This paper proposes a semi-fragile speech watermarking scheme by quantization of Linear Prediction (LP) parameters, i.e. the inverse sine parameters. The watermark decoding performance is analyzed by modelling the parameters estimation error as Laplace distributed noises. The watermark detection threshold is derived according to the requirement of error probability and expected Signal to Noise Ratio (SNR). Experiments show that the proposed watermarking scheme is robust against amplitude scaling and semi-fragile to white noise addition, and thus suitable for speech authentication.