diff --git a/data/chroma-stft-normalized-expected.npy b/data/chroma-stft-normalized-expected.npy
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diff --git a/data/f_analysis.npy b/data/f_analysis.npy
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diff --git a/data/filtered_features.npy b/data/filtered_features.npy
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diff --git a/data/picture.png b/data/picture.png
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diff --git a/data/sorted_features.npy b/data/sorted_features.npy
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diff --git a/data/white_noise.flac b/data/white_noise.flac
deleted file mode 100644
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diff --git a/data/white_noise.mp3 b/data/white_noise.mp3
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diff --git a/src/lib.rs b/src/lib.rs
index 72084b1..e9ad3b4 100644
--- a/src/lib.rs
+++ b/src/lib.rs
@@ -274,7 +274,7 @@ mod tests {
         let paths = vec![
             "./data/s16_mono_22_5kHz.flac",
             "./data/testcue.cue",
-            "./data/white_noise.flac",
+            "./data/white_noise.mp3",
             "definitely-not-existing.foo",
             "not-existing.foo",
         ];
@@ -317,7 +317,7 @@ mod tests {
             (true, PathBuf::from("./data/testcue.cue/CUE_TRACK001"), None),
             (true, PathBuf::from("./data/testcue.cue/CUE_TRACK002"), None),
             (true, PathBuf::from("./data/testcue.cue/CUE_TRACK003"), None),
-            (true, PathBuf::from("./data/white_noise.flac"), None),
+            (true, PathBuf::from("./data/white_noise.mp3"), None),
         ];
 
         assert_eq!(results, expected_results);
diff --git a/src/timbral.rs b/src/timbral.rs
index 6572662..86ab609 100644
--- a/src/timbral.rs
+++ b/src/timbral.rs
@@ -303,13 +303,14 @@ mod tests {
             assert!(0.0000001 > (expected - actual).abs());
         }
 
-        let song = Song::decode(Path::new("data/white_noise.flac")).unwrap();
+        let song = Song::decode(Path::new("data/white_noise.mp3")).unwrap();
         let mut spectral_desc = SpectralDesc::new(22050).unwrap();
         for chunk in song.sample_array.chunks_exact(SpectralDesc::HOP_SIZE) {
             spectral_desc.do_(&chunk).unwrap();
         }
+        println!("{:?}", spectral_desc.get_flatness());
         // White noise - as close to 1 as possible
-        let expected_values = vec![0.6706717, -0.9685736];
+        let expected_values = vec![0.5785303, -0.9426308];
         for (expected, actual) in expected_values
             .iter()
             .zip(spectral_desc.get_flatness().iter())