In this study, we investigate the capability of phonological fea-tures (PFs) in capturing the fine variational structure in speech which arise due to natural phenomenon such as coarticulation. The PF theory provides a framework in which a far more richer description of speech is possible when compared to traditional phonetic representations. However, current approaches toward training PF detectors do not explicitly expose the statistical system to patterns of coarticulation. The analysis presented here shows that despite this handicap, our PF system still learns to capture these variants in speech. In fact, it is noted that the use of phone-based transcriptions to judge the performance of PF systems erroneously labels such variants as errors. Our result show that a large proportion of speech frames that are deemed errors by phone-transcriptions are actually coarticulated as is evidenced by their phonetic context. These findings offer important knowledge in analyzing and improving the utility of PFs in ASR (automatic speech recognition) for spontaneous conversational speech.
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