  Given a sequence of deterministic matrices $A = A_N$ and a sequence of
deterministic nonnegative matrices $\Sigma=\Sigma_N$ such that $A\to a$ and
$\Sigma\to \sigma$ in $\ast$-distribution for some operators $a$ and $\sigma$
in a finite von Neumann algebra $\mathcal{A}$. Let $U =U_N$ and $V=V_N$ be
independent Haar-distributed unitary matrices. We use free probability
techniques to prove that, under mild assumptions, the empirical eigenvalue
distribution of $U\Sigma V^*+A$ converges to the Brown measure of $T+a$, where
$T\in\mathcal{A}$ is an $R$-diagonal operator freely independent from $a$ and
$\vert T\vert$ has the same distribution as $\sigma$. The assumptions can be
removed if $A$ is Hermitian or unitary. By putting $A= 0$, our result removes a
regularity assumption in the single ring theorem by Guionnet, Krishnapur and
Zeitouni. We also prove a local convergence on optimal scale, extending the
local single ring theorem of Bao, Erd\H{o}s and Schnelli.
