会员体验
专利管家(专利管理)
工作空间(专利管理)
风险监控(情报监控)
数据分析(专利分析)
侵权分析(诉讼无效)
联系我们
交流群
官方交流:
QQ群: 891211   
微信请扫码    >>>
现在联系顾问~
热词
    • 1. 发明申请
    • CEPSTRAL SEPARATION DIFFERENCE
    • CEPSTRAL分离差异
    • WO2013187826A2
    • 2013-12-19
    • PCT/SE2013/050648
    • 2013-06-05
    • JEMARDATOR AB
    • KHAN, TahaWESTIN, JerkerDAUGHERTY, Mark
    • G10L25/66
    • G10L21/06G10L15/02G10L19/02G10L25/03G10L25/60G10L25/66
    • A method for characterization of a human speech comprises performing (220) of a discrete transform on a speech sample of the human speech. A speech logarithmic power spectrum is created (222) by taking a logarithmic of the speech frequency spectrum. An inverse discrete transform is performed (224) on the speech logarithmic power spectrum into the quefrency domain. Lifterings (226, 228) of the speech cepstrum is performed, giving a high and low end speech cepstrum, respectively. The discrete transform is performed (230) on the high end speech cepstrum, creating a source excitation log-power spectrum. The discrete transform is performed (232) on the low end speech cepstrum, creating a vocal tract filter log-power spectrum. A cepstral separation difference is calculated (234) as a difference between the source excitation log-power spectrum and the vocal tract filter log-power spectrum. The human speech is characterized (238) based on the cepstral separation difference.
    • 用于表征人类语音的方法包括对人类语音的语音样本执行离散变换(220)。 通过采用语音频谱的对数来创建语音对数功率谱(222)。 在语音对数功率谱上执行逆离散变换(224)到排队域中。 执行语音倒谱的升降(226,228),分别给出高低端语音倒频谱。 在高端语音倒频谱上执行离散变换(230),创建源激励对数功率谱。 在低端语音倒频谱上执行离散变换(232),创建声道滤波器对数功率谱。 计算倒谱分离差(234)作为源激发对数功率谱与声道滤波器对数功率谱之间的差异。 人类语言的特征(238)基于倒谱分离差异。
    • 2. 发明申请
    • MOVEMENT DISORDER MONITORING
    • 运动障碍监测
    • WO2006088415A1
    • 2006-08-24
    • PCT/SE2006/000203
    • 2006-02-14
    • JEMARDATOR ABWESTIN, JerkerDAUGHERTY, MarkGROTH, TorgnyNYHOLM, Dag
    • WESTIN, JerkerDAUGHERTY, MarkGROTH, TorgnyNYHOLM, Dag
    • A61B5/16G06F19/00
    • A61B5/1124A61B5/0022A61B5/16A61B5/4082A61B5/7264G06F19/00G06F19/3418G16H10/20G16H40/63
    • A test battery (10) for patients having fluctuating movement disorder, e.g. Parkinson's disease, comprises both a motor test section (17) and a patient diary collection section (19) collecting data representing patient subjective experiences. The test battery (10) further comprises a scheduler (20), which is arranged to restrict operation of the motor test section (17) and the patient diary collection section (19) to a multitude of predetermined limited time intervals. This restriction in time provides an association in time between the two types of tests, as well as a possibility for timing the test intervals dependent on e.g. the medication schedule or the daily activity schedule. The limited time intervals are preferably shorter than or equal to one hour, and preferably there is at least one limited time interval each 24 hours. The test battery (10) is preferably implemented as a portable device, enabling monitoring under home environment conditions.
    • 用于具有波动运动障碍的患者的测试电池(10),例如 帕金森氏症包括运动测试部分(17)和患者日记收集部分(19),其收集表示患者主观体验的数据。 测试电池(10)还包括调度器(20),其被布置为将电动机测试部分(17)和患者日记收集部分(19)的操作限制到多个预定的有限时间间隔。 这种时间限制提供了两种类型的测试之间的时间关联,以及根据例如测试时间来定时测试间隔的可能性。 服药时间表或日常活动时间表。 有限的时间间隔优选短于或等于1小时,并且优选地每24小时至少有一个有限的时间间隔。 测试电池(10)优选地被实现为便携式设备,使得能够在家庭环境条件下进行监控。
    • 3. 发明公开
    • CEPSTRAL SEPARATION DIFFERENCE
    • CEPSTRAL分离差异
    • EP2862169A2
    • 2015-04-22
    • EP13803604.1
    • 2013-06-05
    • Jemardator AB
    • KHAN, TahaWESTIN, JerkerDAUGHERTY, Mark
    • G10L25/66G10L25/24
    • G10L21/06G10L15/02G10L19/02G10L25/03G10L25/60G10L25/66
    • A method for characterization of a human speech comprises performing (220) of a discrete transform on a speech sample of the human speech. A speech logarithmic power spectrum is created (222) by taking a logarithmic of the speech frequency spectrum. An inverse discrete transform is performed (224) on the speech logarithmic power spectrum into the quefrency domain. Lifterings (226, 228) of the speech cepstrum is performed, giving a high and low end speech cepstrum, respectively. The discrete transform is performed (230) on the high end speech cepstrum, creating a source excitation log-power spectrum. The discrete transform is performed (232) on the low end speech cepstrum, creating a vocal tract filter log-power spectrum. A cepstral separation difference is calculated (234) as a difference between the source excitation log-power spectrum and the vocal tract filter log-power spectrum. The human speech is characterized (238) based on the cepstral separation difference.
    • 用于表征人类语音的方法包括对人类语音的语音样本执行(220)离散变换。 通过取对数的语音频谱来创建(222)语音对数功率谱。 对语音对数功率谱进行逆离散变换(224)到逆频域。 执行语音倒谱的Lifterings(226,228),分别给出高端和低端语音倒谱。 对高端语音倒谱执行离散变换(230),产生源激励对数功率谱。 在低端语音倒谱上执行(232)离散变换,创建声道滤波器对数功率谱。 作为声源激励对数功率谱和声道滤波对数功率谱之差来计算(234)倒谱差分差。 基于倒谱分离差异来表征人类言语(238)。