Automatic Pronunciation Assessment -- A Review

Pronunciation assessment and its application in computer-aided pronunciation training (CAPT) have seen impressive progress in recent years. With the rapid growth in language processing and deep learning over the past few years, there is a need for an updated review. In this paper, we review methods employed in pronunciation assessment for both phonemic and prosodic. We categorize the main challenges observed in prominent research trends, and highlight existing limitations, and available resources. This is followed by a discussion of the remaining challenges and possible directions for future work.Comment: 9 pages, accepted to EMNLP Finding

Analyzing Prosody with Legendre Polynomial Coefficients

This investigation demonstrates the effectiveness of Legendre polynomial coefficients representing prosodic contours within the context of two different tasks: nativeness classification and sarcasm detection. By making use of accurate representations of prosodic contours to answer fundamental linguistic questions, we contribute significantly to the body of research focused on analyzing prosody in linguistics as well as modeling prosody for machine learning tasks. Using Legendre polynomial coefficient representations of prosodic contours, we answer prosodic questions about differences in prosody between native English speakers and non-native English speakers whose first language is Mandarin. We also learn more about prosodic qualities of sarcastic speech. We additionally perform machine learning classification for both tasks, (achieving an accuracy of 72.3% for nativeness classification, and achieving 81.57% for sarcasm detection). We recommend that linguists looking to analyze prosodic contours make use of Legendre polynomial coefficients modeling; the accuracy and quality of the resulting prosodic contour representations makes them highly interpretable for linguistic analysis

Negative vaccine voices in Swedish social media

Vaccinations are one of the most significant interventions to public health, but vaccine hesitancy creates concerns for a portion of the population in many countries, including Sweden. Since discussions on vaccine hesitancy are often taken on social networking sites, data from Swedish social media are used to study and quantify the sentiment among the discussants on the vaccination-or-not topic during phases of the COVID-19 pandemic. Out of all the posts analyzed a majority showed a stronger negative sentiment, prevailing throughout the whole of the examined period, with some spikes or jumps due to the occurrence of certain vaccine-related events distinguishable in the results. Sentiment analysis can be a valuable tool to track public opinions regarding the use, efficacy, safety, and importance of vaccination

Directions for the future of technology in pronunciation research and teaching

This paper reports on the role of technology in state-of-the-art pronunciation research and instruction, and makes concrete suggestions for future developments. The point of departure for this contribution is that the goal of second language (L2) pronunciation research and teaching should be enhanced comprehensibility and intelligibility as opposed to native-likeness. Three main areas are covered here. We begin with a presentation of advanced uses of pronunciation technology in research with a special focus on the expertise required to carry out even small-scale investigations. Next, we discuss the nature of data in pronunciation research, pointing to ways in which future work can build on advances in corpus research and crowdsourcing. Finally, we consider how these insights pave the way for researchers and developers working to create research-informed, computer-assisted pronunciation teaching resources. We conclude with predictions for future developments

Neutral Tone in Mandarin: Representation and Interaction with Utterance-level Prosody

In Standard Mandarin, there are syllables that do not carry any of the four citation tones (T1: High-level tone, T2: Mid-rising tone, T3: Low-convex tone and T4: High-falling tone), and they are said to have a neutral tone (NT). These syllables are usually shorter, lighter, prosodically grouped with the preceding CT-bearing syllables. These characteristics of NT have led to a prevailing view that it has no underlying phonological specification. However, research has focused more on how the surface pitch variations of NT are realized rather than the underlying representation of NT. In contrast, morphological, sociolinguistic and diachronic work on NT has suggested that NT may not be a homogeneous entity. In this thesis, I provide acoustic and psycholinguistic evidence that there are two types of NT, Intrinsic NT and Derived NT. Intrinsic NT refers to morphemes that were lexicalized as tone-deleted, unstressed syllables even before the formation of the four CTs of modern Mandarin. Derived NT refers to morphemes derived from the CTs via stress-related tone-deletion. In Part A, the phonological representation of Intrinsic and Derived NT is explored through two production and two processing experiments. The results show that Intrinsic NT is likely to have an underspecified tonal target while Derived NTs are underlyingly CTs. In addition, both subtypes of NT are metrically light, unlike heavy CTs. Part B explores the interaction between NTs and utterance-level prosody in production and perception experiments. NT-bearing syllables have lengthening patterns under focus similar to CT-bearing syllables, in contrast to the realization of unstressed syllables in English. In perception, the identification of intonation (Statement vs. Question) on Intrinsic NT was similar to Derived NT. When compared to CTs, the NTs elicit less bias towards question than T4, and higher accuracy than T2, which may result from their simpler surface representations.CHINA Scholarship COUNCIL (CSC) and Cambridge Trus