AudioParamDescriptor

The AudioParamDescriptor dictionary of the Web Audio API specifies properties for an AudioParam objects. It is used to create custom AudioParams on an AudioWorkletNode. If the underlying AudioWorkletProcessor has a parameterDescriptors static getter, then the returned array of objects based on this dictionary is used internally by AudioWorkletNode constructor to populate its parameters property accordingly.

属性

name

The DOMString which represents the name of the AudioParam. Under this name the AudioParam will be available in the parameters property of the node, and under this name the AudioWorkletProcessor.process method will acquire the calculated values of this AudioParam.

automationRate 可选

Either "a-rate", or "k-rate" string which represents an automation rate of this AudioParam. Defaults to "a-rate".

minValue 可选

A float which represents minimum value of the AudioParam. Defaults to -3.4028235e38.

maxValue 可选

A float which represents maximum value of the AudioParam. Defaults to 3.4028235e38.

defaultValue 可选

A float which represents initial value of the AudioParam. Defaults to 0.

例子

To demonstrate creation and usage of custom AudioParams, we'll expand the example from AudioWorkletNode page. There we've created a simple node which outputs white noise. Here, additionally, we'll create a custom gain parameter, so we can directly change volume of the output (although you could use GainNode to achieve this as well).

First, we need to define a custom AudioWorkletProcessor, and register it. Note that this should be done in a separate file.

We expand the processor by adding a static parameterDescriptors getter. It will be used internally by the AudioWorkletNode constructor to populate its parameters with instantiated AudioParam objects.

// white-noise-processor.js
class WhiteNoiseProcessor extends AudioWorkletProcessor {
  static get parameterDescriptors () {
    return [{
      name: 'customGain',
      defaultValue: 1,
      minValue: 0,
      maxValue: 1,
      automationRate: 'a-rate'
    }]
  }

  process (inputs, outputs, parameters) {
    const output = outputs[0]
    output.forEach(channel => {
      for (let i = 0; i < channel.length; i++) {
        channel[i] = (Math.random() * 2 - 1) *
          (parameters['customGain'].length > 1 ? parameters['customGain'][i] : parameters['customGain'][0])
        // note: a parameter contains an array of 128 values (one value for each of 128 samples),
        // however it may contain a single value which is to be used for all 128 samples
        // if no automation is scheduled for the moment.
      }
    })
    return true
  }
}

registerProcessor('white-noise-processor', WhiteNoiseProcessor)

Next, in our main scripts file we'll load the processor, create an instance of AudioWorkletNode passing it the name of the processor, and connect the node to an audio graph.

const audioContext = new AudioContext()
await audioContext.audioWorklet.addModule('white-noise-processor.js')
const whiteNoiseNode = new AudioWorkletNode(audioContext, 'white-noise-processor')
whiteNoiseNode.connect(audioContext.destination)

Now we can change the gain on the node like this:

const gainParam = whiteNoiseNode.parameters.get('customGain')
gainParam.setValueAtTime(0, audioContext.currentTime)
gainParam.linearRampToValueAtTime(0.5, audioContext.currentTime + 0.5)

规范

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