## 1 Introduction
Other tools incorporate speech technologies to assist automated speech therapy in childhood apraxia of speech (CAS) [18], whereas others give a visual feedback of the positioning of the articulatory elements to produce different sounds [19]. Diagnosing and training tools for stuttering problems in children have also been developed [20]. However, despite the positive impact that prosodic training would have on communication abilities, little attention has been paid to the development of technological resources that specifically consider the learning of prosody in students with special needs, in particular those with Down syndrome. This can be explained by considering the difficulty of assigning a change in a suprasegmental feature to an intonational meaning in a unique and unambiguous way (since those features-tone, intensity, duration- co-occur to express a wide range of linguistic and paralinguistic meanings), together with the multiplicity of correct possibilities to reach the same intonational meaning. To advance in the line of developing specific resources to minimize the limitations concerning prosody and pragmatics in individuals with developmental and intellectual disabilities, we have developed an educational video game to train prosody, \"PRADIA: Mystery in the city\" [21;22] (see Section 2.1). Automatic assessment of pathological speech has also been researched, but, in general, the studies on the topic are related to specific aspects and populations. Some works focus on the speech intelligibility of people with aphasia [23;24] or speech intelligibility in pathological voices [25;26]. Others try to identify speech disorders in children with cleft lip and palate [27] or to predict automatically some dysarthric speech evaluation metrics, such as intelligibility, severity and articulation impairment [28;29]. In addition, the recognition of speech emotions and autism spectrum disorders has also been investigated [30]. All these works include a subjective evaluation carried out by experts as a reference to train the classification systems. In this work, we analyze the difficulties of automatically predicting the quality of the prosody of the speech produced by individuals with Down syndrome and propose a new approach that will serve as a baseline for future work. Recordings of individuals with Down syndrome collected in different sessions using the educational video game \"PRADIA: Mystery in the city\" gave us information about the relevant features needed to make an automatic classification of the productions. The speech corpus obtained during the game was examined by a therapist, who evaluated in real time the quality of the oral productions, and by a prosody expert, who carried out an off-line evaluation. The judgments of the expert were used to train an automatic classifier that predicts quality by using acoustic features extracted from the recordings of the corpus. Results were related to measurements of participants' developmental level, prosody perception and production performance, obtained in the PEPS-C test. This methodology was followed to achieve two main objectives: (1) developing an automatic classifier to predict the prosodic quality of the utterances produced by individuals with Down syndrome when using the PRADIA video game; and (2) analyzing the impact of the speaker heterogeneity in the classification results. The paper is structured following these objectives. In Section 2, the experimental procedure is described, which includes a description of the video game, the procedure for corpus collection and evaluation, the processing of speech material and the classification of the samples. Section 3 describes the classification results (Objective 1) and the impact of the speaker variability on the classification results (Objective 2). We end the paper with a discussion of the relevance of the results (Section 4) to the assessment of the prosodic quality on people with Down syndrome (Objective 1) and the dependence of the speaker in this assessment (Objective 2).