ZemPod: A semantic web
approach to podcasting
Journal Of Web Semantics 2008
Oscar Celma, Music Technology Group, Spain
Yves Raimond, Centre for Digital Music, UK
August 31th, 2009
Contents
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2
Introduction
Background
System architecture
Usage scenario
Conclusions
Introduction [1/2]
 Podcast
 Portmanteau of the “iPod” and “broadcast”
 A media file distributed in Internet
 Use syndication feeds
 Explosion in popularity of mobile devices
 Make syndication model more attractive
 Thousands of audio podcasts are available
on the net
3
Introduction [2/2]
 There are some limitations of podcasting
 No formal description
 Only textual description available in HTML
 No information about the contents of a podcast
session
 Consists of a single audio file
 Difficult to seek into one of the music tracks
 To overcome these limitations
 Using traditional audio signal processing
 Speech/audio segmentation
 Audio identification
4
 Adding semantics to the podcast
Contents
 Introduction
 Background
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Multimedia web syndication
Speech/music segmentation
Audio identification
The music ontology
 System architecture
 Usage scenario
 Conclusions
5
Multimedia web syndication [1/2]
 File format used for syndication
 RSS
 Really Simple Syndication (RSS 2.0)
 Rich Site Summary (RSS 0.91 and 1.0)
 RDF Site Summary (RSS 1.0)
 Atom
 To standardize feeds notation and autodiscovery
 Due to some limitations and incompatibility versions of
the RSS family
6
Multimedia web syndication [2/2]
 Example of RSS
7
Feeds and the semantic web
 Atom/Owl
 Aims at capturing
the semantics of the
Atom syndication
format
 Feed
 Attached metadata
 Entry
 Holds a text content
8
Speech/music segmentation
 Discriminating between speech
(or spoken content) versus music
 Achieving an automatically and meaningful
segmentation of a podcast session
 Speech/music segmentation methods
9
 Gaussian Mixture Models (GMM)
 Support Vector Machines (SVM) classifiers
 Combination of standard Hidden Markov
Models and Multilayer Perceptrons
Audio identification
 Allows identification of unknown music
 Audio fingerprint
 A unique, compact code derived from
perceptually relevant aspects of a recording
 Usages
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Identification
Authentication
Content-based key generation
Content-based audio retrieval and processing
 Hidden Markov Models (HMM)
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 Can precisely model temporal evolution of
audio signals
Music ontology [1/2]
 Create a formal framework
 Describing music-related information
 Covering complex editorial information
 External Ontologies used by Music Ontology
 OWL-Time ontology
 Describing the temporal content of Web
 Interval, Instant
 FRBR
 Functional Requirements for Bibliographic Records
 Work, Expression, Manifestation, Item
 FOAF
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 Friend Of A Friend
 Person, Group, Organization
Music ontology [2/2]
 Describing a music production workflow
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Contents
 Introduction
 Background
 System architecture
 RDFizing a podcast session
 Access and workflow
 Awareness of feeds
 Resource identifiers
 Usage scenario
 Conclusions
13
System architecture
 Main goal is
 Analysing and
decomposing a
given podcast audio
file
 RDFizing the
podcast information
14
 The system
segments the
audio file into
speech and
music sections
15
 Apply speech
recognition to
extract a list of
textual terms
16
 Weight terms’
relevance
according to a
dictionary of
musical terms
17
 Recognize
music chunks
using
fingerprinting
18
 Query a
metadata
repository to
get basic
information
with the track
19
RDFizing a podcast session
 To describe the semantics of a podcast
 Using Atom-OWL and music ontology
 “From 0 to 2 min, there is someone
speaking about Michel Jackson, then there
is a recording of a ‘Billie Jean’ in 1983”
 Using 2 sub concept of the Event
 MusicSegment
 Temporal region holding music
 SpeechSegment
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 Temporal region holding speech
Access and workflow
 REST interface
 Representational state transfer
 Style of software architecture for distributed
hypermedia systems such as WWW
 Allow us to access the podcast service
 http://zempod.net/
 Considering the podcast service is available
21
Access and workflow
- Awareness of feeds
POST
USER
201 (Created)
http://zempod.net/feed
Location Identifier
http://zempod.net/feed/4567
 Internal representation of this feed
 Music ontology/AtomOWL
 Can be queried through SPARQL
22
Access and workflow
- Resource identifiers
 MO/AtomOWL are designed as a
hierarchical URI space
 Feed
 Supports a syndication
 http://zempod.net/feed/{FEEDID}
 Entry
 Holds a text content
 http://zempod.net/feed/{FEEDID}/entry{ENTRYID}
 Item
 Actual contents
 http://zempod.net/feed/{FEEDID}/entry{ENTRYID}/
item{ITEMID}
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Contents
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Introduction
Background
System architecture
Usage scenario
 Submission of the original feed
 Analysis of the new entries
 Semantic description of the new entries
 Conclusions
24
Submission of the original feed
Original feed
POST
http://www.ourmedia.org
/user/billy2rivers/mrss
201 (Created)
http://zempod.net/feed
Location Identifier
http://zempod.net/feed/1234
25
Analysis of the new entries
 Processing a new podcast session
26
Semantic description of the new entries
USER
27
GET
http://zempod.net/feed/1234
Conclusions
 To solve limitations of podcasting
 No formal description of a podcast
 Difficult to seek into one of the music tracks
 Using traditional audio signal processing
 Speech/music segmentation
 Audio identification
 Using semantic web techniques
 Transform the current RSS to the Atom/OWL
28
 It will ease some important music
information retrieval tasks
Related Ontology – MO/Event
 To express the production process of a pi
ece of music
 The main sub-classes of event
 Performance, Recording, Arrangement,
Composition
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Related Ontology - FRBR
 Functional Requirements for Bibliographic Records
 서지 레코드의 기능상 요건
 목록규칙이나 목록의 완성을 의도하는 개체-관계 모델
 서지 레코드의 구조와 관계
 목록규칙 제정과 시스템 디자인을 위한 정확한 어휘 제공
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WORK
EXPRESSION
MANIFESTATION
ITEM
저작
표현형
구현형
개별자료
is realized
is embodied
is exemplified
실현되다
구현되다
사례가 되다
is owned
is produced
is created
has a subject
소장되다
제작되다
창작되다
주제로 하다
FRBR – Entities and Relationships (1)
 Entities and Primary Relationships
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FRBR – Entities and Relationships (2)
 Entities and “Responsibility” Relationships
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FRBR – Entities and Relationships (3)
 Entities and “Subject” Relationships
WORK
has as subject
has as subject
has as subject
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WORK
EXPRESSION
PERSON
CONCEPT
OBJECT
MENIFESTATION
ITEM
CORPORATE BODY
EVENT
PLACE
MusicBrainz
34