How to use the meyda.extract function in meyda

export const extract = signal => {
  const signalOfSize = Array.from(signal).slice(0, closestPowerOf2(signal.length));
  const features = Meyda.extract(['mfcc', 'spectralCentroid'], signalOfSize)
  console.log(features);
  return features;
};

fn: function() {
          for (let i = 0; i < numFrames; i++) {
            const start = i * frameSize;
            const end = start + frameSize;
            const frame = buffer.subarray(start, end);
            const res = Meyda.extract('mfcc', frame);
          }
        },
      });

      .map(frame => Meyda.extract('amplitudeSpectrum', frame))
      .map(binsPerFrame => getF0(binsPerFrame, sampleRate, humanVoiceRange));

analyser.getAudioFeatures = () => {
    analyser.getByteFrequencyData(freqDataArray);
    analyser.getFloatTimeDomainData(timeDataFloatArray);
    const frequencyData = Array.from(freqDataArray);
    Meyda.fftSize = fftSize;
    Meyda.bufferSize = fftSize;
    const {mfcc, spectralCentroid, rms, loudness} = Meyda.extract([
        'mfcc',
        'spectralCentroid',
        'rms',
        'loudness',
      ],
      timeDataFloatArray
    );
    return {frequencyData, rms, mfcc, spectralCentroid, loudness: loudness.total};
  };
  return analyser;

    .map(frame => Meyda.extract('mfcc', frame));

fn: function() {
          for (let i = 0; i < numFrames; i++) {
            const start = i * frameSize;
            const end = start + frameSize;
            const frame = buffer.subarray(start, end);
            const res = Meyda.extract('amplitudeSpectrum', frame);
          }
        },
      });

fn: function() {
          for (let i = 0; i < numFrames; i++) {
            const start = i * frameSize;
            const end = start + frameSize;
            const frame = buffer.subarray(start, end);
            const res = Meyda.extract('rms', frame);
          }
        },
      });