Technology has paved the way for new modalities in language learning, teaching, and assessment. However, there is still a great deal of work to be done to develop such tools for oral communication, specifically tools that address suprasegmental features in pronunciation instruction. Therefore, this critical literature review examines how…

Purpose: This study builds a new system for automatically assessing learners' speech elicited from an oral discourse completion task (DCT), and evaluates the prediction capability of the system with a view to better understanding factors deemed influential in predicting speaking proficiency scores and the pedagogical implications of the system.…

The present study investigated the speaking module of TOEFL iBT with an emphasis on the dichotomy of independent and integrated tasks. The potential differences between the two speaking conditions were intended to be explored based on the oral performance elicited from a group of Iranian test takers. To collect the required data, a simulated…

Research examining test taker fluency in simulated and face-to-face oral proficiency interview performances has primarily focused on quantitative spoken utterance fluency data alone, with further qualitative investigation of test taker processing fluency's effect being neglected. This study compared four test takers' spoken utterance and…

Recent technology advancements have increased the prospects for automated spoken language technology to provide feedback on speaking performance. In this study we examined user perceptions of using an automated feedback system for preparing for the TOEFL iBT® test. Test takers and language teachers evaluated three types of machine-generated…

Through Many-Facet Rasch analysis, this study explores the rating differences between 1 computer automatic rater and 5 expert teacher raters on scoring 119 students in a computerized English listening-speaking test. Results indicate that both automatic and the teacher raters demonstrate good inter-rater reliability, though the automatic rater…

While fluency in second language speaking can be a challenging construct to measure, it is important to identify the discourse features that contribute to it. This small-scale classroom research project examined the effect of formulaic language sequences on fluency as measured by computer-based speaking tasks of young English learners. Thirty-six…

The ultimate aim of our research project was to use the Google Web Speech API to automate scoring of elicited imitation (EI) tests. However, in order to achieve this goal, we had to take a number of preparatory steps. We needed to assess how accurate this speech recognition tool is in recognizing native speakers' production of the test items; we…

Scores assigned by trained raters and by an automated scoring system (SpeechRater[TM]) on the speaking section of the TOEFL iBT[TM] were validated against a communicative competence criterion. Specifically, a sample of 555 undergraduate students listened to speech samples from 184 examinees who took the Test of English as a Foreign Language…

This study examined the use of automatic speech recognition (ASR) scored elicited oral response (EOR) tests to assess the speaking ability of English language learners. It also examined the relationship between ASR-scored EOR and other language proficiency measures and the ability of the ASR to rate speakers without bias to gender or native…

A renewed focus on foreign language (FL) learning and speech for communication has resulted in computer-assisted language learning (CALL) software developed with Automatic Speech Recognition (ASR). ASR features for FL pronunciation (Lafford, 2004) are functional components of CALL designs used for FL teaching and learning. The ASR features…