Ability to render natural prosody with nuanced intonation and stress is correct.

Neural speech models are trained end to end on large amounts of natural speech and they model timing, intonation, and stress patterns so output sounds more human and expressive. This allows them to render natural prosody and nuanced intonation in ways older synthesis techniques could not reliably reproduce.

Older synthesis approaches tended to be concatenative or parametric and they produced flatter, more robotic speech with limited control over subtle intonation and stress. Neural models overcome those limitations by learning prosodic patterns directly from data.

Cloud Text-to-Speech is the name of a service that can deliver neural voices but the service name is not an extra capability. The question asks about what neural speech models can do so a product name is not the correct choice.

Broader selection of female voice tones is incorrect because the improvement from neural models is about expressiveness and natural prosody across voices and styles rather than simply offering more female tone options.

Voices that are entirely gender neutral is incorrect because neural models can produce gender ambiguous voices but their defining extra capability is natural prosody and nuanced intonation and not a guarantee of complete gender neutrality.

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