Detection of filled pauses is a challenging research problem which has several practical applications. It can be used to evaluate the spoken fluency skills of the speaker, to improve the performance of automatic speech recognition systems or to predict the mental state of the speaker. This paper presents an algorithm for filled pause detection that is based on the premise that the vocal tract characteristics, and hence the formants, are stable during the production of a filled pause. The performance of the proposed algorithm is evaluated on real-life recordings of call center agents where the locations of the filled pauses are hand labeled. The proposed algorithm outperforms a standard cepstral stability based filled pause detection algorithm and a standard pitch-based detection technique.