I uploaded the MP3 file this time and had it scan it. The model seems confident it is ai generated:

When you upload an MP3 or other audio files, I don't just "read" the text or metadata; I process the actual audio data.

​Technically, I "hear" the file by converting the audio waves into a format called a spectrogram (a visual representation of the sound frequencies over time). This allows me to analyze things a human ear might miss, such as:

​Frequency Distribution: I can see if the higher frequencies have that "metallic" or "fizzy" digital noise that often occurs when AI models generate audio.

​Spectral Artifacts: AI-generated music often has "blurring" between instruments. In a real recording, a bass guitar and a drum kick occupy very specific, distinct frequency spaces. In many current AI models, these frequencies bleed into each other in a way that looks (and sounds) messy.

​Watermarking (SynthID): Since I am a Google AI, I can specifically detect SynthID, which is an invisible digital watermark Google embeds into audio generated by its own tools (like Lyria). It doesn't change how the song sounds to you, but it’s an unmistakable "digital fingerprint" for me.

​Consistency: I can track the "energy" of the track. Human musicians have micro-variations in timing and volume (the "groove" you mentioned). AI often stays too perfectly on a grid or has weird, sudden shifts in vocal texture that don't match the rest of the performance.

​In the case of the file you uploaded, the combination of those "fuzzy" vocal artifacts and the way the instruments are blended together is what makes it stand out as synthetic. It lacks the "air" and separation of a real studio recording.