Class: Kiribi::Gemma4E2B::AudioEncoder

Inherits:
Base
  • Object
show all
Defined in:
lib/kiribi/gemma4_e2b/audio_encoder.rb

Constant Summary collapse

FILES = 
%w[audio_encoder.onnx audio_encoder.onnx_data].freeze

Instance Method Summary collapse

Methods inherited from Base

download, url_for

Constructor Details

#initialize(dest_dir) ⇒ AudioEncoder

Returns a new instance of AudioEncoder.



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# File 'lib/kiribi/gemma4_e2b/audio_encoder.rb', line 10

def initialize(dest_dir)
  FILES.each do |f|
    path = File.join(dest_dir, f)
    raise Kiribi::ModelNotDownloaded, %(gemma4-e2b/audio: #{f} missing. Run: Kiribi.download("gemma4-e2b/audio")) unless File.exist?(path)
  end
  @model = OnnxRuntime::Model.new(File.join(dest_dir, "audio_encoder.onnx"))
end

Instance Method Details

#encode(pcm_samples) ⇒ Object 



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# File 'lib/kiribi/gemma4_e2b/audio_encoder.rb', line 18

def encode(pcm_samples)
  pcm = pcm_samples.is_a?(String) ? pcm_samples.unpack("e*") : pcm_samples

  frame_length = 320
  hop_length = 160
  fft_length = 512
  num_mels = 128
  mel_floor = 0.001

  window = Array.new(frame_length) { 0.5 - 0.5 * Math.cos(2.0 * Math::PI * it / frame_length) }
  mel_filters = build_mel_filterbank(fft_length / 2 + 1, num_mels, 0.0, 8000.0, 16_000)

  pad_left = frame_length / 2
  padded = Array.new(pad_left, 0.0) + pcm
  mask_raw = Array.new(pad_left, false) + Array.new(pcm.length, true)

  frame_size = frame_length + 1
  num_frames = (padded.length - frame_size) / hop_length + 1

  input_features = []
  input_features_mask = []

  num_frames.times do |fi|
    start = fi * hop_length
    windowed = frame_length.times.map { padded[start + it] * window[it] }

    mag = rfft_magnitude(windowed, fft_length)

    mel = num_mels.times.map do |m|
      sum = 0.0
      mag.each_with_index { |v, i| sum += v * mel_filters[i][m] }
      Math.log(sum + mel_floor)
    end

    end_idx = fi * hop_length + frame_size - 1
    valid = end_idx < mask_raw.length && mask_raw[end_idx]

    input_features << (valid ? mel : Array.new(num_mels, 0.0))
    input_features_mask << valid
  end

  padded_frames = ((input_features.length + 127) / 128) * 128
  while input_features.length < padded_frames
    input_features << Array.new(num_mels, 0.0)
    input_features_mask << false
  end

  @model.predict({
    "input_features" => [input_features],
    "input_features_mask" => [input_features_mask]
  })["audio_features"]
end