roboaviator

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  • May 14, 2021 at 9:44 am in reply to: Kaldi results / training a new model #2386
    roboaviator
    Participant

      Thank you very much for the detailed response! I will respond here if I have any more questions.
      Thanks again.
      –JD

      April 24, 2021 at 4:55 am in reply to: Kaldi results / training a new model #2352
      roboaviator
      Participant

        Thank you very much for your help.

        I will check my microphone setup and verify that the sound levels are similar to TAMAGO-03. Right now I have an AudioStreamFromMic node connected to a MultiGain node, and I am adjusting the GAIN parameter in MultiGain. Is this the correct approach to adjust volume?

        Regarding your second suggestion, how can I create a model to learn separated sounds for my microphone array? I have noticed that my separated signals are distorted. Do I need to make changes to sub_separation or is there another process?

        I will continue to use the large vocabulary language model.

        Thank you again for your help.
        John

        April 9, 2021 at 1:23 am in reply to: Computing NoiseCM matrix for LocalizeMUSIC #2329
        roboaviator
        Participant

          Excellent, thank you.

          March 16, 2021 at 9:56 pm in reply to: Computing Real-time Noise Level in dB #2308
          roboaviator
          Participant

            Since BGNEstimator returns the noise spectrum (Matrix<float>), is there a node that will compute the overall power contained in the spectrum (a single float dB value for the overall noise level)?

            Thank you,
            JD

            March 15, 2021 at 3:46 am in reply to: Computing Real-time Noise Level in dB #2292
            roboaviator
            Participant

              To give some more information, I am using an 8-channel microphone array and AudioStreamFromMic > MultiFFT to get the frequency spectra.

              February 5, 2021 at 12:37 am in reply to: Julius Feature Vector Length Error #2214
              roboaviator
              Participant

                Great, thank you for the information!
                -JD

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