The invention relates to a voice state detection method suitable for an echo cancellation system. The voice state detection method relates to the field of voice interaction technologies based on an IP network. The voice state detection method comprises the steps of: constructing a support vector machine (SVM) classifier by utilizing noise training samples and voice training samples, wherein signals to be detected are far-end and near-end signals after blocking, carrying out VAD judgment on the block far-end signal by adopting the constructed SVM classifier based on a Gaussian mixture model, stopping updating and filtering of a filter and outputting a near-end voice signal directly if the judgment result is that no voice exists, and carrying out double-end conversation judgment when judging that voice exists at a far end; stopping updating coefficients of the filter when in double-end conversation, and filtering the near-end signal; otherwise, conducting coefficient updating and filtering of the filter according to the far-end signal. The voice state detection method improves accuracy of voice activity detection, prevents a double-end mute state from being misjudged to be a double-end conversation state, and prevents error updating and filtering of the filter without a reference signal.