Toward an integrative model of talker normalization

ÂSuccessful speech perception requires accurate mapping of speech signals to linguistic categories despite talker variation in signals. Although factors like intrinsic and context cues have been identified, a full understanding of talker normalization remains to be achieved. In particular, it is important to examine the cocontribution of intrinsic, extrinsic and other cues in an integrative way. In Experiment 1, we examined the effect of intrinsic cues and typicality of a talker's F0 range relative to population F0 range on word identification in isolation. In Experiment 2, we compared the effects of 4 contexts to identify those that consistently facilitate talker normalization. We found that without contexts, word identification accuracy was low and variable depending on talker typicality. Contexts improved performance across all talkers regardless of typicality. But only meaningless and meaningful speech contexts with cues to a talker's acoustic-phonological space showed consistent effects. We proposed a new model, integrating talker typicality, talker familiarity, and context. Whereas speech signals from familiar or typical talkers may be accurately identified standing alone, a context with cues to a talker's acoustic-phonological space is necessary in the case of unfamiliar and atypical talkers. It is thus the first model that integrates memory and context effects.