Accurate utterance classification in motivational interviews is crucial to automatically understand the quality and dynamics of client-therapist interaction, and it can serve as a key input for systems mediating such interactions. Motivational interviews exhibit three important characteristics. First, there are two distinct roles, namely client and therapist. Second, they are often highly emotionally charged, which can be expressed both in text and in prosody. Finally, context is of central importance to classify any given utterance. Previous works did not adequately incorporate all of these characteristics into utterance classification approaches for mental health dialogues. In contrast, we present M3TCM, a Multi-modal, Multi-task Context Model for utterance classification. Our approach for the first time employs multi-task learning to effectively model both joint and individual components of therapist and client behaviour. Furthermore, M3TCM integrates information from the text and speech modality as well as the conversation context. With our novel approach, we outperform the state of the art for utterance classification on the recently introduced AnnoMI dataset with a relative improvement of 20% for the client- and by 15% for therapist utterance classification. In extensive ablation studies, we quantify the improvement resulting from each contribution.

Many participants in the University of Plymouth study praised the'non-judgemental' nature of the humanoid NAO robot as it delivered its session -- with one even saying they preferred it to a human. Led by the School of Psychology, the study also showed that the robot achieved a fundamental objective of MI as it encouraged participants, who wanted to increase their physical activity, to articulate their goals and dilemmas aloud. MI is a technique that involves the counsellor supporting and encouraging someone to talk about their need for change, and their reasons for wanting to change. The role of the interviewer in MI is mainly to evoke a conversation about change and commitment, and the robot was programmed with a set script designed to elicit ideas and conversation on how someone could increase their physical activity. When finished answering each question, the participant taped the top of NAO's head to continue, with some sessions lasting up to an hour.

New research, from the University of Plymouth, U.K., indicates that a social robot can deliver a'helpful' and'enjoyable' motivational interview. This artificial intelligence equipped machine could be used to help counsel humans with a wide variety of problems, supplanting psychologists across a number of areas. Of course the use of a machine in place of a qualified psychologist remains many years away and even when the technology reaches an acceptable level of competency, revealing all to a machine may not be to everyone's taste. Nonetheless, the advances made in a recent study show how close artificial intelligence is coming to offering a counseling service. The focus has been on the "motivational interview".

New research has shown for the first time that a social robot can deliver a'helpful' and'enjoyable' motivational interview (MI) - a counselling technique designed to support behaviour change. Many participants in the University of Plymouth study praised the'non-judgemental' nature of the humanoid NAO robot as it delivered its session - with one even saying they preferred it to a human. Led by the School of Psychology, the study also showed that the robot achieved a fundamental objective of MI as it encouraged participants, who wanted to increase their physical activity, to articulate their goals and dilemmas aloud. MI is a technique that involves the counsellor supporting and encouraging someone to talk about their need for change, and their reasons for wanting to change. The role of the interviewer in MI is mainly to evoke a conversation about change and commitment, and the robot was programmed with a set script designed to elicit ideas and conversation on how someone could increase their physical activity.