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USING PROXIES FOR OOV KEYWORDS IN THE KEYWORD SEARCH TASK

机译:在关键字搜索任务中使用oov关键字的代理

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摘要

We propose a simple but effective weighted finite state transducer (WFST) based framework for handling out-of-vocabulary (OOV) keywords in a speech search task. State-of-the-art large vocabulary continuous speech recognition (LVCSR) and keyword search (KWS) systems are developed for conversational telephone speech in Tagalog. Word-based and phone-based indexes are created from word lattices, the latter by using the LVCSR system's pronunciation lexicon. Pronunciations of OOV keywords are hypothesized via a standard grapheme-to-phoneme method. In-vocabulary proxies (word or phone sequences) are generated for each OOV keyword using WFST techniques that permit incorporation of a phone confusion matrix. Empirical results when searching for the Babel/NIST evaluation keywords in the Babel 10 hour development-test speech collection show that (i) searching for word proxies in the word index significantly outperforms searching for phonetic representations of OOV words in a phone index, and (ii) while phone confusion information yields minor improvement when searching a phone index, it yields up to 40% improvement in actual term weighted value when searching a word index with word proxies.
机译:我们提出了一种简单但有效的加权有限状态传感器(WFST)基于语音搜索任务中的词汇量(OOV)关键词的框架。最先进的大词汇表连续语音识别(LVCSR)和关键字搜索(KWS)系统是在Tagalog中的会话电话演讲开发的。基于Word的和基于电话的索引是从Word格式创建的,后者使用LVCSR系统的发音词典。 OOV关键字的发音是通过标准的石墨对 - 音素方法假设。使用WFST技术为每个OoV关键字生成词汇代理(Word或电话序列),该技术允许掺入电话混淆矩阵。在Babel中搜索Babel / NIST评估关键字时的经验结果10小时显影 - 测试语音收集展示(i)搜索单词索引中的Word代理显着优于电话索引中OoV单词的语音表示的优势,( ii)虽然在搜索电话索引时,电话混淆信息产生了微小的改进,但在使用Word代理搜索单词索引时,它的实际术语加权值的提高高达40%。

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