公开(公告)号：US09881630B2

公开(公告)日：2018-01-30

申请号：US14984373

申请日：2015-12-30

Applicant: GOOGLE INC.

Inventor： Herbert Buchner ,  Simon J. Godsill ,  Jan Skoglund

IPC: G10L21/02 ,  G10L19/26 ,  G10L21/0224 ,  G10L21/028 ,  G10L21/0216 ,  G10L21/0208 ,  G10L21/0232

CPC classification number: G10L19/26 ,  G10L21/0208 ,  G10L21/0216 ,  G10L21/0224 ,  G10L21/0232 ,  G10L21/028 ,  G10L2021/02161 ,  G10L2021/02165 ,  H04R2410/05

Abstract: Provided are methods and systems for acoustic keystroke transient cancellation/suppression for user communication devices using a semi-blind adaptive filter model. The methods and systems are designed to overcome existing problems in transient noise suppression by taking into account some less-defective signal as side information on the transients and also accounting for acoustic signal propagation, including the reverberation effects, using dynamic models. The methods and systems take advantage of a synchronous reference microphone embedded in the keyboard of the user device, and utilize an adaptive filtering approach exploiting the knowledge of this keybed microphone signal.

公开(公告)号：US09520141B2

公开(公告)日：2016-12-13

申请号：US13781262

申请日：2013-02-28

Applicant: GOOGLE INC.

Inventor： Jens Enzo Nyby Christensen ,  Simon J. Godsill ,  Jan Skoglund

IPC: G10L21/02 ,  G10L25/48 ,  G10L21/0216 ,  G10L25/84 ,  G10L25/93 ,  G10L21/0208

CPC classification number: G10L25/48 ,  G10L21/02 ,  G10L21/0208 ,  G10L21/0216 ,  G10L25/84 ,  G10L25/93 ,  G10L2025/935

Abstract: Provided are methods and systems for detecting the presence of a transient noise event in an audio stream using primarily or exclusively the incoming audio data. Such an approach offers improved temporal resolution and is computationally efficient. The methods and systems presented utilize some time-frequency representation of an audio signal as the basis in a predictive model in an attempt to find outlying transient noise events and interpret the true detection state as a Hidden Markov Model (HMM) to model temporal and frequency cohesion common amongst transient noise events.

Abstract translation: 提供了用于检测音频流中瞬时噪声事件的存在的方法和系统，其主要或排他地使用输入音频数据。 这种方法提供了改进的时间分辨率，并且在计算上是有效的。 所提出的方法和系统利用音频信号的一些时间频率表示作为预测模型的基础，以试图找出偏离的瞬态噪声事件，并将真实检测状态解释为隐马尔可夫模型（HMM）来模拟时间和频率 瞬态噪声事件中共同的凝聚力。