Posts by SV1BDS

  • More LNB for 10Ghz

    Hi,

    When a LNB is used with IF of 432 MHz the output is reduced as it is designed for frequencies of more than 950 MHz. One solution is to increase the inductance in the bias tee of the lnb input. I mean the inductance of it's own not the external!!!

  • MY QO100 SETUP

    Hi,

    Some more results regarding noise level. 12.3 Hz is archived with variable noise level. Without noise 9.5 Hz is archived. With noise at 0.1 of amplitude of signal 16 Hz is archived.

  • MY QO100 SETUP

    Hi,

    I noticed that 0.1 sec frequency evaluations follow normal distribution (as normally expected). For every file that I test there are some decades of 0.1 sec samples. The mean error of 25 Hz found until now is computed at each 0.1 sec sample. I compute the mean value for each voice file and then measure the difference from the real frequency. In this way there are more realistic results that they did not depend from the distribution of the error but only from the mean value of the all the samples. The new mean error is found to be 12.3 Hz only.

  • MY QO100 SETUP

    Hi,

    The SSB offset frequency model is been added to a gnuradio embedded Python block. It takes as input 800 samples (0.1 sec) and return the frequency offset. It will be used in a complete SSB receiver for QO100.

  • MY QO100 SETUP

    Hi,

    This is a : dropbox link


    A demo working package is build to demonstrate SSB offset frequency finding. This is not a practical application for everyday usage but a demo one that can be used without special hardware. I personally use WSL Ubuntu 22.04.

    There are 3 files, two Python3 programs and the AI model file. The model file is not permited to used in a commercial application. To use the programs the user must make a websdr recording from QO100 websdr web interface. The system can find frequency shifts from -300 Hz to +300 Hz. In order not to loose audio information the bandwidth can be increased. Before use the findfreq.py be sure that you have do pip3 install numpy librosa tensorflow (if pip3 does not exist load it as a package). Then you can find the frequency shift by calling python3 findfreq.py websdr-recording-xxx.wav .

    If all is OK the signed mean frequency will displayed. Then we can convert the downloaded file calling the gnuradio python3 converter (be sure that you have gnuradio installed). The syntax is for example:

    python3 shiftfreq.py -i websdr-recording-xxx.wav -o outfile.wav -f 177

    Please note that 177 is an example of frequency shift that the program do. It must be same value but opposite sign of the mean value founded before. The outfile.wav can be played in order to determine if is on proper frequency.

    George SV1BDS

  • MY QO100 SETUP

    Quote from DC7KG

    Hi,

    does the artificial intelligence understand the speech?

    Detlev

    Hi Detlev,

    I come back to your question. In general AI understanding the speech. There exist python modules that you can feed with voice in various languages and return in text the content. But probably these will fail decoding if the voice is shifted even and a few Hz. A new training for recognising voice that is shifted a few Hz is required. The results maybe will be more poor than the existing. Of course if you get text, translation can be implemented and cross language QSO become a new reality in ham radio communications. One more idea I had during development of the current solution is a voice activated squelch that will recognise human voice and open audio. In general with AI it seems that new applications can implemented that it was not possible to do until now.

  • MY QO100 SETUP

    Hi,

    For comparison : I used CNN with 64,128,256 neurones and 64 final. 26000 different voices with 824000 training data of 0.1 sec (22.2 hours). No GPU and no external funding, during vacations!!!

  • File size limit

    Hi,

    I want to upload a file that is less than 5 Mb that do artificial intelligence SSB frequency beat. The file limit is 1 Mb. Is any plan to increase file limit?

  • MY QO100 SETUP

    Hi,

    A new model is implemented trained with variable levels of noise added to signals. It requires much more training time (9 hours vs 20 minutes) but with better results. It is better suited for audio and video. The produced model has now 25 Hz of mean error and 1376 of squared error. It must mentioned that data used for testing performance is not used for training.

  • MY QO100 SETUP

    Hi,

    Noise is added to learning (up to 0.1 of voice amplitude) and now can find frequency shift in a noisy environment. Performance is dropped to 45 Hz of mean error which is 7.5%. A gnuradio flowchart is planned to created that will use this.