Audio Processing Recipes¶

Practical recipes for common audio processing tasks.

Normalize Audio Volume¶

Normalize audio to target peak level.

import numpy as np
import coremusic as cm

def normalize_audio(input_path, output_path, target_peak=0.9):
    """Normalize audio to target peak level"""
    with cm.AudioFile(input_path) as input_file:
        # Read audio
        data_bytes, count = input_file.read(input_file.frame_count)
        samples = np.frombuffer(data_bytes, dtype=np.float32)

        # Find current peak
        current_peak = np.max(np.abs(samples))

        # Calculate and apply gain
        if current_peak > 0:
            gain = target_peak / current_peak
            samples *= gain
            print(f"Applied gain: {gain:.3f}x ({20*np.log10(gain):.2f}dB)")

        # Write output
        with cm.ExtendedAudioFile.create(
            output_path,
            cm.capi.fourchar_to_int('WAVE'),
            input_file.format
        ) as output_file:
            output_file.write(count, samples.tobytes())

# Usage
normalize_audio("quiet_audio.wav", "normalized.wav", target_peak=0.9)

Apply Fade In/Out¶

Add smooth fade effects to audio.

import numpy as np
import coremusic as cm

def apply_fades(input_path, output_path, fade_in_duration=2.0, fade_out_duration=2.0):
    """Apply fade in and fade out to audio"""
    with cm.AudioFile(input_path) as input_file:
        data_bytes, count = input_file.read(input_file.frame_count)
        samples = np.frombuffer(data_bytes, dtype=np.float32)

        sample_rate = input_file.format.sample_rate
        channels = input_file.format.channels_per_frame

        # Calculate fade lengths
        fade_in_samples = int(fade_in_duration * sample_rate)
        fade_out_samples = int(fade_out_duration * sample_rate)

        # Reshape to (frames, channels)
        frames = len(samples) // channels
        audio_2d = samples.reshape(frames, channels)

        # Apply fades
        fade_in_curve = np.linspace(0, 1, fade_in_samples)[:, np.newaxis]
        audio_2d[:fade_in_samples] *= fade_in_curve

        fade_out_curve = np.linspace(1, 0, fade_out_samples)[:, np.newaxis]
        audio_2d[-fade_out_samples:] *= fade_out_curve

        samples = audio_2d.flatten()

        # Write output
        with cm.ExtendedAudioFile.create(
            output_path,
            cm.capi.fourchar_to_int('WAVE'),
            input_file.format
        ) as output_file:
            output_file.write(count, samples.tobytes())

Change Sample Rate¶

Resample audio to different sample rate using ExtendedAudioFile.

import coremusic as cm

def resample_audio(input_path, output_path, target_sample_rate=48000.0):
    """Resample audio with automatic conversion"""
    with cm.ExtendedAudioFile(input_path) as input_file:
        in_format = input_file.file_format

        # Create output format with new sample rate
        out_format = cm.AudioFormat(
            sample_rate=target_sample_rate,
            format_id=in_format.format_id,
            format_flags=in_format.format_flags,
            channels_per_frame=in_format.channels_per_frame,
            bits_per_channel=in_format.bits_per_channel
        )

        # Set client format for automatic conversion
        input_file.client_format = out_format

        with cm.ExtendedAudioFile.create(
            output_path,
            cm.capi.fourchar_to_int('WAVE'),
            out_format
        ) as output_file:
            # Copy with automatic resampling
            chunk_size = 8192
            while True:
                data, count = input_file.read(chunk_size)
                if count == 0:
                    break
                output_file.write(count, data)

Mix Multiple Tracks¶

Mix multiple audio tracks into stereo output.

import numpy as np
import coremusic as cm

def mix_tracks(track_files, output_path, levels=None):
    """Mix multiple audio tracks with individual levels"""
    if levels is None:
        levels = [1.0] * len(track_files)

    # Load all tracks
    tracks = []
    max_frames = 0

    for file_path, level in zip(track_files, levels):
        with cm.AudioFile(file_path) as audio:
            data_bytes, count = audio.read(audio.frame_count)
            samples = np.frombuffer(data_bytes, dtype=np.float32)
            samples *= level  # Apply level
            tracks.append(samples)
            max_frames = max(max_frames, len(samples))

    # Pad tracks to same length
    for i in range(len(tracks)):
        if len(tracks[i]) < max_frames:
            tracks[i] = np.pad(tracks[i], (0, max_frames - len(tracks[i])))

    # Mix (sum all tracks)
    mixed = np.sum(tracks, axis=0)

    # Normalize to prevent clipping
    peak = np.max(np.abs(mixed))
    if peak > 1.0:
        mixed /= peak

    # Write output
    with cm.AudioFile(track_files[0]) as audio:
        format = audio.format

    with cm.ExtendedAudioFile.create(
        output_path,
        cm.capi.fourchar_to_int('WAVE'),
        format
    ) as output_file:
        num_frames = len(mixed) // format.channels_per_frame
        output_file.write(num_frames, mixed.tobytes())

# Usage
tracks = ["drums.wav", "bass.wav", "melody.wav"]
levels = [1.0, 0.8, 0.9]
mix_tracks(tracks, "mixed.wav", levels=levels)

Split Audio into Chunks¶

Split long audio file into smaller segments.

import coremusic as cm
from coremusic.audio import AudioSlicer
from pathlib import Path

def split_audio(input_path, output_dir, chunk_duration=30.0):
    """Split audio file into fixed-duration chunks"""
    output_dir = Path(output_dir)
    output_dir.mkdir(parents=True, exist_ok=True)

    slicer = AudioSlicer(input_path)
    duration = slicer.duration
    num_chunks = int(duration / chunk_duration) + 1

    for i in range(num_chunks):
        start_time = i * chunk_duration
        end_time = min((i + 1) * chunk_duration, duration)

        # Extract slice
        slice_data = slicer.slice_time_range(start_time, end_time)

        # Save chunk
        output_path = output_dir / f"chunk_{i:03d}.wav"
        slicer.save_slice(slice_data, str(output_path))

Merge Audio Files¶

Concatenate multiple audio files into one.

import coremusic as cm

def merge_audio_files(input_files, output_path):
    """Merge multiple audio files sequentially"""
    with cm.AudioFile(str(input_files[0])) as first_file:
        format = first_file.format

    with cm.ExtendedAudioFile.create(
        output_path,
        cm.capi.fourchar_to_int('WAVE'),
        format
    ) as output_file:
        for input_path in input_files:
            with cm.AudioFile(str(input_path)) as input_file:
                data, count = input_file.read(input_file.frame_count)
                output_file.write(count, data)

# Usage
files = ["intro.wav", "main.wav", "outro.wav"]
merge_audio_files(files, "complete.wav")