公开(公告)号：US20160196833A1

公开(公告)日：2016-07-07

申请号：US14591418

申请日：2015-01-07

Applicant: GOOGLE INC.

Inventor： Simon J. GODSILL ,  Herbert BUCHNER ,  Jan SKOGLUND

IPC: G10L21/0208 ,  H04R3/00

Abstract: Provided are methods and systems for enhancing speech when corrupted by transient noise (e.g., keyboard typing noise). The methods and systems utilize a reference microphone input signal for the transient noise in a signal restoration process used for the voice part of the signal. A robust Bayesian statistical model is used to regress the voice microphone on the reference microphone, which allows for direct inference about the desired voice signal while marginalizing the unwanted power spectral values of the voice and transient noise. Also provided is a straightforward and efficient Expectation-maximization (EM) procedure for fast enhancement of the corrupted signal. The methods and systems are designed to operate easily in real-time on standard hardware, and have very low latency so that there is no irritating delay in speaker response.

Abstract translation: 提供了当被瞬态噪声（例如键盘打字噪声）损坏时增强语音的方法和系统。 该方法和系统在用于信号的语音部分的信号恢复过程中利用用于瞬态噪声的参考麦克风输入信号。 鲁棒的贝叶斯统计模型用于回归参考麦克风上的语音麦克风，这允许对所需语音信号的直接推断，同时边缘化语音和瞬态噪声的不需要的功率谱值。 还提供了一种直接有效的期望最大化（EM）程序，用于快速增强损坏的信号。 这些方法和系统被设计为能够在标准硬件上实时地进行操作，并且具有非常低的延迟，使得扬声器响应没有刺激性的延迟。

公开(公告)号：US20140244247A1

公开(公告)日：2014-08-28

申请号：US13781262

申请日：2013-02-28

Applicant: GOOGLE INC.

Inventor： Jens Enzo Nyby CHRISTENSEN ,  Simon J. GODSILL ,  Jan SKOGLUND

IPC: G10L21/0232

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科夫模型（HMM）来建模时间和频率 瞬态噪声事件中共同的凝聚力。

公开(公告)号：US20170194015A1

公开(公告)日：2017-07-06

申请号：US14984373

申请日：2015-12-30

Applicant: GOOGLE INC.

Inventor： Herbert BUCHNER ,  Simon J. GODSILL ,  Jan SKOGLUND

IPC: G10L19/26 ,  G10L21/028 ,  G10L21/0224

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.