It is well known that automatic speech recognition systems that process wideband speech perform better than those processing narrowband one. Nevertheless, in order to take advantage from the wideband benefit, the problem of coexistence of true and pseudo wideband speech signals must be taken into account, where pseudo wideband signals are referred as data sampled at 16 kHz for a bandwidth of 0-4000 Hz only. In this paper, a series of speaker-independent, continuous speech phoneme recognition experiments have been carried out using the BREF80 and ESTER French corpus to quantify the problem of coexistence. An approach for solving it is proposed and it is based on the identification of the type of the signal. Then, once the signal type is identified, the system responds with the appropriate speech recognition model. The signal type identification uses a new acoustic description of the 16 kHz sampled signals and reaches a high identification rate.
