论文标题
关于风格在与神经模型分析演讲中的作用
On the Role of Style in Parsing Speech with Neural Models
论文作者
论文摘要
书面文本和对话演讲的差异是很大的。以前接受过树岸文本培训的解析器在自发的演讲方面取得了非常差的结果。对于口语，风格的不匹配也扩展到韵律线索，尽管它的理解程度不高。本文在神经语言处理的最新进展中重新检查了在解析语音中使用书面文本。我们表明，神经方法有助于使用书面文本改善自发语音的解析，而韵律进一步改善了这种最先进的结果。此外，我们发现读与自发不匹配的不对称降解，自发语音对于训练解析器的通常有用。
The differences in written text and conversational speech are substantial; previous parsers trained on treebanked text have given very poor results on spontaneous speech. For spoken language, the mismatch in style also extends to prosodic cues, though it is less well understood. This paper re-examines the use of written text in parsing speech in the context of recent advances in neural language processing. We show that neural approaches facilitate using written text to improve parsing of spontaneous speech, and that prosody further improves over this state-of-the-art result. Further, we find an asymmetric degradation from read vs. spontaneous mismatch, with spontaneous speech more generally useful for training parsers.
