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    • 3. 发明授权
    • Predicting pronouns of dropped pronoun style languages for natural language translation
    • 预测用于自然语言翻译的代词缩略语言代词
    • US08903707B2
    • 2014-12-02
    • US13348995
    • 2012-01-12
    • Bing ZhaoImed ZitouniXiaoqiang LuoVittorio Castelli
    • Bing ZhaoImed ZitouniXiaoqiang LuoVittorio Castelli
    • G06F17/28
    • G06F17/2827
    • A method, an apparatus and an article of manufacture for determining a dropped pronoun from a source language. The method includes collecting parallel sentences from a source and a target language, creating at least one word alignment between the parallel sentences in the source and the target language, mapping at least one pronoun from the target language sentence onto the source language sentence, computing at least one feature from the mapping, wherein the at least one feature is extracted from both the source language and the at least one pronoun projected from the target language, and using the at least one feature to train a classifier to predict position and spelling of at least one pronoun in the target language when the at least one pronoun is dropped in the source language.
    • 一种用于从源语言确定掉落代词的方法,装置和制品。 该方法包括从源和目标语言收集并行句子,在源和目标语言中的并行句子之间创建至少一个单词对齐,将来自目标语言句子的至少一个代词映射到源语言句子上,计算 所述映射中的至少一个特征,其中从所述源语言和从所述目标语言投射的所述至少一个代词中提取所述至少一个特征,并且使用所述至少一个特征来训练分类器来预测位置和拼写的位置和拼写 当至少一个代词在源语言中被删除时,目标语言中至少有一个代词。
    • 6. 发明申请
    • Predicting Pronouns for Pro-Drop Style Languages for Natural Language Translation
    • 预测自然语言翻译中Pro-Drop风格语言的代词
    • US20130185049A1
    • 2013-07-18
    • US13348995
    • 2012-01-12
    • Bing ZhaoImed ZitouniXiaoqiang LuoVittorio Castelli
    • Bing ZhaoImed ZitouniXiaoqiang LuoVittorio Castelli
    • G06F17/28G06F17/27
    • G06F17/2827
    • A method, an apparatus and an article of manufacture for determining a dropped pronoun from a source language. The method includes collecting parallel sentences from a source and a target language, creating at least one word alignment between the parallel sentences in the source and the target language, mapping at least one pronoun from the target language sentence onto the source language sentence, computing at least one feature from the mapping, wherein the at least one feature is extracted from both the source language and the at least one pronoun projected from the target language, and using the at least one feature to train a classifier to predict position and spelling of at least one pronoun in the target language when the at least one pronoun is dropped in the source language.
    • 一种用于从源语言确定掉落代词的方法,装置和制品。 该方法包括从源和目标语言收集并行句子,在源和目标语言中的并行句子之间创建至少一个单词对齐,将来自目标语言句子的至少一个代词映射到源语言句子上,计算 所述映射中的至少一个特征,其中从所述源语言和从所述目标语言投射的所述至少一个代词中提取所述至少一个特征,并且使用所述至少一个特征来训练分类器来预测位置和拼写的位置和拼写 当至少一个代词在源语言中被删除时,目标语言中至少有一个代词。
    • 7. 发明授权
    • Packet loss concealment based on statistical n-gram predictive models for use in voice-over-IP speech transmission
    • 基于用于语音IP语音传输的统计n-gram预测模型的分组丢失隐藏
    • US07701886B2
    • 2010-04-20
    • US10856728
    • 2004-05-28
    • Minkyu LeeQiru ZhouImed Zitouni
    • Minkyu LeeQiru ZhouImed Zitouni
    • H04Q11/00
    • G10L19/04G10L19/005H04L65/80H04Q2213/13034H04Q2213/13296H04Q2213/13389
    • A method for performing packet loss concealment of lost packets in Voice over IP (Internet Protocol) speech transmission. Statistical n-gram models are initially created with use of a training speech corpus, and then, packets lost during transmission are advantageously replaced based on these models. In particular, the existence of statistical patterns in successive voice over IP (VoIP) packets is advantageously exploited by first using conventional vector quantization (VQ) techniques to quantize the parameter data for each packet with use of a corresponding VQ index, and then determining statistical correlations between consecutive sequences of such VQ indices representative of the corresponding sequences of n packets. The statistic n-gram predictive models so created are then used to predict parameter data for use in representing lost data packets.
    • 一种用于在IP语音(因特网协议)语音传输中执行丢包隐藏丢失分组的方法。 最初使用训练语音语料库创建统计n-gram模型,然后基于这些模型有利地替换传输期间丢失的分组。 特别地,通过首先使用常规矢量量化(VQ)技术来利用相应的VQ索引对每个分组的参数数据进行量化,有利地利用连续IP语音(VoIP)分组中的统计模式的存在,然后确定统计 这种VQ索引的连续序列之间的相关性表示n个分组的相应序列。 然后,如此创建的统计量n-gram预测模型用于预测用于表示丢失数据分组的参数数据。