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. 发明授权
    • Peer-aware ranking of voice streams
    • 语音流的对等感知排名
    • US09331887B2
    • 2016-05-03
    • US11277932
    • 2006-03-29
    • Li-wei HeDinei A. FlorencioXun Xu
    • Li-wei HeDinei A. FlorencioXun Xu
    • H04L12/16H04L29/06H04L12/66
    • H04L29/06027H04L12/66H04L65/403H04L65/4038
    • A peer-aware voice stream ranking method that makes decisions based on information about participants of a voice conference over a network. Whether to send a participant's own audio packet out on the network is based both on information about the participant's own voice packet and voice packets that the participant receives from other clients. A Voice Activity Score (VAS) is computed for each frame of a particular voice stream. The VAS includes a voiceness component, indicating the likelihood that the audio frame contains speech or voice, and an energy level component that indicating the ratio of current frame energy to the long-term average of energy for a current speaker. Using the VAS from the participants, the method also ranks the client's voice stream as compared to other clients' voice streams in the voice conference. If there are participants higher ranking, the client's voice stream is not sent.
    • 基于通过网络进行语音会议的参与者的信息进行决策的对等感知语音流排序方法。 是否在网络上发送参与者自己的音频数据包都是基于参与者自己的语音数据包和参与者从其他客户端收到的语音数据包的信息。 为特定语音流的每个帧计算语音活动分数(VAS)。 VAS包括声音分量,指示音频帧包含语音或语音的可能性,以及指示当前帧能量与当前说话者的长期能量平均值的比率的能量分量。 使用来自参与者的VAS,与语音会议中的其他客户端的语音流相比,该方法还对客户端的语音流进行排序。 如果参与者排名较高,则不会发送客户端的语音流。
    • 2. 发明申请
    • PEER-AWARE RANKING OF VOICE STREAMS
    • 同声传译语音流
    • US20070230372A1
    • 2007-10-04
    • US11277932
    • 2006-03-29
    • Li-wei HeDinei FlorencioXun Xu
    • Li-wei HeDinei FlorencioXun Xu
    • H04L12/16
    • H04L29/06027H04L12/66H04L65/403H04L65/4038
    • A peer-aware voice stream ranking method that makes decisions based on information about participants of a voice conference over a network. Whether to send a participant's own audio packet out on the network is based both on information about the participant's own voice packet and voice packets that the participant receives from other clients. A Voice Activity Score (VAS) is computed for each frame of a particular voice stream. The VAS includes a voiceness component, indicating the likelihood that the audio frame contains speech or voice, and an energy level component that indicating the ratio of current frame energy to the long-term average of energy for a current speaker. Using the VAS from the participants, the method also ranks the client's voice stream as compared to other clients' voice streams in the voice conference. If there are participants higher ranking, the client's voice stream is not sent.
    • 基于通过网络进行语音会议的参与者的信息进行决策的对等感知语音流排序方法。 是否在网络上发送参与者自己的音频数据包都是基于参与者自己的语音数据包和参与者从其他客户端收到的语音数据包的信息。 为特定语音流的每个帧计算语音活动分数(VAS)。 VAS包括声音分量,指示音频帧包含语音或语音的可能性,以及指示当前帧能量与当前说话者的长期能量平均值的比率的能量分量。 使用来自参与者的VAS,与语音会议中的其他客户端的语音流相比,该方法还对客户端的语音流进行排序。 如果参与者排名较高,则不会发送客户端的语音流。
    • 4. 发明申请
    • SINGLE CELL CLASSIFICATION METHOD, GENE SCREENING METHOD AND DEVICE THEREOF
    • 单细胞分类方法,基因筛选方法及其装置
    • US20140206006A1
    • 2014-07-24
    • US14239650
    • 2012-08-24
    • Xun XuLi BaoWeiming HeYong HouYe Tao
    • Xun XuLi BaoWeiming HeYong HouYe Tao
    • G06F19/22
    • G16B30/00C12Q1/6827C12Q1/6869G16B20/00
    • Provided are a single cell classification method, a gene screening method and a device for implementing the method. In that, the single cell classification method includes the following steps: sequencing the whole genomes of a plurality of single cell samples from the same group, respectively, so as to obtain reads from each single cell sample; aligning the reads from each single cell sample to the sequence of a reference genome, respectively, and performing data filtering on said reads; on the basis of the filtered reads, determining a consistent genotype of each single cell sample, in which consistent genotypes of all the single cell samples constitute an SNP dataset of said group; aimed at said each single cell, on the basis of the SNP dataset of said group, determining a corresponding genotype for each cell at a site corresponding to a position in an SNP dataset of the reference genome; and selecting an SNP site associated with cell mutation, and on the basis of the genotype of said single cell at the site, classifying said single cell.
    • 提供单细胞分类方法,基因筛选方法和实施该方法的装置。 其中,单细胞分类方法包括以下步骤:从同一组分别测序多个单细胞样品的全基因组,从而获得每个单细胞样品的读数; 将每个单个细胞样本的读数分别对准参考基因组的序列,并对所述读取执行数据过滤; 基于经过滤的读数,确定每个单细胞样品的一致的基因型,其中所有单细胞样品的一致基因型构成所述组的SNP数据集; 针对所述每个单细胞,基于所述组的SNP数据集,在对应于参照基因组的SNP数据集中的位置的位点处确定每个细胞的相应基因型; 并选择与细胞突变相关的SNP位点,并且基于所述单细胞在所述位点处的基因型,对所述单细胞进行分类。
    • 5. 发明授权
    • Entropy decoding methods and apparatus using most probable and least probable signal cases
    • 使用最可能和最不可能的信号情况的熵解码方法和装置
    • US08749409B2
    • 2014-06-10
    • US13113918
    • 2011-05-23
    • Xun Xu
    • Xun Xu
    • H03M7/00
    • H03M7/4018
    • An entropy decoding apparatus may include a data structure stored in memory. The data structure may include a decoding engine vector or context engine vector. The decoding engine vector many have a first set of bits representing a value corresponding to a state of a coding engine, a second set of bits representing an offset value, and a third set of bits representing the contents of an input stream buffer. The context vector may have a first set of bits representing an addresses of a context most probable state, a second set of bits representing a plurality of possible values corresponding to a least probable symbol state of a coding engine, a third set of bits representing an addresses of a context least probable state, a fourth set of bits representing a binary most probable symbol value, and a fifth set of bits representing a binary least probable symbol value.
    • 熵解码装置可以包括存储在存储器中的数据结构。 数据结构可以包括解码引擎向量或上下文引擎向量。 解码引擎向量许多具有表示对应于编码引擎的状态的值的第一组比特,表示偏移值的第二比特组,以及表示输入流缓冲器的内容的第三组比特。 上下文矢量可以具有表示上下文最可能状态的地址的第一组位,表示与编码引擎的最小可能符号状态对应的多个可能值的第二组位,表示第一组位的第三组位 上下文最小可能状态的地址,表示二进制最可能符号值的第四组位,以及表示二进制最小可能符号值的第五组位。