diff --git a/pyproject.toml b/pyproject.toml
index a10027a..3b36be0 100644
--- a/pyproject.toml
+++ b/pyproject.toml
@@ -34,7 +34,6 @@ dev = [
     "tensorflow==2.20.0",
     "tensorflow-io==0.37.1",
     "tensorflow-hub==0.16.1",
-    "pydub==0.25.1",
     "librosa==0.11.0"
 ]
 test = [
diff --git a/tests/unit/nightingale/test_audio_preprocessor.py b/tests/unit/nightingale/test_audio_preprocessor.py
new file mode 100644
index 0000000..2f71958
--- /dev/null
+++ b/tests/unit/nightingale/test_audio_preprocessor.py
@@ -0,0 +1,57 @@
+import os
+from pathlib import Path
+
+import numpy as np
+import soundfile as sf
+import pytest
+
+from nightingale.data_pipeline.audio_preprocessor import AudioPreprocessor
+
+def _write_test_wav(path: Path, sr: int = 16000, channels: int = 1, duration=0.5):
+    t = np.linspace(0, duration, int(sr * duration), endpoint=False)
+    tone = 0.1 * np.sin(2 * np.pi * 440 * t)
+    if channels == 1:
+        data = tone.astype(np.float32)
+    else:
+        data = np.stack([tone, tone], axis=-1).astype(np.float32)
+    path.parent.mkdir(parents=True, exist_ok=True)
+    sf.write(str(path), data, sr)
+
+def test_is_yamnet_ready_true_for_matching_wav(tmp_path):
+    ap = AudioPreprocessor(target_sr=16000, mono=True)
+    p = tmp_path / "mono_16k.wav"
+    _write_test_wav(p, sr=16000, channels=1)
+    assert ap.is_yamnet_ready(str(p)) is True
+
+def test_load_audio_resamples_and_converts_to_mono(tmp_path):
+    ap = AudioPreprocessor(target_sr=16000, mono=True)
+    p = tmp_path / "stereo_22k.wav"
+    _write_test_wav(p, sr=22050, channels=2)
+    wav, sr = ap.load_audio(str(p))
+    assert sr == ap.target_sr
+    assert wav.dtype == np.float32
+    assert wav.ndim == 1  # mono
+
+def test_process_file_creates_output_and_is_ready(tmp_path):
+    ap = AudioPreprocessor(target_sr=16000, mono=True)
+    inp = tmp_path / "in" / "stereo_src.wav"
+    out = tmp_path / "out" / "converted.wav"
+    _write_test_wav(inp, sr=22050, channels=2)
+    # ensure output does not exist initially
+    assert not out.exists()
+    ap.process_file(str(inp), str(out))
+    assert out.exists()
+    assert ap.is_yamnet_ready(str(out)) is True
+
+def test_process_folder_creates_mirrored_structure(tmp_path):
+    ap = AudioPreprocessor(target_sr=16000, mono=True)
+    input_root = tmp_path / "input_root"
+    subfolder = input_root / "sub1"
+    file_in = subfolder / "sound.wav"
+    _write_test_wav(file_in, sr=22050, channels=2)
+
+    output_root = tmp_path / "output_root"
+    ap.process_folder(str(input_root), str(output_root))
+    expected_out = output_root / "sub1" / "sound.wav"
+    assert expected_out.exists()
+    assert ap.is_yamnet_ready(str(expected_out)) is True
\ No newline at end of file
diff --git a/uv.lock b/uv.lock
index 3536712..53c39a0 100644
--- a/uv.lock
+++ b/uv.lock
@@ -1807,7 +1807,6 @@ dev = [
     { name = "librosa" },
     { name = "matplotlib" },
     { name = "numpy" },
-    { name = "pydub" },
     { name = "scikit-learn" },
     { name = "seaborn" },
     { name = "tensorflow" },
@@ -1840,7 +1839,6 @@ dev = [
     { name = "librosa", specifier = "==0.11.0" },
     { name = "matplotlib", specifier = "==3.10.6" },
     { name = "numpy", specifier = "==2.3.3" },
-    { name = "pydub", specifier = "==0.25.1" },
     { name = "scikit-learn", specifier = "==1.7.2" },
     { name = "seaborn", specifier = "==0.13.2" },
     { name = "tensorflow", specifier = "==2.20.0" },
@@ -2334,15 +2332,6 @@ wheels = [
     { url = "https://files.pythonhosted.org/packages/48/f7/925f65d930802e3ea2eb4d5afa4cb8730c8dc0d2cb89a59dc4ed2fcb2d74/pydantic_core-2.41.4-pp311-pypy311_pp73-win_amd64.whl", hash = "sha256:c173ddcd86afd2535e2b695217e82191580663a1d1928239f877f5a1649ef39f", size = 2147775, upload-time = "2025-10-14T10:23:45.406Z" },
 ]
 
-[[package]]
-name = "pydub"
-version = "0.25.1"
-source = { registry = "https://pypi.org/simple" }
-sdist = { url = "https://files.pythonhosted.org/packages/fe/9a/e6bca0eed82db26562c73b5076539a4a08d3cffd19c3cc5913a3e61145fd/pydub-0.25.1.tar.gz", hash = "sha256:980a33ce9949cab2a569606b65674d748ecbca4f0796887fd6f46173a7b0d30f", size = 38326, upload-time = "2021-03-10T02:09:54.659Z" }
-wheels = [
-    { url = "https://files.pythonhosted.org/packages/a6/53/d78dc063216e62fc55f6b2eebb447f6a4b0a59f55c8406376f76bf959b08/pydub-0.25.1-py2.py3-none-any.whl", hash = "sha256:65617e33033874b59d87db603aa1ed450633288aefead953b30bded59cb599a6", size = 32327, upload-time = "2021-03-10T02:09:53.503Z" },
-]
-
 [[package]]
 name = "pygments"
 version = "2.19.2"