public static List <VokaturiAnalysis> CalculateEmotion(float[] samples, int frequency, int channels, float duration)
{
if (duration < 1)
{
throw new ArgumentException("Audioclip requires minimum length of 1.0s!");
}
int numSamplesPerChannel = (int)(duration * frequency);
//create voices for each channel
voices = new IntPtr[channels];
for (int i = 0; i < channels; i++)
{
voices[i] = VokaturiLib.VoiceCreate(frequency, numSamplesPerChannel);
}
if (channels == 2)
{
VokaturiLib.VoiceFillInterlacedStereoFloat32Array(voices[0], voices[1], samples.Length / 2, samples);
}
else
{
VokaturiLib.VoiceFillFloat32Array(voices[0], samples.Length, samples);
}
VokaturiLib.VokaturiQuality quality = new VokaturiLib.VokaturiQuality();
VokaturiLib.VokaturiEmotionProbabilities emotionProbabilities = new VokaturiLib.VokaturiEmotionProbabilities();
List <VokaturiAnalysis> vokaturiAnalyses = new List <VokaturiAnalysis>();
for (int i = 0; i < channels; i++)
{
VokaturiLib.VoiceExtract(voices[i], ref quality, ref emotionProbabilities);
vokaturiAnalyses.Add(new VokaturiAnalysis(quality, emotionProbabilities));
//Debug.Log($"Channel {i}: {quality}");
//Debug.Log($"Channel {i}: {emotionProbabilities}");
}
//destroy voices
for (int i = 0; i < channels; i++)
{
VokaturiLib.VoiceDestroy(voices[i]);
}
return(vokaturiAnalyses);
}
//calculates emotion for the audioClip, starting at offsetSeconds for length of duration and when needed wraps automatically
public static List <VokaturiAnalysis> CalculateEmotion(AudioClip audioClip, float offsetSeconds, float duration)
{
if (duration < 1)
{
throw new ArgumentException("Audioclip requires minimum length of 1.0s!");
}
if (audioClip.channels > 2)
{
throw new ArgumentException("Audioclip more than 2 channels not supported!");
}
int numSamplesPerChannel = (int)(duration * audioClip.frequency);
int numSamples = numSamplesPerChannel * audioClip.channels;
if (numSamples > audioClip.samples)
{
throw new ArgumentException($"Audioclip is smaller ({audioClip.samples}) than requested number of samples ({numSamples})!");
}
//create voices for each channel
voices = new IntPtr[audioClip.channels];
for (int i = 0; i < audioClip.channels; i++)
{
voices[i] = VokaturiLib.VoiceCreate(audioClip.frequency, numSamplesPerChannel);
}
int offsetSamples = (int)Math.Round(offsetSeconds * audioClip.frequency * audioClip.channels);
float[] samples = new float[numSamples];
audioClip.GetData(samples, offsetSamples); //automatically wraps when: offsetSamples + samples.Length > audioClip.samples
if (audioClip.channels == 2)
{
VokaturiLib.VoiceFillInterlacedStereoFloat32Array(voices[0], voices[1], samples.Length / 2, samples);
}
else
{
VokaturiLib.VoiceFillFloat32Array(voices[0], samples.Length, samples);
}
VokaturiLib.VokaturiQuality quality = new VokaturiLib.VokaturiQuality();
VokaturiLib.VokaturiEmotionProbabilities emotionProbabilities = new VokaturiLib.VokaturiEmotionProbabilities();
List <VokaturiAnalysis> vokaturiAnalyses = new List <VokaturiAnalysis>();
for (int i = 0; i < audioClip.channels; i++)
{
VokaturiLib.VoiceExtract(voices[i], ref quality, ref emotionProbabilities);
vokaturiAnalyses.Add(new VokaturiAnalysis(quality, emotionProbabilities));
//Debug.Log($"Channel {i}: {quality}");
//Debug.Log($"Channel {i}: {emotionProbabilities}");
}
//destroy voices
for (int i = 0; i < audioClip.channels; i++)
{
VokaturiLib.VoiceDestroy(voices[i]);
}
return(vokaturiAnalyses);
}