摘要
由一位新闻记者兼机器人与机器学习的工作人员新闻编辑每日新闻-机器学习-智能系统的最新研究结果已经发表。根据NewsRx记者的《来自中国湖南的新闻》报道，研究表明：“基于conformer的模型在视听语音识别中已经被证明是非常有效的，它整合了听觉和视觉输入，显著提高了语音识别的准确性。然而，广泛使用的基于conformer模型的SoftMax注意机制遇到了可扩展性问题，其空间和节奏复杂性随着序列长度的平方增长。”
Abstract
By a News Reporter-Staff News Editor at Robotics & Machine Learning Daily News Daily News – Current study results on Machine Learn ing - Intelligent Systems have been published. According to news originating fro m Hunan, People’s Republic of China, by NewsRx correspondents, research stated, “Conformer-based models have proven highly effective in Audio-visual Speech Reco gnition, integrating auditory and visual inputs to significantly enhance speech recognition accuracy. However, the widely utilized softmax attention mechanism w ithin conformer models encounters scalability issues, with its spatial and tempo ral complexity escalating quadratically with sequence length.”
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