Decode Audio File Online
Hercules Montero
This is an experimental tool for listening to, analysing and decoding International Morse code. No information from the microphone is transmitted to the server, but the connection to the server is encrypted nonetheless.
To re-enable the microphone, you need to change your web browser's settings. For Chrome click on the video-camera icon with a red cross in the address bar. For Firefox click on the microphone icon in the address bar, or if it's not there, click on the globe icon instead.
The decoder will analyse sound coming from the microphone or from an audio file. The spectrogram of the sound is shown in the main graph along with a pink region showing the frequency being analysed. If the volume in the chosen frequency is louder than the "Volume threshold" then it is treated as being part of a dit or dah, and otherwise it records a gap (this is shown in the lower graph that looks like a barcode). From these timings it determines if something is a dit, dah, or a sort of space and then converts it into a letter shown in the message box.
In fully automatic mode, the decoder selects the loudest frequency and adjusts the Morse code speed to fit the data. If you want to fix the frequency or speed then click on the "Manual" checkboxes and type in your chosen values. The frequency can only be certain values and the closest allowed value will be chosen.
There are three parameters which are not automatic: the minimum and maximum volume filter settings and the volume threshold setting. The volume filter (which uses dB) discards very quiet (very negative) or very loud (close to zero) sounds and scales the size of the remaining data. The volume threshold is the value (0-255) which the measured volume in the analysed frequency must exceed to be counted as a dit or dah.
Convert Base64 to Audio online using a free decoder tool which allows you to decode Base64 as sound file and play it directly in the browser. In addition, you will receive some basic information about this audio file (duration, MIME type, extension, size). And, of course, you will have a special link to download the audio file to your device. If you are looking for the reverse process, check Audio to Base64.
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The decodeAudioData() method of the BaseAudioContext Interface is used to asynchronously decode audio file data contained in an ArrayBuffer that is loaded from fetch(), XMLHttpRequest, or FileReader. The decoded AudioBuffer is resampled to the AudioContext's sampling rate, then passed to a callback or promise.
This function implements two alternative ways to asynchronously return the audio data or error messages: it returns a Promise that fulfills with the audio data, and also accepts callback arguments to handle success or failure. The primary method of interfacing with this function is via its Promise return value, and the callback parameters are provided for legacy reasons.
A callback function to be invoked when the decoding successfully finishes. The single argument to this callback is an AudioBuffer representing the decodedData (the decoded PCM audio data). Usually you'll want to put the decoded data into an AudioBufferSourceNode, from which it can be played and manipulated how you want.
In this example loadAudio() uses fetch() to retrieve an audio file and decodes it into an AudioBuffer using the callback-based version of decodeAudioData(). In the callback, it plays the decoded buffer.
\n The decodeAudioData() method of the BaseAudioContext\n Interface is used to asynchronously decode audio file data contained in an\n ArrayBuffer that is loaded from fetch(),\n XMLHttpRequest, or FileReader. The decoded\n AudioBuffer is resampled to the AudioContext's sampling\n rate, then passed to a callback or promise.\n
\n A callback function to be invoked when the decoding successfully finishes. The\n single argument to this callback is an AudioBuffer representing the\n decodedData (the decoded PCM audio data). Usually you'll want to put the\n decoded data into an AudioBufferSourceNode, from which it can be played\n and manipulated how you want.\n
\n In this example loadAudio() uses fetch() to retrieve an audio\n file and decodes it into an AudioBuffer using the callback-based version of decodeAudioData(). In the callback, it plays the decoded buffer.\n
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I'm not looking to send/receive a fax via a modem, but just to "replay" the communications tones and parse out the fax message. I understand there are duplex issues and not knowing which end of the conversation is sending what.
This tool is part of the SpanDSP library from soft-switch project. You can download it from -switch.org/downloads/spandsp/ and configure it with --enable-tests. Source code is in tests/fax_decode.c file.
Note that the fax transmission is not so-much a transmission, as a 2-way communication. Thus, you cannot simply play this audio back into a fax machine and expect it to work. However, luckily, the fax image data transmission itself is uninterrupted, so it is possible to filter out the unnecessary data.
I dont know about using a program to do that, but you could always play the sound through your modem to a fax machine and print them out that way. assuming it plays correctly, you wouldnt need to worry about the two machines playing nice and getting an error because the bits that were identifiers wouldnt be heard by your machine while its transmitting. but this is all speculation to the highest degree.
Building on what Jasen said, you could set up your linux box to accept faxes, and then play that sound over the lines going to the computer. If your recording involves the ring tones sent over, it should work.
we are trying to use diferent trained models with online-audio-server-decode-faster functionality. All is OK with a normal triphone model (tri1) but when we try to use a SGMM model, we got this error: (the paths are edited)
You would create a copy of online-audio-server-decode-faster that would be
for SGMMs. The differences would be similar to the differences from
gmm-latgen-faster to sgmm2-latgen-faster. You may also have to create a
decodable object that works for online decoding for SGMM2, if it doesn't
already exist.
Dan
As much as I'd like to say 'use Espruino', until I make some more optimisations it's going to struggle to decode several different radio protocols at once, and then once you've done that you'll probably still want to communicate with a PC/server at some point in order to stick everything online.
What if I just had a Git Repo which used the same kind of code I'd make for the Espruino+Audio comms? We could then make a whole selection of different radio decoders (remote control sockets, LighwaveRF, doorbells, weather stations, electricity meters, oil level monitors, Espruinos, etc) that worked together.
Maybe later we can run it all on Espruino, but for now I'd just love to be able to put a bunch of really cheap home-made sensors around the house. I already have a PC that runs all the time (as I'd imagine a few of you do), and sticking an RF receiver into the audio jack of it would cost about 5.
Is anyone interested in working on this? I could come up with a very basic framework that grabbed the audio, converted it to a stream of bit lengths, and then pushed it through some decoders - it'd just be up to you to write decoders for the devices that you have (or make!)...
Also there is a library for the Pi that appears to be able to use a receiver connected to the Pi's IO directly (via WiringPi). I think someone posted this (or something similar) before, but we thought that it needed an Arduino - it seems it doesn't! Pretty impressive as I really thought this kind of thing would be hard on a Pi.
So does anyone know of a nice collection of RF decoders (in any language) - in a decent one-decoder-per-file form? Most of the stuff i've seen so far seems to be really nasty... If there isn't something then it seems like a good project - especially as it could just bridge everything to MQTT.
I've also got a webpage that will decode signals from the mains socket remote control and an 'Owl' electricity monitor. When I get it a bit more polished (hopefully with the ability to post data to something like Xively) I'll post it up on GitHub.
Personally I think it's a really neat solution. Maybe 3 in parts (and no software installation) and you can get all your 433Mhz wireless sensors online - and then maybe you'll decide you want to add some Espruino-based sensors too :)
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