the track and the text output is about 1/20th of the size of its corresponding mp3. Unlike other automatic methods of acoustic feature extraction, which progress strictly on raw audio signal, our technology was inspired by how people perceive music. As a result, developers are able to automatically extract and use a wide array of time-based musical attributes for any song, including: timbre, pitch, rhythm, loudness, onsets, beats, tempo, sections, time signature, key, etc.
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