tools rhythm compmusicseminar · 14 dec, 2013 ajay srinivasamurthy akshay anantapadmanabhan,...

Computational Tools for Rhythm Analysis

CompMusic Seminar, IIT Madras, Chennai, India 14 Dec, 2013

Ajay Srinivasamurthy

Akshay Anantapadmanabhan, Vinutha T Prasad, Vignesh Ishwar

Computational rhythm analysis

§  Rhythm § Musical events in time that group into patterns

§  Computational Tools §  Understand temporal aspects of music

Patterns Structures

Tasks

Onset Detection

Tāla Tracking

Segmentation

Rhythmic pattern extraction

Rhythmic similarity

Simple

Complex

Tasks

Onset Detection

Tāla Tracking

Segmentation

Rhythmic pattern extraction

Rhythmic similarity

Simple

Complex

Onset Detection

Onset Detection

§  Many sources §  Different spectral characteristics

Onset Detection

§  Mridangam stroke onsets §  Right and Left

Pre-processing: Melody Suppression Original

Melody Suppressed

Jagadanandakaraka,  Pure  Expressions  by  Aneesh  Vidyashankar  

Mridangam Onsets: Right

Jagadanandakaraka,  Pure  Expressions  by  Aneesh  Vidyashankar  

Mridangam Onsets: Left

Jagadanandakaraka,  Pure  Expressions  by  Aneesh  Vidyashankar  

Tāla Tracking

Tāla recognition

Tāla tracking

§  Tracking events in the tāla cycle §  Akshara, beats, sama, edupu (of a composition)

§  Supervised

Akshara period

§  Periodicity in onsets §  Correct metrical level – aksharas

Aksharas

Onsets Tempogram

Ajay   Srinivasamurthy,   Xavier   Serra,   “A   Supervised   Approach   to   Hierarchical  Metrical   Cycle   Tracking   from   Audio  Music  Recordings”,  submiHed  to  ICASSP  2014.    

Prior knowledge about Akshara

period

Akshara tracking

Jagadanandakaraka,  Pure  Expressions  by  Aneesh  Vidyashankar  

Where are the sama ?

Jagadanandakaraka,  Pure  Expressions  by  Aneesh  Vidyashankar  

Tracking the sama

Jagadanandakaraka,  Pure  Expressions  by  Aneesh  Vidyashankar  

Model for tāla structure

Model for sama characteristics

Learning the sama

Jagadanandakaraka,  Pure  Expressions  by  Aneesh  Vidyashankar  

Model for tāla structure

Need  an  audio  collec,on  with  expert  annota,ons    

Model for sama characteristics

Tāla tracking in Dunya

The goal !

Svara  raga  sudha,  Rendezvous  with  Legends,    ChiRbabu  (Veena)   2  kalai  

The goal !

Jaya  Jaya,  Maestro  in  Concert,    Dr.  M  L  Vasanthakumari    

Rhythm based similarity: Tāla

§  Listener participation §  Structural Similarity

§  Based on components of a tāla

User feedback

Identify tāla  components

Compute similarity measures

Segmentation

Structural segmentation: Concert

A  part  of  a  concert  

Kriti

Tani āvartanam

Padi  Sarala  and  Hema  A  Murthy,  “Inter  and  intra  segmentaWon  of  CarnaWc  music  recordings  for  archival,”  in  Proc.  ISMIR  2013,  Brazil.  

Structural segmentation: Kriti

Pallavi, Anupallavi, Charanam, Swaram, Niraval

Rhythmogram

Ragam-Tanam-Pallavi

Percussion solo – Tabla

Percussion solo

Tani āvartanam transcription

Machine Learning Stroke Models

Thom  

Tha  Dheem  

Strokes

Stroke Sequences Transcribed Strokes

Training Testing

Akshay  Anantapadmanabhan,  Ashwin  Bellur,  Hema  Murthy,  “Modal  Analysis  and  TranscripWon  of  Strokes  of  the  Mridangam   using   Non-­‐negaWve  Matrix   FactorizaWon”,   in   Proc.   of   38th   InternaWonal   Conference   on   AcousWcs,  Speech,  and  Signal  Processing  (ICASSP),  2013.  

Rhythmic patterns and similarity

Discovery and representation

Rhythm Similarity – Patterns

In the future…

From  Ninne  NammiW,  December  Season  2007,  Gayathri  Girish  

From  Ninne  NammiW,  PaddhaR  -­‐  K  V  Narayanaswamy  &  N  Ramani,  by  K  V  Narayanaswamy  &  N  Ramani,  2003  

From  Ninne  Nammi  Nanu,  December  Season  2003,  O.S.  Thyagarajan  

The question

From  Ninne  NammiW,  PaddhaR  -­‐  K  V  Narayanaswamy  &  N  Ramani,  by  K  V  Narayanaswamy  &  N  Ramani,  2003  

From  Ninne  Nammi  Nanu,  December  Season  2003,  O.S.  Thyagarajan  

?

Carnatic Music Beat Station

Thank you!

Extra slides

Periodicity and Continuity

Sama tracking

§  Knowledge-based

Ajay   Srinivasamurthy,   Xavier   Serra,   “A   Supervised   Approach   to   Hierarchical  Metrical   Cycle   Tracking   from   Audio  Music  Recordings”,  submiHed  to  ICASSP  2014.    

Onsets

Model for Tala structure

Audio features

Cycle Period

Possible locations

Sama Tracking

Annotated Test Corpus

Ajay   Srinivasamurthy,   Xavier   Serra,   “A   Supervised   Approach   to   Hierarchical  Metrical   Cycle   Tracking   from   Audio  Music  Recordings”,  submiHed  to  ICASSP  2014.    

Model for Tala structure

Audio features

Sama Candidates

Onsets

Sama Period

Sama Tracking

Need  a  test  corpus    with  expert  annota,ons  

Rhythm Similarity