Virtual Conductor for String Quartet Practice

This paper presents a system that emulates an ensemble conductor for string quartets. This application has been developed as a support tool for individual and group practice, so that users of any age range can use it to further hone their skills, both for regular musicians and students alike. The virtual conductor designed can offer similar indications to those given by a real ensemble conductor to potential users regarding beat times, dynamics, etc. The application developed allows the user to rehearse his/her performance without the need of having an actual conductor present, and also gives access to additional tools to further support the learning/practice process, such as a tuner or a melody evaluator. The system developed also allows for both solo practice and group practice. A set of tests were conducted to check the usefulness of the application as a practice support tool. A group of musicians from the Chamber Orchestra of Malaga including an ensemble conductor tested the system, and reported to have found it a very useful tool within an educational environment and that it helps to address the lack of this kind of educational tools in a self-learning environment.This work has been funded by the Ministerio de Economia y Competitividad of the Spanish Government under Project No. TIN2010-21089-C03- 02 and Project No. IPT-2011-0885-430000 and by the Ministerio de Industria, Turismo y Comercio under Project No. TSI-090100-2011-25

A Speaker Diarization System for Studying Peer-Led Team Learning Groups

Peer-led team learning (PLTL) is a model for teaching STEM courses where small student groups meet periodically to collaboratively discuss coursework. Automatic analysis of PLTL sessions would help education researchers to get insight into how learning outcomes are impacted by individual participation, group behavior, team dynamics, etc.. Towards this, speech and language technology can help, and speaker diarization technology will lay the foundation for analysis. In this study, a new corpus is established called CRSS-PLTL, that contains speech data from 5 PLTL teams over a semester (10 sessions per team with 5-to-8 participants in each team). In CRSS-PLTL, every participant wears a LENA device (portable audio recorder) that provides multiple audio recordings of the event. Our proposed solution is unsupervised and contains a new online speaker change detection algorithm, termed G 3 algorithm in conjunction with Hausdorff-distance based clustering to provide improved detection accuracy. Additionally, we also exploit cross channel information to refine our diarization hypothesis. The proposed system provides good improvements in diarization error rate (DER) over the baseline LIUM system. We also present higher level analysis such as the number of conversational turns taken in a session, and speaking-time duration (participation) for each speaker.Comment: 5 Pages, 2 Figures, 2 Tables, Proceedings of INTERSPEECH 2016, San Francisco, US

Collecting ground truth annotations for drum detection in polyphonic music

In order to train and test algorithms that can automatically detect drum events in polyphonic music, ground truth data is needed. This paper describes a setup used for gathering manual annotations for 49 real-world music fragments containing different drum event types. Apart from the drum events, the beat was also annotated. The annotators were experienced drummers or percussionists. This paper is primarily aimed towards other drum detection researchers, but might also be of interest to others dealing with automatic music analysis, manual annotation and data gathering. Its purpose is threefold: providing annotation data for algorithm training and evaluation, describing a practical way of setting up a drum annotation task, and reporting issues that came up during the annotation sessions while at the same time providing some thoughts on important points that could be taken into account when setting up similar tasks in the future

Network maps of student work with physics, other sciences, and math in an integrated science course

In 2004 Denmark introduced a compulsory integrated science course the most popular upper secondary study program. One of the nation-wide course aims are for students to "achieve knowledge about some of the central scientific issues and their social, ethical, and historical perspectives". This is to be done via collaboration between the subjects, and often involves physics and another scientific subject. The official teaching plans further state that mathematics must be used for analysing data. We use network analysis to study six different implementations of the course in terms of the structure of different kinds of teaching/learning activities. By creating networks maps of each lesson, we show that teaching/learning activities in the course seldom tends to address how sciences can work together to solve a problem, but rather stages each natural science as a distinct and separate activity with a distinct identity.Comment: 4 pages, 3 figures, 1 table, based on poster presented at PERC 2017 (http://www.compadre.org/per/conferences/2017/

EEG in the classroom: Synchronised neural recordings during video presentation

We performed simultaneous recordings of electroencephalography (EEG) from multiple students in a classroom, and measured the inter-subject correlation (ISC) of activity evoked by a common video stimulus. The neural reliability, as quantified by ISC, has been linked to engagement and attentional modulation in earlier studies that used high-grade equipment in laboratory settings. Here we reproduce many of the results from these studies using portable low-cost equipment, focusing on the robustness of using ISC for subjects experiencing naturalistic stimuli. The present data shows that stimulus-evoked neural responses, known to be modulated by attention, can be tracked in for groups of students with synchronized EEG acquisition. This is a step towards real-time inference of engagement in the classroom.Comment: 14 pages, 5 figures, 3 tables. Preprint version. Revision of original preprint. Supplementary materials added as ancillary fil

Detecting Low Rapport During Natural Interactions in Small Groups from Non-Verbal Behaviour

Rapport, the close and harmonious relationship in which interaction partners are "in sync" with each other, was shown to result in smoother social interactions, improved collaboration, and improved interpersonal outcomes. In this work, we are first to investigate automatic prediction of low rapport during natural interactions within small groups. This task is challenging given that rapport only manifests in subtle non-verbal signals that are, in addition, subject to influences of group dynamics as well as inter-personal idiosyncrasies. We record videos of unscripted discussions of three to four people using a multi-view camera system and microphones. We analyse a rich set of non-verbal signals for rapport detection, namely facial expressions, hand motion, gaze, speaker turns, and speech prosody. Using facial features, we can detect low rapport with an average precision of 0.7 (chance level at 0.25), while incorporating prior knowledge of participants' personalities can even achieve early prediction without a drop in performance. We further provide a detailed analysis of different feature sets and the amount of information contained in different temporal segments of the interactions.Comment: 12 pages, 6 figure