Abstract: An apparatus, a server, a method, and a tangible machine-readable medium thereof for processing and recognizing a sound signal are provided. The apparatus is configured to sense the sound signal of the environment and to dynamically derive and to transmit a feature signal and a sound feature message of the sound signal to the server. The server is configured to retrieve the stored sound models according to the sound feature message and to compare each of the sound models with the feature signal to determine whether the sound signal is abnormal after receiving the feature signal and the sound feature message.

Abstract: An apparatus, a server, a method, and a tangible machine-readable medium thereof for processing and recognizing a sound signal are provided. The apparatus is configured to sense the sound signal of the environment and to dynamically derive and to transmit a feature signal and a sound feature message of the sound signal to the server. The server is configured to retrieve the stored sound models according to the sound feature message and to compare each of the sound models with the feature signal to determine whether the sound signal is abnormal after receiving the feature signal and the sound feature message.

Abstract: A dividing module divides a voice signal into voice frames. A likelihood value generation module compares each of the voice frames with a first voice model and a second voice model to generate first likelihood values and second likelihood values. A decision module decides a windows size according to the first likelihood values and the second likelihood values. An accumulation module accumulates the first likelihood values and the second likelihood values inside the window size to generate a first sum and a second sum. A determination module determines whether the voice signal is abnormal according to the first sum and the second sum. While the voice has a big change in the environment, the decision module can dynamically adapt the windows size for decreasing the false rate of the detection and speeding up the determining of the abnormal voice.

Abstract: A device, method, and computer readable medium for adjusting speech models with selected speech data are provided. The first determination module determines whether the keyword is valid. If so, the first computing module computes the adjustment weight according to the keyword, while the second computing module computes temporary models according to the keyword, designated speech model and speech models. The adjustment module weighs the speech models and temporary models according to the adjustment weight to update the speech models. As a result, the robustness of the speech models is improved.