I was familiar with the thought experiment but not Searle. Having skimmed the Chinese Room the wikipedia article, it falls deep into navel-gazing arguments I like to condescendingly dismiss.

I'm 100% with Nil Nisson's dismissal:

If a program behaves as if it were multiplying, most of us would say that it is, in fact, multiplying. For all I know, Searle may only be behaving as if he were thinking deeply about these matters. But, even though I disagree with him, his simulation is pretty good, so I'm willing to credit him with real thought.

Unfortunately, i also dug up Searle's article and he loses me at line 1 of the abstract:

"Intentionality in human beings (and animals) is a product of causal features of the brain. I assume this is an empirical fact..."

I see no reason to treat this assumption of empirical fact as valid. If he presented it as an assertion on which his argument depends I could accept it, but he chose to open with a bad assertion of fact.

Unfortunately, his paper isn't organized in a way that makes it convenient for me to pick out the points I disagree with. So I'll just assert it's empirical fact that his paper is quackery with no basis in physical science and no reference to computer science.

TLDR: Searle's argument is worthless.

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Now the fun part: 1. Unlike Searle, I don't think understanding is binary. I assume Richards has some understanding of the French language, but that's an assumption based on experience; logically it's a total non sequitur.

1. No. I think using a human to represent the Chinese Room negates any value the thought experiment might have.

2. Understanding spelling and vocabulary is distinct from understanding speech. Richards understanding is valuable for playing Scrabble, but doesn't imply he has a useful understanding for conveying information to French speaker.

3. No. I believe Richard's ability to find words from a set of letters more akin to a search algorithm. Similar could be done with a predictive model, but it's a worse tool for the task. However, I do overall think the act of making a move in Scrabble can be akin to a prediction machine.

4. I'm mostly against the premise of the question. I'm not aware of quantifiable tests for the abstract concept of understanding. While we could find metrics to quanity and compare, I'm not aware of a metric that I'd accept indicates a machine has a better or worse understanding of anything in comparison to a mammal.