A’ingae (also known as Cofán or Kofán) is a language isolate spoken by approximately 1,500 people in 13 communities in Ecuador and Colombia (Figure 1). Traditionally, the A’i (speakers of A’ingae) lived in the Andean foothills, but over the past century they have migrated down the Aguarico and San Miguel rivers, founding communities at Dureno and Zábalo, where the language is most widely spoken. This migration was spurred in large part by extensive oil contamination; an issue of great concern to the Foundation for the Survival of the Cofán People (FSC) and the community at large (Cepek 2012: 103; 2018: 1–15). Another concern in the Cofán community is the decreasing use of A’ingae, which, according to Ethnologue (Simons & Fennig 2017), is ‘endangered’ in Ecuador and ‘severely endangered’ in Colombia as a growing emphasis on Spanish disincentivizes the younger generation from learning A’ingae.

Linguistic convergence is the phenomenon in which interlocutors' speech characteristics become more similar to each other's. One of the methods frequently used to measure convergence is the difference-indifference (DID) approach, comparing change in absolute distance between a subject and an interlocutor or model talker. We show that this approach is not a reliable measure of convergence when the starting values of the subject and the interlocutor or model talker are close, which can result in the measurement of apparent divergence, while extreme starting points can result in overestimation of convergence. These biases are of particular concern in studies that look for individual differences in convergence. We propose an alternative approach, linear combination, which does not have the same biases, and demonstrate the advantages of this method using data from convergence studies of four linguistic characteristics and simulated data.

Because of restrictions on in-person research due to COVID-19, researchers are now relying on remotely recorded data to a much greater extent than in the past. Given the change in methodology, it is important to know how remote recording might affect acoustic measurements, either because of different recording devices used by participants and consultants or because of the software used to make recordings. This study investigates audio signal fidelity across different inperson recording equipment and remote recording software when compared to solid-state digital audio. We show that equipment choice and software can have a large effect on acoustic measurements, including those of frequency, duration, and noise. The issues do not just reflect decreased reliability; some measurements are systematically shifted in particular recording conditions. These results show the importance of carefully considering and documenting equipment choices, particularly for crosslinguistic or cross-speaker comparisons. We close with a framework for researchers to use in deciding what types of recording may be most appropriate.*

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