Abstract: There is provided automatic detection of pronunciation errors in spoken words utilizing a neural network model that is trained for a target phoneme. The target phoneme may be a phoneme in English language. The pronunciation errors may be detected in English words.

Abstract: There is provided a method, comprising: receiving an audio waveform of a recording comprising a pronounced word comprising a target phoneme; transforming the audio waveform to a sequence of frames; extracting one or more acoustic features from the sequence of frames; receiving a sequence of phonetic symbols representing ideal pronunciation of the pronounced word; mapping the sequence of phonetic symbols using a neural network trained for the target phoneme to obtain an embedded phonetic sequence; classifying, by a neural network trained for the target phoneme, a pronunciation in the recording as correct or as comprising one or more pronunciation errors in the target phoneme based on the one or more acoustic features and the embedded phonetic sequence.