The application discloses a foreign language teaching effect evaluation method and
system based on
artificial intelligence, and the content comprises data collection, speech
feature extraction, multi-
modal fusion evaluation modeling and teaching effect evaluation. The application relates to the technical field of intelligent evaluation of teaching effect, and particularly discloses a foreign language teaching effect evaluation method and
system based on
artificial intelligence. The scheme constructs a pronunciation articulation
composite index through
formant difference analysis, calculates acoustic semantic
coupling degree, and evaluates phoneme transfer stability, so that the articulation, accuracy and coherence of speech can be accurately quantified in a multi-
noise environment. The scheme introduces
modal attention, realizes bidirectional interaction of multi-
modal information by using full-
interconnection cross-modal cross-attention, and innovatively introduces a complementary gating mechanism to adaptively adjust the modal fusion ratio. Local scores are generated by combining a lightweight network, meta-decision network dynamically allocates weights, and finally, end-to-end optimization is realized by using a differentiable weighting strategy, so that the teaching effect evaluation of
fineness and accuracy is realized.