NCKitAudioNormalizer

Optional post-denoise loudness normalization on a mono Float32 buffer.

API

Swift

public enum NCKitAudioNormalizer {
    public static func applySpeechGatedMakeupGain(
        _ samples: inout [Float],
        sampleRate: Int,
        targetRmsDbfs: Float = -18,
        maxGainDb: Float = 15,
        peakCeilingDbfs: Float = -1
    )

    public static func softLimitInPlace(
        _ samples: inout [Float],
        peakCeilingDbfs: Float = -1
    )
}

Speech-gated makeup gain

Swift

import NCKit

var samples: [Float] = loadFloatSamples(from: denoisedWavURL)  // your reader

NCKitAudioNormalizer.applySpeechGatedMakeupGain(
    &samples,
    sampleRate: 48_000,
    targetRmsDbfs: -18,
    maxGainDb: 15,
    peakCeilingDbfs: -1
)

Peak limit only (no gain)

Swift

NCKitAudioNormalizer.softLimitInPlace(&samples, peakCeilingDbfs: -1)

After file denoise

Swift

try NCKitFileProcessor.processFile(
    inputURL: inputURL,
    outputURL: tempWavURL,
    processor: processor
)

var samples = try loadFloat32Wav(url: tempWavURL)
NCKitAudioNormalizer.applySpeechGatedMakeupGain(&samples, sampleRate: 48_000)
try writeFloat32Wav(samples: samples, sampleRate: 48_000, to: finalWavURL)

Parameters

Parameter	Default	Meaning
targetRmsDbfs	-18	Target speech RMS
maxGainDb	15	Max boost cap
peakCeilingDbfs	-1	Tanh limiter ceiling

No-op when the clip is too short or has too few speech windows.