LANGUAGE MODEL MODIFICATION FOR LOCAL SPEECH RECOGNITION SYSTEMS USING REMOTE SOURCES
    1.
    发明申请
    LANGUAGE MODEL MODIFICATION FOR LOCAL SPEECH RECOGNITION SYSTEMS USING REMOTE SOURCES 审中-公开
    使用远程来源的本地语音识别系统的语言模型修改

    公开(公告)号:US20160379626A1

    公开(公告)日:2016-12-29

    申请号:US14752450

    申请日:2015-06-26

    摘要: A language model is modified for a local speech recognition system using remote speech recognition sources. In one example, a speech utterance is received. The speech utterance is sent to at least one remote speech recognition system. Text results corresponding to the utterance are received from the remote speech recognition system. A local text result is generated using local vocabulary. The received text results and the generated text result are compared to determine words that are out of the local vocabulary and the local vocabulary is updated using the out of vocabulary words.

    摘要翻译: 对于使用远程语音识别源的本地语音识别系统,修改了语言模型。 在一个示例中,接收到讲话语音。 语音发音被发送到至少一个远程语音识别系统。 从远程语音识别系统接收到与话语相对应的文本结果。 使用本地词汇生成本地文本结果。 将接收到的文本结果和生成的文本结果进行比较,以确定不在本地词汇表中的单词,并且使用词汇单词更新本地词汇表。

    AUTOMATIC PERSONAL IDENTIFIABLE INFORMATION REMOVAL FROM AUDIO

    公开(公告)号:US20220084521A1

    公开(公告)日:2022-03-17

    申请号:US17456270

    申请日:2021-11-23

    IPC分类号: G10L15/22

    摘要: This disclosure describes systems, methods, and devices related to automatic personal identifiable information (PII) removal. A system may detect a sound signal received from a vicinity of a machine during the operation of the machine. The system may perform speech detection to detect a segment of the sound signal that comprises a speech signal. The system may modify the sound signal at the segment of the sound signal by performing a segment replacement mechanism. The system may generate a filtered sound signal to be used for monitoring the operation of the machine.

    ADAPTIVE PHASE DIFFERENCE BASED NOISE REDUCTION FOR AUTOMATIC SPEECH RECOGNITION (ASR)
    9.
    发明申请
    ADAPTIVE PHASE DIFFERENCE BASED NOISE REDUCTION FOR AUTOMATIC SPEECH RECOGNITION (ASR) 有权
    自适应语音识别自适应噪声抑制(ASR)

    公开(公告)号:US20150078571A1

    公开(公告)日:2015-03-19

    申请号:US14124790

    申请日:2013-09-17

    IPC分类号: G10K11/178

    摘要: Embodiments of a system and method for adapting a phase difference-based noise reduction system are generally described herein. In some embodiments, spatial information associated with a first and second audio signal are determined, wherein the first and second audio signals including a target audio inside a beam and noise from outside the beam. A signal-to-noise ratio (SNR) associated with the audio signals is estimated. A mapping of phase differences to gain factors is adapted for determination of attenuation factors for attenuating frequency bins associated with noise outside the beam. Spectral subtraction is performed to remove estimated noise from the single-channel signal based on a weighting that affects frequencies associated with a target signal less. Frequency dependent attenuation factors are applied to attenuate frequency bins outside the beam to produce a target signal having noise reduced.

    摘要翻译: 这里一般地描述用于适配基于相位差的降噪系统的系统和方法的实施例。 在一些实施例中,确定与第一和第二音频信号相关联的空间信息,其中第一和第二音频信号包括波束内的目标音频和来自波束外的噪声。 估计与音频信号相关联的信噪比(SNR)。 相位差与增益因子的映射适用于确定用于衰减与波束外的噪声相关联的频率仓的衰减因子。 基于影响与目标信号相关的频率的加权,进行光谱减法以从单信道信号中去除估计的噪声。 应用频率相关的衰减因子来衰减波束外的频率仓,以产生具有降噪的目标信号。

    ENHANCED SPATIAL AUDIO-BASED VIRTUAL SEATING ARRANGEMENTS

    公开(公告)号:US20220343289A1

    公开(公告)日:2022-10-27

    申请号:US17853853

    申请日:2022-06-29

    IPC分类号: G06Q10/10

    摘要: This disclosure describes systems, methods, and devices related to presenting video conferencing virtual seating arrangements. A method may include generating a first similarity score indicative of a first similarity between a first voice of a first virtual meeting user and a second voice of a second virtual meeting user; generating a second similarity score indicative of a second similarity between the first voice of the first virtual meeting user and a third voice of a third virtual meeting user; determining, based on the first similarity score and the second similarity score, a similarity loss for a virtual seating arrangement; determining that the similarity loss is a minimum similarity loss of respective similarity losses for different virtual seating arrangements; generating presentation data, for the virtual meeting, including virtual representations of the virtual meeting users arranged based on the virtual seating arrangement; and presenting the presentation data.