Multidimensional Signals and Analytic Flexibility: Estimating Degrees of Freedom in Human-Speech Analyses

Recent empirical studies have highlighted the large degree of analytic flexibility in data analysis that can lead to substantially different conclusions based on the same data set. Thus, researchers have expressed their concerns that these researcher degrees of freedom might facilitate bias and can lead to claims that do not stand the test of time. Even greater flexibility is to be expected in fields in which the primary data lend themselves to a variety of possible operationalizations. The multidimensional, temporally extended nature of speech constitutes an ideal testing ground for assessing the variability in analytic approaches, which derives not only from aspects of statistical modeling but also from decisions regarding the quantification of the measured behavior. In this study, we gave the same speech-production data set to 46 teams of researchers and asked them to answer the same research question, resulting in substantial variability in reported effect sizes and their interpretation. Using Bayesian meta-analytic tools, we further found little to no evidence that the observed variability can be explained by analysts’ prior beliefs, expertise, or the perceived quality of their analyses. In light of this idiosyncratic variability, we recommend that researchers more transparently share details of their analysis, strengthen the link between theoretical construct and quantitative system, and calibrate their (un)certainty in their conclusions

Non-convergence of pitch and duration: Word-prosody of Garo

Garo is an understudied Sino-Tibetan language spoken in Northeast India. There is currently only an impressionistic description of its word prosody by Burling (2003) which says that it is a stress final language. Recent studies have highlighted problems with impressionistic descriptions of prosody (de Lacy, 2014), and methodological problems with some acoustic studies which do not control for confounds of sentence prominence (Gordon, 2014; Roettger & Gordon, 2017). Edge prominent languages also have added complexity about whether prominence should be analysed as metrical prominence or boundary effect (Jun, 1998; Jun & Fougeron, 2000). Keeping all of these facts in mind, a production study was designed to elicited target words in carrier sentences which controlled for confounds of higher level prosody following Athanasopoulou et al. (2021) and Vogel et al. (2017). Binary logistic regression conducted on the measurements of acoustic properties revealed that F0 is the cue for stress in Garo. I analysed the F0 pattern as an intonational pitch LH* where L associated to the first syllable and H* associates to the final syllable. The cue for stress in Garo is thus more specifically an association of intonational pitch accent. Due to the trisyllabic structure of the target words in this study, the foot structure could not be determined. The cues for stress were not found to be enhanced under focus and they were also found to be unaffected post-focally. The focus particle was found to add an IP boundary at the end of the focused constituent and additionally, it was found to upstep the L of the LH* intonational pitch accent. Therefore, the prosodic focus is present only with the focus particle in Garo. The findings of this study thus confirm that Garo has word stress on the final syllable signaled by F0. What separates Garo from other edge prominent languages is that it has F0 events on every prosodic word making it clear that it has stress. The prosodic expression of focus is also only present with the focus particle which makes it similar to other languages with morphosyntactic ways of expressing focus

The Phonology of Gemination in Garo

Even though gemination is one of the most attested phonological processes crosslinguistically, the amount of literature on it is very modest (Mubarak & Jebur, 2018). This also stands true for Garo (understudied Sino-Tibetan language of India and Bangladesh), where Burling (2003), the sole descriptive work of the language does not describe the process. This stands in the way of answering whether assimilated geminates (McCarthy, 1986) are prevalent in languages, and if so, what universal principles motivate it. This paper examines the gemination process in Garo and explains it in the autosegmental phonology framework (Kenstowicz, 1994; Goldsmith, 1976). This paper finds that gemination is a predictable process triggered by morpheme concatenation. Whenever a morpheme with a coda combines with another that lacks an onset, the coda of the preceding morpheme spreads to the onset of the following morpheme e.g. [t͡ sʰat] “thick” + [-a] “neutral tense” = [t͡ sʰat.ta] “be thick”. These types of geminates are preserved by the geminate integrity constraint (Crystal, 2008) and are immune to the aspiration rule of Garo. There are of course exceptions to this process. These exceptions are however easily explained by onset constraints that apply in the language without exceptions or in other cases by an appeal to an identity rule (Kenstowicz, 1994; Kiparsky, 1982). Considering the process within the broader typology, it appears that the gemination is motivated by the need for onsets in syllables, and that languages can achieve this unmarked structure (Rice, 2007) through phonological processes even though underlying marked syllable configurations exists. See full abstract linked below

Multidimensional signals and analytic flexibility: Estimating degrees of freedom in human speech analyses

Recent empirical studies have highlighted the large degree of analytic flexibility in data analysis which can lead to substantially different conclusions based on the same data set. Thus, researchers have expressed their concerns that these researcher degrees of freedom might facilitate bias and can lead to claims that do not stand the test of time. Even greater flexibility is to be expected in fields in which the primary data lend themselves to a variety of possible operationalizations. The multidimensional, temporally extended nature of speech constitutes an ideal testing ground for assessing the variability in analytic approaches, which derives not only from aspects of statistical modeling, but also from decisions regarding the quantification of the measured behavior. In the present study, we gave the same speech production data set to 46 teams of researchers and asked them to answer the same research question, resulting insubstantial variability in reported effect sizes and their interpretation. Using Bayesian meta-analytic tools, we further find little to no evidence that the observed variability can be explained by analysts’ prior beliefs, expertise or the perceived quality of their analyses. In light of this idiosyncratic variability, we recommend that researchers more transparently share details of their analysis, strengthen the link between theoretical construct and quantitative system and calibrate their (un)certainty in their conclusions