A former MIT professor and authority on audio technology has found a flaw in Arbitron’s new Personal People Meter system of measuring radio audiences that puts stations with low-frequency content (news and talk) at a disadvantage to high-frequency content, such as music.

Here’s a link to the paper by Dr. Barry Blesser of 25-Seven Systems.

Arbitron used to measure radio audiences by asking listeners to fill out diaries in which they listed the stations they heard. Last year, Arbitron switched to PPMs, pager-like devices (pictured) worn by listeners. The PPM has a microphone to pick up what a listener hears. The PPM searches the incoming audio for a “watermark” that stations add to their signal to identify themselves. The “watermark” is imperceptible to the listener.

Blesser’s research indicates that it takes the PPM longer to register the watermark of low-frequency broadcasts than high-frequency programs.

Even the voice of an announcer can be a factor in whether a station is properly credited under the PPM system:

Considering that a male fundamental pitch might be as low as 80 Hz, some announcers may have a speaking style that is weak in high frequencies. Depending on the structure of the vocal cords and articulation style, there may or may not be any energy at the 12th harmonic of that pitch (which happens to be the center frequency of the first channel of the PPM encoder) for some announcer.

Because fricative phonemes (such as /s/, /z/, /th/, and /f/) contain a broadband hissing component that is like white noise, they can encode large amounts of data. But some announcers may have weak or rapid articulation of such fricatives. Consonants, although short in duration, are good for PPM; pregnant pauses and halting delivery are not. Speaking style matters.

While the typical radio program may produce perfect watermarking performance, and while the average reliability over the universe might be 99%, there are likely to be some announcer voices, vocal articulation styles, and specific genres of music that belong to the 1% failure cases. If a particular program on a particular station is one of the failure cases, that program might experience “bad luck” in its audience ratings.