This work is dealing with a case of L1-L2 interference in language learning. The Germans learning French as a second language frequently produce unvoiced fricatives in word-final position instead of the expected voiced fricatives. We investigated the production of French fricatives for 16 non-native (8 beginner-and 8 advanced-learners) and 8 native speakers, and designed auditory feedback to help them realize the right voicing feature. The productions of all speakers were categorized either as voiced or unvoiced by experts. The same fricatives were also evaluated by non-experts in a perception experiment targeting VCs. We compare the ratings by experts and non-experts with the feature-based analysis. The ratio of locally unvoiced frames in the consonantal segment and also the ratio between consonantal duration and V1 duration were measured. The acoustic cues of neighboring sounds and pitch-based features play a significant role in the voicing judgment. As expected, we found that beginners face more difficulties to produce voiced fricatives than advanced learners. Also, the production becomes easier for the learners, especially for the beginners, if they practice repetition after a native speaker. We use these findings to design and develop feedback via speech analysis/synthesis technique TD-PSOLA using the learner's own voice.

We are interested in the problem of discourse parsing of textual documents. We present a novel end-to-end discourse parser that, given a plain text document in input, identifies the discourse relations in the text, assigns them a semantic label and detects discourse arguments spans. The parsing architecture is based on a cascade of decisions supported by Conditional Random Fields (CRF). We train and evaluate three different parsers using the PDTB corpus. The three system versions are compared to evaluate their robustness with respect to deep/shallow and automatically extracted syntactic features.

Background Quantitative data reports are widely produced to inform health policy decisions. Policymakers are expected to critically assess provided information in order to incorporate the best available evidence into the decision-making process. Many other factors are known to influence this process, but little is known about how quantitative data reports are actually read. We explored the reading behavior of (future) health policy decision-makers, using innovative methods. Methods We conducted a computer-assisted laboratory study, involving starting and advanced students in medicine and health sciences, and professionals as participants. They read a quantitative data report to inform a decision on the use of resources for long-term care in dementia in a hypothetical decision scenario. Data were collected through eye-tracking, questionnaires, and a brief interview. Eye-tracking data were used to generate ‘heatmaps’ and five measures of reading behavior. The questionnaires provided participants’ perceptions of understandability and helpfulness as well as individual characteristics. Interviews documented reasons for attention to specific report sections. The quantitative analysis was largely descriptive, complemented by Pearson correlations. Interviews were analyzed by qualitative content analysis. Results In total, 46 individuals participated [students (85%), professionals (15%)]. Eye-tracking observations showed that the participants spent equal time and attention for most parts of the presented report, but were less focused when reading the methods section. The qualitative content analysis identified 29 reasons for attention to a report section related to four topics. Eye-tracking measures were largely unrelated to participants’ perceptions of understandability and helpfulness of the report. Conclusions Eye-tracking data added information on reading behaviors that were not captured by questionnaires or interviews with health decision-makers.

Despite its murderous act, carbon monoxide (CO) is found to be a very crucial small gaseous messenger molecule in dictating prime biological and physiological processes. Determination of endogenous or exhaled CO levels can throw significant light on smoking status and can be used as a breath biomarker of inflammatory diseases. Therefore, fluorescence imaging of CO in biofluids will empower one with the minute details of various disease states that involve CO. Unfortunately, such efficient fluorescent probes are less in number and also associated with tedious protocols. This enticed our attention and inspired us to look upon developing perceptive imaging agents for CO in a living system. In this report, a resorufin-based "turn-on" orange emissive molecular probe has been successfully utilized to detect CO in an aqueous system. The mono protection of a resorufin unit with an allyl chloroformate furnished a weakly fluorescent small molecular probe P1. Further, the P1+Pd 2+ ensemble has been successfully developed in situ using PdCl 2 (as Pd 2+ ) and utilized as a light-up signaling mechanism tool for the sensing of CO at the nanomolar level (62 nM) through deprotection mechanism. The probe selectively detects CO without any interference from other anions, gasotransmitters and fatty acids. The present integrated probe P1+Pd 2+ system has been found to be highly sensitive to detect CO in cellular systems as well.

Conversational interaction is a dynamic activity in which participants engage in the construction of meaning and in establishing and maintaining social relationships. Lexical and prosodic accommodation have been observed in many studies as contributing importantly to these dimensions of social interaction. However, while previous works have considered accommodation mechanisms at global levels (for whole conversations, halves and thirds of conversations), this work investigates their evolution through repeated analysis at time intervals of increasing granularity to analyze the dynamics of alignment in a spoken language corpus. Results show that the levels of both prosodic and lexical accommodation fluctuate several times over the course of a conversation.