Segmentation Cues in Conversational Speech: Robust Semantics and Fragile Phonotactics

Abstract

Multiple cues influence listeners’ segmentation of connected speech into words, but most previous studies have used stimuli elicited in careful readings rather than natural conversation. Discerning word boundaries in conversational speech may differ from the laboratory setting. In particular, a speaker’s articulatory effort – hyperarticulation vs. hypoarticulation (H&H) – may vary according to communicative demands, suggesting a compensatory relationship whereby acoustic-phonetic cues are attenuated when other information sources strongly guide segmentation. We examined how listeners’ interpretation of segmentation cues is affected by speech style (spontaneous conversation vs. read), using cross-modal identity priming. To elicit spontaneous stimuli, we used a map task in which speakers discussed routes around stylized landmarks. These landmarks were two-word phrases in which the strength of potential segmentation cues – semantic likelihood and cross-boundary diphone phonotactics – was systematically varied. Landmark-carrying utterances were transcribed and later re-recorded as read speech. Independent of speech style, we found an interaction between cue valence (favorable/unfavorable) and cue type (phonotactics/semantics). Thus, there was an effect of semantic plausibility, but no effect of cross-boundary phonotactics, indicating that the importance of phonotactic segmentation may have been overstated in studies where lexical information was artificially suppressed. These patterns were unaffected by whether the stimuli were elicited in a spontaneous or read context, even though the difference in speech styles was evident in a main effect. Durational analyses suggested speaker-driven cue trade-offs congruent with an H&H account, but these modulations did not impact on listener behavior. We conclude that previous research exploiting read speech is reliable in indicating the primacy of lexically based cues in the segmentation of natural conversational speech.

Transformation from auditory to linguistic representations across auditory cortex is rapid and attention dependent for continuous speech

“…A similar word-onset electroencephalographic (EEG) response [19] emerged only after listeners learned to segment an artificial language into words [18], suggesting that it is not a response to local acoustic properties alone. A response tightly locked to word onset suggests that whichever cues listeners use to detect word boundaries [46–48], boundaries seem to be generally detected as they occur, rather than after incorporating cues occurring subsequent to word onset.…”

A relationship between processing speech in noise and dysarthric speech

“…Lexical cues refer to higherlevel information arising from knowledge of individual words and syntactic, semantic, and pragmatic relations between words. Segmental cues include phonemic, phonotactic, and co-articulatory features, and suprasegmental cues refer to speech rhythm properties, including metrical stress (see White et al, 2012, for more detail of the segmentation cue categories).…”

Speech Rate and Turn-Transition Pause Duration in Dutch and English Spontaneous Question-Answer Sequences

“…Question-answer sequences were extracted from corpora of spontaneous conversations in Dutch (Van Son et al 2008) and English (White et al 2012). As described below, the corpora were both comprised of free conversations between people who were either friends or colleagues in university environments.…”

“…The English dataset was sampled from a corpus of eight dyadic lab-based conversations (White et al 2012, which also includes read sentences and map task speech, not analysed here). Each conversational recording was between 16 and 22 min long.…”