fluencj

Fluencj is a proposed measure of linguistic and interactive fluency, intended to reflect the ease and naturalness of speech and dialogue across languages and modalities. It combines aspects of lexical diversity, syntactic cohesion, prosodic timing, and contextual adaptability into a single score.

Key components include: speech rate stability, pause distribution, lexical variety, syntactic alignment with discourse context, error rate, and discourse coherence across turns. It also considers modality differences when evaluating spoken versus written output and cross-language transfer.

Measurement typically reports fluencj on a 0 to 1 scale or 0 to 100, derived from automated analyses of audio and text along with human judgments. Data sources include conversational transcripts, dialogue datasets, and interactive tasks with chatbots or voice assistants. Validation requires cross-linguistic studies and benchmark datasets.

Applications include evaluating language learning tools, informing speech synthesis and recognition systems, benchmarking AI conversational agents, and studying second-language acquisition. It is used alongside traditional fluency and coherence measures to provide a multifaceted view of communicative competence.

Limitations include a lack of universal standard, sensitivity to sampling and task design, cross-language comparability challenges, and potential bias in human judgments. As a developing concept, fluencj remains a topic of ongoing methodological debate and refinement.