We introduce the Million Song Dataset, a freely-available collection of audio features and metadata for million contemporary popular music tracks. describe its creation process, content, possible uses. Attractive Database include range existing resources to which it is linked, fact that largest current research dataset in our field. As an illustration, we present year prediction as example application, task has, until now, been difficult study owing absence large set suitable data. show...

Abstract Social tags are free text labels that applied to items such as artists, albums and songs. Captured in these is a great deal of information highly relevant Music Information Retrieval (MIR) researchers including about genre, mood, instrumentation, quality. Unfortunately there also irrelevant noise the tags. Imperfect they may be, social source human-generated contextual knowledge music become an essential part solution many MIR problems. In this article, we describe state art...

The ACM Recommender Systems Challenge 2018 focused on automatic music playlist continuation, which is a form of the more general task sequential recommendation. Given arbitrary length, challenge was to recommend up 500 tracks that fit target characteristics original playlist. For Challenge, Spotify released dataset one million user-created playlists, along with associated metadata. Participants could submit their approaches in two tracks, i.e., main and creative where former allowed teams...

Abstract Social tags are user-generated keywords associated with some resource on the Web. In case of music, social have become an important component "Web 2.0" recommender systems, allowing users to generate playlists based use-dependent terms such as chill or jogging that been applied particular songs. this paper, we propose a method for predicting these directly from MP3 files. Using set 360 classifiers trained using online ensemble learning algorithm FilterBoost, map audio features onto...

The ACM Recommender Systems Challenge 2018 focused on the task of automatic music playlist continuation, which is a form more general sequential recommendation. Given arbitrary length with some additional meta-data, was to recommend up 500 tracks that fit target characteristics original playlist. For RecSys Challenge, Spotify released dataset one million user-generated playlists. Participants could compete in two tracks, i.e., main and creative tracks. track were only allowed use provided...

Sphinx-4 is an open source HMM-based speech recognition system written in the Java™ programming language.The design of decoder incorporates several new features response to current demands on large vocabulary systems.Some aspects include graph construction for multilevel parallel decoding with multiple feature streams without use compound HMMs, incorporation a generalized search algorithm that subsumes Viterbi as special case, token stack efficient maintenance paths during search, language...

Content recommender systems often rely on modeling users' past behavioral data to provide personalized recommendations - a practice that works well for suggesting more of the same and media require little time investment from users, such as music tracks. However, this approach can be further optimized where user is higher, podcasts, because there broader space goals might not captured by implicit signals their behavior. Allowing users directly specify help narrow possible recommendations....

We propose a recommendation technique that works by collecting text descriptions of items and using this textual aura to compute the similarity between techniques drawn from information retrieval. show how representation can be used explain similarities terms further it steer recommender. describe system demonstrates these we'll detail some preliminary experiments aimed at evaluating quality recommendations effectiveness explanations item similarity.

Several authors have presented systems that estimate the audio similarity of two pieces music through calculation a distance metric, such as Euclidean distance, between spectral features calculated from audio, related to timbre or pitch signal. These can be augmented with other, temporally rhythmically based zero-crossing rates, beat histograms, fluctuation patterns form more well-rounded function. It is our contention perceptual cultural labels, genre, style, emotion music, are also very...

With the recent dramatic transformations in world of digital music, a music listener is now just couple clicks away from being able to listen nearly any song that has ever been recorded. so much readily available, tools help user find new, interesting matches his or her taste become increasingly important. In this article we explore one such tool: recommendation. We describe common recommendation use cases as finding new artists, others with similar listening tastes, and generating...

The world of music is changing rapidly. We are now just a few clicks away from being able to listen nearly any song that has ever been recorded. This easy access endless supply how we explore, discover, share and experience music.

Recommender systems are ubiquitous and influence the information we consume daily by helping us navigate vast catalogs of like music databases. However, their linear approach surfacing content in ranked lists limits ability to help grow understand our personal preferences. In this paper, study how can better support users exploring a novel space, specifically focusing on genres. Informed interviews with expert listeners, developed TastePaths: an interactive web tool that helps explore...

As the world of online music grows, recommendation systems become an increasingly important way for listeners to discover new music. Commercial recommenders such as Last.fm and Pandora have enjoyed commercial critical success. But how well do these really work? How good are recommendations? far into Long Tail reach? In this tutorial we look at current state-of-the-art in recommendation. We examine research systems, focusing on advantages disadvantages various strategies. some challenges...

We will discuss the methodology and accuracy of Echo Nest Musical Fingerprint (ENMFP), an open-source fingerprint code generator query server that works on music files. define fingerprinting as matching arbitrary audio signal to its underlying song in a 10 million database. 1. MUSIC FINGERPRINTING “Fingerprinting” files [1] [3] is becoming necessary feature for any large scale understanding service or system. Online stores want resolve existing user catalog against their cloud storage save...

Music is a complex form of communication in which both artists and cultures express their ideas identity. When we listen to music do not simply perceive the acoustics sound temporal pattern, but also its relationship other sounds, songs, artists, emotions. Owing complex, culturally-defined distribution acoustic patterns amongst these relationships, it unlikely that general audio similarity metric will be suitable as metric. Hence, are able emulate human perception songs without making...

The proverbial celestial jukebox has become a reality. With today's online music services fan is never more than few clicks away from being able to listen nearly any song that ever been recorded. Recommender systems can play key role in this new ecosystem, helping listeners explore, discover, organize and share music. However, many ways recommendation very different other well-studied domains such as books movies. In talk we explore how recommender be used the space, particular challenges...

The Echo Nest Corporation, a music intelligence platform company based on years of retrieval research and development, provides number retrieval, search in- teractivity tools to stores, social networks, musicians, developers labels around the world. Our platform1 consists series heterogeneous data types: text from web crawls, audio signal processing machine learning, natural language processing, graph manipulation large scale map-reduce style aggregation sorting.

The world of music is changing rapidly. We are now just a few clicks away from being able to listen nearly any song that has ever been recorded. This easy access endless supply how we explore, discover, share and experience