Many robots use their voice to communicate with people in spoken language but the voices commonly used for robots are often optimized for transactional interactions, rather than social ones. This can limit their ability to create engaging and natural interactions. To address this issue, we designed a spontaneous text-to-speech tool and used it to author natural and spontaneous robot speech. A crowdsourcing evaluation methodology is proposed to compare this type of speech to natural speech and state-of-the-art text-to-speech technology, both in disembodied and embodied form. We created speech samples in a naturalistic setting of people playing tabletop games and conducted a user study evaluating Naturalness, Intelligibility, Social Impression, Prosody, and Perceived Intelligence. The speech samples were chosen to represent three contexts that are common in tabletopgames and the contexts were introduced to the participants that evaluated the speech samples. The study results show that the proposed evaluation methodology allowed for a robust analysis that successfully compared the different conditions. Moreover, the spontaneous voice met our target design goal of being perceived as more natural than a leading commercial text-to-speech.