How is a "good" or "bad" singer defined in signal processing terms? I was watching the American and Indian idol auditions on youtube earlier in the day. I watched both successful and failed contestants and I was able to distinguish the really bad from the good singers even if I did not recognize the song or had ever heard the melody. Among the good singers, however, my limited knowledge of music prevented me from further discerning how good or bad they were. That set me thinking and I have the following questions to ask:   


When we say that a singer is "good", what do we mean by it in signal processing terms?
What factors/characteristics should we consider when we say (with some authority) that the person is a "good" singer? Is it pitch, the "tune", "melody"? How much weight should these (and other parameters) have when taking such a decision? 
How important a role would pitch play in this? I mean, if a man was to sing My heart will go on in perfect tune (with low pitch), would he get a score higher than a woman who sang the same song (but much less perfectly)?
When the contestants are shown singing, there is no background score playing. Yet, we are able to figure out who is singing well and who is not. So does that mean that the background score is pretty much irrelevant when it comes to deciding good/bad singing ability?  
Can the above points be extended to all types of songs and genres? For instance, in most classical music (vocal), the singer is pretty much primary. The instruments etc. are present simply to aid the singer. These songs are tougher to sing (any Hindustani classical or Largo al Factotum). Songs from rock/heavy metal (We will rock you/Suicide blonde) are a little easier to sing (IMO), because the instruments are primary and vocals are secondary.  
How do we (if at all) compare two songs?


I suppose that the above problem would eventually lead me to look at karaoke scoring algorithms, of which there are good open-source options (Performous, UltraStar Deluxe etc.). But before I look at these in detail, I thought it would be great to put this out and see what ideas others in the community (with a far greater knowledge of music and ability) have on this.  

P.S: Reference to some papers/material on this would be great.

P.S: Some of the above examples/points are my opinions. Given what I know about music, they may be way off the mark. Please feel free to add/suggest more questions or correct opinions I may have expressed. I will be only too happy to make the necessary edits.
First order, some DSP analysis might be able to detect central pitch, pitch variation (vibrato), timbre (overtone richness), and note onset, and say whether these are grossly out-of-tune, thin, or off-time, by how much and how often.

However, second-order, good musicians play with subtile variations in pitch (equal vs. just intonation, barbershop quartet harmonization as the key changes, etc.) and in timing (jazz, blues, "swing" rhythms, etc.).  How to "score" the latter is probably more a topic for computer AI than DSP.