Do face masks introduce bias in speech technologies? The case of automated scoring of speaking proficiency

The COVID-19 pandemic has led to a dramatic increase in the use of face masks worldwide. Face coverings can affect both acoustic properties of the signal as well as speech patterns and have unintended effects if the person wearing the mask attempts to use speech processing technologies. In this paper we explore the impact of wearing face masks on the automated assessment of English language proficiency. We use a dataset from a large-scale speaking test for which test-takers were required to wear face masks during the test administration, and we compare it to a matched control sample of test-takers who took the same test before the mask requirements were put in place. We find that the two samples differ across a range of acoustic measures and also show a small but significant difference in speech patterns. However, these differences do not lead to differences in human or automated scores of English language proficiency. Several measures of bias showed no differences in scores between the two groups

Applying rhythm metrics to non-native spontaneous speech

This study investigates a variety of rhythm metrics on two corpora of non-native spontaneous speech and compares the nonnative distributions to values from a corpus of native speech. Several of the metrics are shown to differentiate well between native and non-native speakers and to also have moderate correlations with English proficiency scores that were assigned to the non-native speech. The metric that had the highest correlation with English proficiency scores (apart from speaking rate) was rPVIsyl (the raw Pairwise Variability Index for syllables), with r = −0.43. Index Terms: Rhythm metrics, non-native speech, fluency 1

An activation domain of plasmid R1 TraI protein delineates stages of gene transfer initiation

Bacterial conjugation is a form of type IV secretion that transports protein and DNA to recipient cells. Specific bacteriophage exploit the conjugative pili and cell envelope spanning protein machinery of these systems to invade bacterial cells. Infection by phage R17 requires F-like pili and coupling protein TraD, which gates the cytoplasmic entrance of the secretion channel. Here we investigate the role of TraD in R17 nucleoprotein uptake and find parallels to secretion mechanisms. The relaxosome of IncFII plasmid R1 is required. A ternary complex of plasmid oriT, TraD and a novel activation domain within the N-terminal 992 residues of TraI contributes a key mechanism involving relaxase-associated properties of TraI, protein interaction and the TraD ATPase. Helicase-associated activities of TraI are dispensable. These findings distinguish for the first time specific protein domains and complexes that process extracellular signals into distinct activation stages in the type IV initiation pathway. The study also provided insights into the evolutionary interplay of phage and the plasmids they exploit. Related plasmid F adapted to R17 independently of TraI. It follows that selection for phage resistance drives not only variation in TraA pilins but diversifies TraD and its binding partners in a plasmid-specific manner

Fast Generation of Abstracts from General Domain Text Corpora by Extracting Relevant Sentences

This paper describes a system for generating text abstracts which relies on a general, purely statistical principle, i.e., on the notion of "relevance;", as it is defined in terms of the combina- tion of tf*idf weights of words in a senrenee. The systen generates abstracts from newspaper articles by selecting tile "most relevant" sentences and combin- ing them in text order. Since neither domain knowledge nor text-sort-specific heuristics are involved, this system provides maximal generality and flexibility. Also, it is fast and can be efficiently implemented for both on-line and off-line purposes. An experiment shows that recall and precision for the extracted sen- tences (taking the sentences extracteel by hmnan subjects as a baseline) is within the same range as recall/precision when the human subjects are cronpared mnongst each other: this means in fact that the performance of the system is indistinguishable from the performance of a human abstractor. Finally, the system yields significantly better results than a default "lead" algorithm does which chooses just some initial sentences from the text

Automatic summarization of open-domain multiparty dialogues in diverse genres

Automatic summarization of open-domain spoken dialogues is a relatively new research area. This article introduces the task and the challenges involved and motivates and presents an approach for obtaining automatic-extract summaries for human transcripts of multiparty dialogues of four different genres, without any restriction on domain. We address the following issues, which are intrinsic to spoken-dialogue summarization and typically can be ignored when summarizing written text such as news wire data: (1) detection and removal of speech disfluencies; (2) detection and insertion of sentence boundaries; and (3) detection and linking of cross-speaker information units (question-answer pairs). A system evaluation is performed using a corpus of 23 dialogue excerpts with an average duration of about 10 minutes, comprising 80 topical segments and about 47,000 words total. The corpus was manually annotated for relevant text spans by six human annotators. The global evaluation shows that for the two more informal genres, our summarization system using dialoguespecific components significantly outperforms two baselines: (1) a maximum-marginal-relevance ranking algorithm using TF*IDF term weighting, and (2) a LEAD baseline that extracts the first n words from a text. 1

Automatic Construction of Frame Representations for Spontaneous Speech in Unrestricted Domains

This paper presents a system which automatically generates shallow semantic frame structures for conversational speech in unrestricted domains. We argue that such shallow semantic representations can indeed be generated with a minimum amount of linguistic knowledge engineering and without having to explicitly construct a semantic knowledge base. The system is designed to be robust to deal with the problems of speech dysfluencies, ungrammaticalities, and imperfect speech recognition. Initial results on speech transcripts are promising in that correct mappings could be identified in 21% of the clauses of a test set (resp. 44% of this test set where ungrammatical or verb-less clauses were removed). 1 Introduction In syntactic and semantic analysis of spontaneous speech, little research has been done with regard to dealing with language in unrestricted domains. There are several reasons why so far an in-depth analysis of this type of language data has been considered prohibitively hard: ..