KaudioAnalyser
1.4.2indexedReal-time and file-based audio analysis with pitch detection (FFT/YIN), spectrum analysis, and note-frequency utilities including A4 tuning and formatted note output.
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Real-time and file-based audio analysis with pitch detection (FFT/YIN), spectrum analysis, and note-frequency utilities including A4 tuning and formatted note output.
KaudioAnalyser is a powerful audio analysis tool designed to provide acoustic characteristics from audio flow in real-time or from audio files.
This library can be used in KMP projects, and it works well with
Kodio.
This lib support to get Flow<Byte> from microphone and WAV file.
If you want to analyze an audio file, I recommend you use FFmpegKit, even though it has been retired, because it is still the easiest way to use FFmpeg in KMP.
If you want to contribute or have any questions, please feel free to open an issue or a pull request.
If you want to view a demo project using KaudioAnalyser, you can check out the Audio-Detection-Tool
repositories {
mavenCentral()
}
dependencies {
implementation("io.github.sor2171:kaudioanalyser:1.4.2")
}
println(getNoteData(512, 440, NoteNameStyle.Scientific))
// NoteData(name=C5, cent=-37.63199, frequency=512.0, a4=440.0, style=Scientific)
val frequency1 = getFrequency("D5", 440f) // 587.3295f
val frequency2 = "E3".getNoteFrequency() // 164.81378f
val frequency3 = "E3".getNoteFrequency(432) // 161.81717f
println(NoteData(name = "B6", a4 = 440f).fillAll())
// NoteData(name=B6, cent=0.0, frequency=1975.5334, a4=440.0, style=Scientific)
println(NoteData(frequency = 1024f, a4 = 440f).fillAll())
// NoteData(name=C6, cent=-37.63199, frequency=1024.0, a4=440.0, style=Scientific)
println(NoteData(frequency = 1024f, a4 = 440f, style = NoteNameStyle.Helmholtz).fillAll())
// NoteData(name=c''', cent=-37.63199, frequency=1024.0, a4=440.0, style=Helmholtz)
// if used in KMP with Kodio
var audioQuality by rememberSaveable { mutableStateOf(AudioQuality.Standard) }
var bufferSize by rememberSaveable { mutableStateOf(2048) }
// for YIN algorithm, this buffer size could be enough
var detectedFrequency by remember { mutableStateOf(0f) }
val detector = remember(audioQuality, bufferSize) {
PitchDetector(audioQuality.format.sampleRate, bufferSize)
}
LaunchedEffect(
isRecording,
isPausing,
audioQuality,
bufferSize
) {
if (isRecording && !isPausing) {
withContext(Dispatchers.Default) {
val recorder = Kodio.recorder(quality = audioQuality)
try {
delay(500) // wait for the recorder to be released
recorder.start()
recorder.liveAudioFlow?.toAudioWindows(
windowSize = bufferSize,
hopSize = bufferSize / 2,
channels = audioQuality.format.channels.count,
bytesPerSample = audioQuality.format.bytesPerSample
)?.collect { floatWindow ->
val frequency = detector.detectPitchYIN(floatWindow)
// or you can use FFT-based pitch detection, like this:
// val frequency = detector.detectPitch(floatWindow)
// it needs larger buffer size to be accurate
withContext(Dispatchers.Main) {
// stable the frequency by averaging with previous value
detectedFrequency = if (frequency > 0f) {
if (detectedFrequency == 0f) frequency
else detectedFrequency * 0.5f + frequency * 0.5f
} else {
0f
}
}
}
} finally {
recorder.release()
}
}
}
}
// also, used in KMP with Kodio
var audioQuality by rememberSaveable { mutableStateOf(AudioQuality.Standard) }
var bufferSize by rememberSaveable { mutableStateOf(8192) }
val analyzer = remember(bufferSize) { SpectrumAnalyzer(bufferSize) }
// spectrumData is a list of pairs of frequency and magnitude,
// you can use it to visualize the frequency spectrum.
var spectrumData by remember { mutableStateOf(FloatArray(0)) }
LaunchedEffect(
isRecording,
isPausing,
audioQuality,
bufferSize
) {
if (isRecording && !isPausing) {
withContext(Dispatchers.Default) {
val recorder = Kodio.recorder(quality = audioQuality)
try {
delay(500) // wait for the recorder to be released
recorder.start()
recorder.liveAudioFlow?.toAudioWindows(
windowSize = bufferSize,
hopSize = bufferSize / 2,
channels = audioQuality.format.channels.count,
bytesPerSample = audioQuality.format.bytesPerSample
)?.collect { floatWindow ->
spectrumData = analyzer
.processAudioWindow(floatWindow)
}
} finally {
recorder.release()
}
}
}
}
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