A technique is presented for quantizing the articulatory space, i.e. for replacing the continuum of all possible vocal tract shapes by a finite set of shapes that span the articulatory space. Vocal tract shapes are represented as vectors of parameters that control an articulatory model, so vector quantization are applicable for deriving this codebook of tract shapes. Samples of the articulatory space are generated by interpolating model parameters along paths between selected target configurations. These shapes constitute the training data that are clustered to form the codebook. Such a codebook of shapes has direct application when vocal tract shapes must be estimated from speech. One such application, which motivated the present study, is the use of the codebook to providing starting configurations for an optimizing articulatory speech synthesizer. >