Clustering around the pitch floor

Austin Zheng

I use the following steps to get a scatter plot of frequency estimates:

1. Load clips into Praat

2. Use the To Pitch (ac) program in Praat with the following parameters:
    TimeStep: 60 ms;  PitchFloor: 50 Hz;  PitchCeiling: 400 Hz;  SilenceThreshold: 0;  VoicingThreshold: 0;
    OctaveCost: 0;  OctaveJumpCost: 0;  VoicedUnvoicedCost: 0; Hanning window
3. Save the Pitch object in a .txt file using Praat
4. Convert the .txt file to a .csv file using Python
5. Use Python to read the .csv file, filter out all candidates with frequency above 400 Hz, and select the candidate with the highest strength for each frame. Call these the strongest candidates.
6. Create a scatter plot of the strongest candidates

When I do this, I notice that there is a cluster of frequency estimates near the pitch floor. I continue to observe this when I lower the pitch floor to 25 Hz, and then to 10 Hz. It seems to me that the clustering is a result of measurement as some function of the pitch floor, rather than the presence of noise in the clips (which should have a fixed Hz, not one that changes based on the pitch floor). 

Could I ask about possible explanations for this observation? 

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