All it takes is one bad telephone connection, in which one’s own voice echoes in the earpiece

with a slight delay, to be convinced that input to the auditory system affects speech production. The disruptive effect of delayed auditory feedback is well established (Stuart et al., 2002 and Yates, click here 1963) but is just one source of evidence for the acoustic influence on speech output. Adult-onset deafness is another: individuals who become deaf after becoming proficient with a language nonetheless suffer speech articulation declines as a result of the lack of auditory feedback, which is critical to maintain phonetic precision over the long term (Waldstein, 1990). Other forms of altered auditory feedback, such as digitally shifting the voice pitch or the frequency of a speech formant (frequency band), has been shown experimentally to lead to automatic compensatory see more adjustments on the part of the speaker within approximately 100 ms (Burnett et al., 1998 and Purcell and Munhall, 2006).

At a higher level of analysis, research on speech error patterns at the phonetic, lexical, and syntactic levels shows that the perceptual system plays a critical role in self-monitoring of speech output (both overt and inner speech) and that this self-perception provides feedback signals that guide repair processes in speech production (Levelt, 1983 and Levelt, 1989). It is not just acoustic perception of one’s own voice that affects speech production. The common anecdotal observation that speakers can pick up accents as a result of spending extended periods in a different linguistic community, so-called “gestural drift,” Mephenoxalone has been established quantitatively

(Sancier and Fowler, 1997). In the laboratory setting, it has been shown that phonetic patterns such voice pitch and vowel features introduced into “ambient speech” of the experimental setting is unintentionally (i.e., automatically) reproduced in the subjects’ speech (Cooper and Lauritsen, 1974, Delvaux and Soquet, 2007 and Kappes et al., 2009). This body of work demonstrates that perception of others’ speech patterns influence the listener’s speech patterns. Nowhere is this more evident than in development, where the acoustic input to a prelingual child determines the speech patterns s/he acquires. Thus, it is uncontroversial that the auditory system plays an important role in speech production; without it, speech cannot be learned or maintained with normal precision. Computationally, auditory-motor interaction in the context of speech production has been characterized in terms of feedback control models. Such models can trace their lineage back to Fairbanks (Fairbanks, 1954), who adapted Wiener’s (Wiener, 1948) feedback control theory to speech motor control. Fairbanks proposed that speech goals were represented in terms of a sequence of desired sensory outcomes and that the articulators were driven to produce speech by a system that minimized the error between desired and actual sensory feedback.