Abstract: The present invention discloses an anti-giant panda LIF monoclonal antibody, a hybridoma cell line, and use thereof, and belongs to the field of biotechnology. The antibody comprises a heavy chain variable region having an amino acid sequence set forth in SEQ ID NO. 1 and a light chain variable region having an amino acid sequence set forth in SEQ ID NO. 2. The hybridoma cell line LIF-2 is deposited at China Center for Type Culture Collection on Oct. 28, 2021 with the accession number of CCTCC NO: C202171. The anti-giant panda LIF monoclonal antibody developed by the present invention can accurately identify the target protein LIF, and lays an important foundation for LIF protein localization, tissue expression information, study on LIF and a receptor and a target cell thereof by using the high-specificity LIF monoclonal antibody and exploration of the effect of LIF in embryonic diapause in giant pandas.

Abstract: A hybrid machine learning-based and DSP statistical post-processing technique is disclosed for voice activity detection. The hybrid technique may use a DNN model with a small context window to estimate the probability of speech by frames. The DSP statistical post-processing stage operates on the frame-based speech probabilities from the DNN model to smooth the probabilities and to reduce transitions between speech and non-speech states. The hybrid technique may estimate the soft decision on detected speech in each frame based on the smoothed probabilities, generate a hard decision using a threshold, detect a complete utterance that may include brief pauses, and estimate the end point of the utterance. The hybrid voice activity detection technique may incorporate a target directional probability estimator to estimate the direction of the speech source. The DSP statistical post-processing module may use the direction of the speech source to inform the estimates of the voice activity.