Tag: internet

Remote controlled shortwave radio system

Under construction…

The first in a series describing a system for internet remote control of a shortwave radio station. Its not something new. There are commercial products that provide remote operation of amateur radio transceivers. The purpose of this project is to make it possible to use shortwave radio sounds in musical performance, without the need of an antenna system.

Features:

  • Max/MSP for USB serial control of radio, OSC remote interface, user interface, Midi device handling, and an SQLITE database of preset frequencies.
  • Low latency, good quality audio using Soundjack by Alex Carot.
  • Hardware control of radio using Midi controllers (CDJ-101 and Launchpad)
  • Bi-directional OSC and VOIP using Logmein Hamachi VPN
  • Additional hardware control of AC power and antenna selection using Arduino and a WeMo switch.
  • TouchOSC Ipad audio mixer control using MOTU Cuemix
  • TeamViewer remote desktop software for logging into to base station compuer
  • Optional radio user interface control with Ipod TouchOSC, Griffin Powermate dial, and Korg Nano-kontrol.
  • Optional VOIP backup using Mumble.

System diagram

base station:

remote-radio-sys1

remote control:

remote-radio-sys2

 

 

 

 

 

 

Uploading tracks for Echonest analysis

Get track analysis data for your music using the Echonest API.

The track analysis includes summary information about a track including tempo, key signature, time signature mode, danceability, loudness, liveness, speechinesss, acousticness and energy along with detailed information about the song structure (sections) beat structure (bars, beats tatums) and detailed info about timbre, pitch and loudness envelope (segment).

track API documentation: http://developer.echonest.com/docs/v4/track.html

Its a two (or three) step process. Here’s an example of how to upload your track and get an audio summary, using curl from the command line in Mac OS. Note, you will need to register with Echonest to get a developer API key here: http://developer.echonest.com/raw_tutorials/register.html

upload

Note that the path to the filename needs to be complete or relative to the working directory. Also, in this example there was no metadata identifying the title of the song. You may want to change this before uploading. Replace the API key with your key.

curl -F “api_key=TV2C30KWEJDKVIT9P” -F “filetype=mp3” -F “track=@/Users/tkzic/internetsensors/echo-nest/bowlingnight.mp3” “http://developer.echonest.com/api/v4/track/upload”

Here is the response returned:

{“response”: {“status”: {“version”: “4.2”, “code”: 0, “message”: “Success”}, “track”: {“status”: “pending”, “artist”: “Tom Zicarelli”, “title”: “”, “release”: “”, “audio_md5”: “7edc05a505c4aa4b8ff87ba40b8d7624”, “bitrate”: 128, “id”: “TRLFXWY14ACC02F24C”, “samplerate”: 44100, “md5”: “78ccac72a2b6c1aed1c8e059983ce7c7”}}}

track profile

Here’s the query to get the analysis – using the ID returned by the previous call.  Replace the API key with your key.

curl “http://developer.echonest.com/api/v4/track/profile?api_key=TV2C30KYGHTUVIT9P&format=json&id=TRLFXWY14ACC02F24C&bucket=audio_summary”

Here is the response – which also contains a URL that you can use to get more detailed segment based acoustic analysis of the track.

{

“response”: { “status”: { “code”: 0, “message”: “Success”, “version”: “4.2” }, “track”: { “analyzer_version”: “3.2.2”, “artist”: “Tom Zicarelli”, “audio_md5”: “7edc05a505c4aa4b8ff87ba40b8d7624”, “audio_summary”: { “acousticness”: 0.64550727753299, “analysis_url”: “http://echonest-analysis.s3.amazonaws.com/TR/TRLFXWY14ACC02F24C/3/full.json?AWSAccessKeyId=AKIAJRDFEY23UEVW42BQ&Expires=1420763215&Signature=OLqYwvuzVmAqp1xLTi5x4CsYJuE%3D”, “danceability”: 0.5680872294350238, “duration”: 245.91673, “energy”: 0.19974462311717034, “instrumentalness”: 0.8089125726216321, “key”: 11, “liveness”: 0.10906007889455183, “loudness”: -25.331, “mode”: 1, “speechiness”: 0.03294587631927559, “tempo”: 93.689, “time_signature”: 4, “valence”: 0.43565861274829504 }, “bitrate”: 128, “id”: “TRLFXWY14ACC02F24C”, “md5”: “78ccac72a2b6c1aed1c8e059983ce7c7”, “samplerate”: 44100, “status”: “complete” } } }

analysis

Use the analysis_url returned by the previous request. Note that it expires a few minutes after the request. But you can always re-run the audio_profile request to get a new analysis_url

curl “http://echonest-analysis.s3.amazonaws.com/TR/TRLFXWY14ACC02F24C/3/full.json?AWSAccessKeyId=AKIASVIFEY23UEGE42BQ&Expires=1420763215&Signature=OLqYwvuzVmAqp1xLTi5x4CsYJuE%3D”

The analysis result is too large to display here. For more information, get the Echonest Analyze Documentation: http://developer.echonest.com/docs/v4/_static/AnalyzeDocumentation.pdf