Despite recent advancements in automated speech recognition (ASR) technologies, reports of unequal performance across speakers of different demographic groups abound. At the same time, the focus on performance metrics such as the Word Error Rate (WER) in prior studies limit the specificity and scope of recommendations that can be offered for system engineering to overcome these challenges. The current
study bridges this gap by investigating the performance of Otter’s automatic captioning system on native and non-native English speakers of different language background through a linguistic analysis of segment-level errors. By examining language-specific error profiles for vowels and consonants motivated by linguistic theory, we find that certain categories of errors can be predicted from the phonological structure of a speaker’s native language.

Language-specific Effects on Automatic Speech Recognition Errors for World Englishes

Word learning is characterized by a bias for mapping meanings at the “basic”-level such as apple, as opposed to a subordinate-level like red apple (Markman, 1990). The fact that learners nevertheless acquire subordinate nouns has been attributed to properties of the referential world that co-occur with the word (e.g., Xu and Tanenbaum, 2007b; Spencer et al., 2011). However, learners may also make inferences about the informativity of labels as intentional linguistic acts. We investigated whether learners exploit information about semantic contrast to generalize word meanings beyond the basic level. Experiment 1 found that the introduction of a labelled alternative at the subordinate level (green apple) eliminated the basic-level bias. Experiment 2 found that the presence of the alternative exemplar without a label merely suppressed the bias. We propose that the acquisition of subordinate-level meanings is facilitated by expectations of informativity which allow learners to enter the relevant alternatives into consideration.

The acquisition of subordinate nouns as pragmatic inference: Semantic alternatives modulate subordinate meanings

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OS6 - Dialogue and Conversational Interaction & Speech recognition and synthesis and spoken language understanding

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Language-specific Effects on Automatic Speech Recognition Errors for World Englishes

The acquisition of subordinate nouns as pragmatic inference: Semantic alternatives modulate subordinate meanings

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