We present a speech transmission system operating at a low bit rate (about 1000 bits/s), which is based on the following principle. The speech signal is analysed using a LPC technique and, for each frame, the global parameters of the input signal (energy, pitch, voicing) on the one hand, and secondly the filter coefficients are separately coded. Studies have been mainly focused on the last point. We have compared several representation spaces (autocorrelation, cepstrum, LPC analysis without and with preemphasis), in order to choose the most suitable representation for a good vector quantization. The latter has been performed by a very simple algorithm, which we have compared to the “LBG” method. We have shown that, in our experimental conditions, the simplicity of our algorithm is an advantage, and that it performs a good vector quantization of the spectral space. The second part of the study is oriented towards the use of the codebook obtained as described above. We compute it from several speakers, for a total of about 30000 frames (about six minutes) of speech: it consists of more than 1500 vectors. We have studied how to obtain a fast coding of a vector with this codebook, losing the optimality of the nearest neighbour coding. We have shown that the distortion is only slightly increased by using clustering techniques on the codebook, leading to a hierarchical coding decision, which allows a very fast coding of any new vector. In conclusion, the simplification of the codebook construction (associated with a correct choice of the spectral representation space), and a fast (but suboptimal) method of coding with such a codebook lead to a system whose performances are only slightly degraded compared to reference spectral vector quantization systems for speech transmission.