Returning a NumPy array (or list) of strings of words repeated N times
It would seem you're doing it the right way. One thing though: you might want to replace the following piece of code:

[[x[i]]*b[i] for i in range(len(x))]


A few points as to how you could improve this:


I suggest you use zip to iterate over two arrays simultaneously.
Also, prefer using () over [], since it creates a generator expression, rather than a list.
A similar argument holds with the construct join([ ... ]). Simply use join( ... ) instead, which would avoid creating the list in memory. 
Better variable names will also help with clarity.




([s] * count for s, count in zip(strings, counts))


Finally, formatting can make loads of difference:

import numpy as np

strings = ['yugoslavia', 'zealand', 'zimbabwe', 'zip', 'zone']
counts_array = np.array([[2,1,0,0,5], [0,0,1,3,0]])
result = np.apply_along_axis(
    lambda counts: ' '.join(item for sublist in
                                ([s] * count for s, count in zip(strings, counts))
                            for item in sublist),
    1, counts_array)


An equally ugly alternative might involve using two join statements:

result = np.apply_along_axis(
    lambda counts: ' '.join(filter(None,
                  (' '.join([s] * count) for (s, count) in zip(strings, counts)))),
    1, counts_array)


Note how I've had to use filter, as per this question, in order to remove the extra spaces emanating from the empty strings.