Suchergebnisse

The utility of technical materials is influenced to a marked extent by their reading level or readability. This article describes the derivation and validation of the Automated Readability Index (ARI) for use with technical materials. The method allows for the easy, automatic collection of data as narrative material is typed on a slightly modified electric typewriter. Data collected includes word length (a measure of word difficulty) and sentence length (a measure of sentence difficulty). Appropriate weightings of these factors in a multiple regression equation result in an index of reading difficulty. Uses of the index for evaluating and controlling the readability of large quantities of technical material are described.

The Automated Readability Index (ARI) is a measure of reading difficulty level of narrative material. In computing the ARI a modified electric typewriter is used to compute average word and sentence length. One hundred and ten Army National Guard personnel read passages of technical material at three levels of reading difficulty, 8th, 12th, and 16th grades, as measured by the ARI. Tested reading comprehension was lower for material written at the highest level of difficulty (16th grade), and was significantly correlated with scores previously obtained on the Armed Forces Qualification Test, which can be considered a measure of general reading ability.

Past research has demonstrated that there are cognitive processing costs associated with comprehension of speech generated by text-to-speech synthesizers, relative to comprehension of natural speech. This finding has important performance implications for the many applications that use such systems. The purpose of this study was to ascertain whether certain characteristics of synthetic speech slow on-line, real-time cognitive processing. Whereas past research has focused on the phonemic acoustic structure of synthetic speech, we manipulated prosodic, syntactic, and semantic cues in a task requiring participants to recall sentences spoken either by a human or by one of two speech synthesizers. The findings were interpreted to suggest that inappropriate prosodic modeling in synthetic speech was the major source of a performance differential between natural and synthetic speech. Prosodic cues, along with others, guide the parsing of speech and provide redundancy. When these cues are absent or inaccurate, the additional burden placed on working memory may exceed its capacity, particularly in time-limited, demanding tasks. Actual or potential applications of this research include improvement of text-to-speech output systems in warning systems, feedback devices in aerospace vehicles, educational and training modules, aids for the handicapped, consumer products, and technologies designed to increase the functional independence of older adults.