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FastAudioProcess Roadmap 🗺️

Vision: To provide the fastest possible native and SIMD audio processing primitives for the FastJava ecosystem, optimizing where standard Java APIs fail.

🟢 v0.1.0: Initial Release (Current)

  • Format Conversions: MP3 to WAV conversion.
  • Resampling: Wave resampling to 44100Hz.
  • SIMD RMS Volume Calculation: High-performance volume level computation accelerated by Java 17 Vector API (SIMD).

🟢 v0.1.1: Audio DSP, FX & Waveform Release (Current)

  • Wake-Word Integration Utilities:
    • Frame Normalization: Energy-sensitive amplitude normalization.
    • Band-limited Pre-Emphasis Filter: High-pass filtering to boost higher speech frequencies.
    • Modellfriendly Frame-Chunking Pipelines: Buffering audio frames tailored to wake-word neural networks.
  • Log-Mel Feature Extraction: Ultra-fast extraction of MFCCs / Log-Mel spectrograms for local speech models.
  • Audio-Manipulation & FX Library:
    • Equalizer (IIR/FIR crossover filters)
    • Dynamic Processing (Noise Gate)
    • Pitch-Shifting (Native speed-preserved & resampling-based)
  • Audio I/O & Mixing:
    • Multi-channel mixing (downmix / upmix)
  • Waveform Visualization & Metering:
    • In-memory signal downsampling (generateWaveformPoints) for timeline plotting.
    • Absolute peak amplitude tracking (getFramePeak) for real-time streams.

🟡 v0.1.2: Future steps

  • Whisper & TTS Substrates:
    • Native integration helper for Whisper (STT) and local TTS engine (Style-TTS/VITS).
  • VAD Trigger Integration:
    • Stable Voice Activity Detection (VAD) runtime bindings.
  • Fast Audio Embedding extraction:
    • CLAP/Wav2Vec ONNX extraction.
  • AI Noise Reduction:
    • RNNoise / Demucs JNI bindings.
  • CREAM Integration:
    • Audio event markers on timetables and timeline node snapshots.

Focus: Performance is our USP. We optimize where Java stops.