Simon music

Projecte que presenta la implementació per a dispositius Android del joc 'Simon says'.

Predictability of music descriptor time series and its application to cover song detection

Intuitively, music has both predictable and unpredictable components. In this work we assess this qualitative statement in a quantitative way using common time series models fitted to state-of-the-art music descriptors. These descriptors cover different musical facets and are extracted from a large collection of real audio recordings comprising a variety of musical genres. Our findings show that music descriptor time series exhibit a certain predictability not only for short time intervals, but also for mid-term and relatively long intervals. This fact is observed independently of the descriptor, musical facet and time series model we consider. Moreover, we show that our findings are not only of theoretical relevance but can also have practical impact. To this end we demonstrate that music predictability at relatively long time intervals can be exploited in a real-world application, namely the automatic identification of cover songs (i.e. different renditions or versions of the same musical piece). Importantly, this prediction strategy yields a parameter-free approach for cover song identification that is substantially faster, allows for reduced computational storage and still maintains highly competitive accuracies when compared to state-of-the-art systems.

A two-stage approach for tonic identification in indian art music

In this paper we propose a new approach for tonic identification in Indian art music and present a proposal for acomplete iterative system for the same. Our method splits the task of tonic pitch identification into two stages. In the first stage, which is applicable to both vocal and instrumental music, we perform a multi-pitch analysis of the audio signal to identify the tonic pitch-class. Multi-pitch analysisallows us to take advantage of the drone sound, which constantlyreinforces the tonic. In the second stage we estimate the octave in which the tonic of the singer lies and is thusneeded only for the vocal performances. We analyse the predominant melody sung by the lead performer in order to establish the tonic octave. Both stages are individually evaluated on a sizable music collection and are shown toobtain a good accuracy. We also discuss the types of errors made by the method.Further, we present a proposal for a system that aims to incrementally utilize all the available data, both audio and metadata in order to identify the tonic pitch. It produces a tonic estimate and a confidence value, and is iterative in nature. At each iteration, more data is fed into the systemuntil the confidence value for the identified tonic is above a defined threshold. Rather than obtain high overall accuracy for our complete database, ultimately our goal is to develop a system which obtains very high accuracy on a subset of the database with maximum confidence.

Applause identification and its relevance to archival of Carnatic music

A Carnatic music concert is made up of a sequence of pieces, where each piece corresponds to a particular genre and ra¯aga (melody). Unlike a western music concert, the artist may be applauded intra-performance inter-performance. Most Carnatic music that is archived today correspond to a single audio recordings of entire concerts.The purpose of this paper is to segment single audio recordings into a sequence of pieces using thecharacteristic features of applause and music. Spectral flux, spectral entropy change quite significantly from music to applause and vice-versa. The characteristics of these features for a subset of concerts was studied. A threshold based approach was used to segment the pieces into music fragments and applauses. Preliminary resultson recordings 19 concerts from matched microphones show that the EER is about 17% for a resolution of 0.25 seconds. Further, a parameter called CUSUM is estimatedfor the applause regions. The CUSUM values determine the strength of the applause. The CUSUM is used to characterise the highlights of a concert.

A method for extracting semantic information from on-line art music discussion forums

In this paper a method for extracting semantic informationfrom online music discussion forums is proposed. The semantic relations are inferred from the co-occurrence of musical concepts in forum posts, using network analysis. The method starts by defining a dictionary of common music terms in an art music tradition. Then, it creates a complex network representation of the online forum by matchingsuch dictionary against the forum posts. Once the complex network is built we can study different network measures, including node relevance, node co-occurrence andterm relations via semantically connecting words. Moreover, we can detect communities of concepts inside the forum posts. The rationale is that some music terms are more related to each other than to other terms. All in all, this methodology allows us to obtain meaningful and relevantinformation from forum discussions.

A Musically aware system for browsing and interacting with audio music collections

In the context of the CompMusic project we are developing methods to automatically describe/annotate audio music recordings pertaining to various music cultures. As away to demonstrate the usefulness of the methods we are also developing a system to browse and interact with specific audio collections. The system is an online web application that interfaces with all the data gathered (audio, scores plus contextual information) and all the descriptions that are automatically generated with the developed methods. In this paper we present the basic architecture of the proposed system, the types of data sources that it includes,and we mention some of the culture specific issues that we are working on for its development. The system is in a preliminary stage but it shows the potential that MIR technologies can have in browsing and interacting with musiccollections of various cultures.

Opportunities for a cultural specific approach in the computational description of music

The current research in Music Information Retrieval (MIR) is showing the potential that the Information Technologies can have in music related applications. Amajor research challenge in that direction is how to automaticallydescribe/annotate audio recordings and how to use the resulting descriptions to discover and appreciate music in new ways. But music is a complex phenomenonand the description of an audio recording has to deal with this complexity. For example, each musicculture has specificities and emphasizes different musicaland communication aspects, thus the musical recordings of each culture should be described differently. At the same time these cultural specificities give us the opportunity to pay attention to musical concepts andfacets that, despite being present in most world musics, are not easily noticed by listeners. In this paper we present some of the work done in the CompMusic project, including ideas and specific examples on how to take advantage of the cultural specificities of differentmusical repertoires. We will use examples from the art music traditions of India, Turkey and China.

Asiakastyytyväisyystutkimus ResMed Finland Oy:n huolto-osastolle

Tämä insinöörityö on tehty osana ResMed Finland Oy:n huoltotoiminnan laadun parannus- ja kehittämisprojektia. Työtehtävänä oli suorittaa yrityksen huolto-osaston asiakastyytyväisyystutkimus. Työn tavoitteena oli selvittää, miten laadukkaana asiakkaat kokevat yrityksen huoltoosaston toiminnan sekä millä osa-alueilla yrityksen huoltotoimintaa tulisi erityisesti kehittää, jotta se täyttäisi paremmin asiakkaan siihen kohdistamat odotukset, tarpeet ja vaatimukset. Työ aloitettiin selvittämällä, mistä osatekijöistä palvelun laatu ja asiakastyytyväisyys muodostuvat, ja miten ne vaikuttavat yrityksen toimintaan ja kannattavuuteen. Lisäksi selvitettiin perusteita asiakastyytyväisyystutkimuksen tekemiselle ja yleisesti huoltopalvelun ulottuvuuksia asiakaspalvelun osa-alueena. Alkuselvitysten jälkeen aloitettiin varsinainen asiakastyytyväisyystutkimuksen suorittaminen. Tutkimus tehtiin lomakekyselynä. Kysely koski huoltohenkilökunnan ja huoltotoiminnan lisäksi huoltokoulutusta, varaosamyyntiä sekä yrityksen tuotteiden ja varaosien Internet- markkinointisivustoa (www.resmedtuotteet.fi). Kysymykset esitettiin sekä monivalintamuodossa että avoimina kysymyksinä. Asiakastyytyväisyystutkimus suoritettiin helmi - kesäkuun aikana vuonna 2006. Kyselylomakkeita postitettiin yhteensä 45 kappaletta. Näistä 17 palautui täytettynä takaisin, joten tutkimuksen vastausprosentti oli 38. Pienistä puutteistaan huolimatta, ResMedin huoltotoiminta sai tutkimuksen perusteella yleisarvosanaksi kiitettävän. Työn tuloksena saatiin paljon arvokasta tietoa yrityksen huoltotoiminnasta -mitä hyvää siinä nykyisellään on ja mitkä sen osa-alueet tarvitsevat kipeimmin kohennusta. Tutkimus auttoi myös asiakkaiden tarpeiden ja odotuksien kartoittamisessa. Työn avulla yritys sai tietoonsa, mitkä huoltotoiminnan osa-alueet ovat asiakkaiden mielestä tärkeimpiä, ja mihin sen on siis erityisesti panostettava.