A method of answering machine detection, comprising: receiving an audio stream ; identifying a set of landmark features in a section of the audio stream; deriving an audio fingerprint for the section of the audio stream from the set of landmark features identified; comparing the derived audio fingerprint with at least one of a plurality of stored audio fingerprints, each derived from a respective audio stream; and determining that the received audio stream is a recorded message of an answering machine if the derived audio fingerprint is substantially equivalent to one of the plurality of stored audio fingerprints; characterised in that : the step of identifying the set of landmark features in the section of the audio stream comprises identifying points of inflection in the audio stream by stepping through sample values making up the audio stream, comparing the amplitude at each sample value with the amplitude of at least the immediately adjacent sample values, and determining whether a sample value comprises a point of inflection, and using at least some of these as landmark features; wherein, identifying points of inflection further comprises determining whether the difference in amplitude between a sample value identified as a point of inflection and the difference in amplitude between it and at least the immediately adjacent sample values exceeds a threshold, and if the threshold is exceeded, identifying that point of inflection as a persistent landmark feature for deriving the audio fingerprint. receiving an audio stream ; identifying a set of landmark features in a section of the audio stream; deriving an audio fingerprint for the section of the audio stream from the set of landmark features identified; comparing the derived audio fingerprint with at least one of a plurality of stored audio fingerprints, each derived from a respective audio stream; and determining that the received audio stream is a recorded message of an answering machine if the derived audio fingerprint is substantially equivalent to one of the plurality of stored audio fingerprints; characterised in that : the step of identifying the set of landmark features in the section of the audio stream comprises identifying points of inflection in the audio stream by stepping through sample values making up the audio stream, comparing the amplitude at each sample value with the amplitude of at least the immediately adjacent sample values, and determining whether a sample value comprises a point of inflection, and using at least some of these as landmark features; wherein, identifying points of inflection further comprises determining whether the difference in amplitude between a sample value identified as a point of inflection and the difference in amplitude between it and at least the immediately adjacent sample values exceeds a threshold, and if the threshold is exceeded, identifying that point of inflection as a persistent landmark feature for deriving the audio fingerprint. the step of identifying the set of landmark features in the section of the audio stream comprises identifying points of inflection in the audio stream by stepping through sample values making up the audio stream, comparing the amplitude at each sample value with the amplitude of at least the immediately adjacent sample values, and determining whether a sample value comprises a point of inflection, and using at least some of these as landmark features; wherein, identifying points of inflection further comprises determining whether the difference in amplitude between a sample value identified as a point of inflection and the difference in amplitude between it and at least the immediately adjacent sample values exceeds a threshold, and if the threshold is exceeded, identifying that point of inflection as a persistent landmark feature for deriving the audio fingerprint. <EOS>