Evaluation and Inter-Comparison of Oxygen-Based OC-EC Separation Methods for Radiocarbon Analysis of Ambient Aerosol Particle Samples

Radiocarbon analysis is a widely-used tool for source apportionment of aerosol particles. One of the big challenges of this method, addressed in this work, is to isolate elemental carbon (EC) for 14C analysis. In the first part of the study, we validate a two-step method (2stepCIO) to separate total carbon (TC) into organic carbon (OC) and EC against the EUSAAR_2 thermal-optical method regarding the recovered carbon concentrations. The 2stepCIO method is based on the combustion of OC in pure oxygen at two different temperature steps to isolate EC. It is normally used with a custom-built aerosol combustion system (ACS), but in this project, it was also implemented as a thermal protocol on a Sunset OC-EC analyzer. Results for the recovered EC mass concentration showed poor agreement between the 2stepCIO method on the ACS system and on the Sunset analyzer. This indicates that the EC recovery is sensitive not only to the temperature steps, but also to instrument-specific parameters, such as heating rates. We also found that the EUSAAR_2 protocol itself can underestimate the EC concentration on untreated samples compared to water-extracted samples. This is especially so for highly loaded filters, which are typical for 14C analysis. For untreated samples, the EC concentration on long-term filter samples (two to five days sampling time) was 20–45% lower than the sum of EC found on the corresponding 24-h filter samples. For water-extracted filter samples, there was no significant difference between long-term and the sum of daily filter samples. In the second part of this study, the 14C was measured on EC isolated by the 2stepCIO method and compared to methods from two other laboratories. The different methods agree well within their uncertainty estimates

On-line experimental methods to evaluate text-to-speech (TTS) synthesis : effects of voice gender and signal quality on intelligibility, naturalness and preference

Three experiments are reported that use new experimental methods for the evaluation of text-to-speech (TTS) synthesis from the user's perspective. Experiment 1, using sentence stimuli, and Experiment 2, using discrete “call centre” word stimuli, investigated the effect of voice gender and signal quality on the intelligibility of three concatenative TTS synthesis systems. Accuracy and search time were recorded as on-line, implicit indices of intelligibility during phoneme detection tasks. It was found that both voice gender and noise affect intelligibility. Results also indicate interactions of voice gender, signal quality, and TTS synthesis system on accuracy and search time. In Experiment 3 the method of paired comparisons was used to yield ranks of naturalness and preference. As hypothesized, preference and naturalness ranks were influenced by TTS system, signal quality and voice, in isolation and in combination. The pattern of results across the four dependent variables – accuracy, search time, naturalness, preference – was consistent. Natural speech surpassed synthetic speech, and TTS system C elicited relatively high scores across all measures. Intelligibility, judged naturalness and preference are modulated by several factors and there is a need to tailor systems to particular commercial applications and environmental conditions

Report on the Third ESCA TTS workshop evaluation procedure.

This paper provides a description and rationale for the EvaluationProcedure taking place at the Workshop. The procedure has threegoals. First, setting a precedent of providing conference participantswith a more candid and thorough picture of the quality of current TTS systems than is usually available in the form of prepared conference demonstrations. Second, providing results that will be informative for TTS systems developers. Third, stimulating a discussion and contributing to a consensus building process on text-to-speech synthesis evaluation