---
_id: '26770'
abstract:
- lang: eng
  text: "Automatic transcription of meetings requires handling of overlapped speech,
    which calls for continuous speech separation (CSS) systems. The uPIT criterion
    was proposed for utterance-level separation with neural networks and introduces
    the constraint that the total number of speakers must not exceed the number of
    output channels. When processing meeting-like data in a segment-wise manner, i.e.,
    by separating overlapping segments independently and stitching adjacent segments
    to continuous output streams, this constraint has to be fulfilled for any segment.
    In this contribution, we show that this constraint can be significantly relaxed.
    We propose a novel graph-based PIT criterion, which casts the assignment of utterances
    to output channels in a graph coloring problem. It only requires that the number
    of concurrently active speakers must not exceed the number of output channels.
    As a consequence, the system can process an arbitrary number of speakers and arbitrarily
    long segments and thus can handle more diverse scenarios.\r\nFurther, the stitching
    algorithm for obtaining a consistent output order in neighboring segments is of
    less importance and can even be eliminated completely, not the least reducing
    the computational effort. Experiments on meeting-style WSJ data show improvements
    in recognition performance over using the uPIT criterion. "
author:
- first_name: Thilo
  full_name: von Neumann, Thilo
  id: '49870'
  last_name: von Neumann
  orcid: https://orcid.org/0000-0002-7717-8670
- first_name: Keisuke
  full_name: Kinoshita, Keisuke
  last_name: Kinoshita
- first_name: Christoph
  full_name: Boeddeker, Christoph
  id: '40767'
  last_name: Boeddeker
- first_name: Marc
  full_name: Delcroix, Marc
  last_name: Delcroix
- first_name: Reinhold
  full_name: Haeb-Umbach, Reinhold
  id: '242'
  last_name: Haeb-Umbach
citation:
  ama: 'von Neumann T, Kinoshita K, Boeddeker C, Delcroix M, Haeb-Umbach R. Graph-PIT:
    Generalized Permutation Invariant Training for Continuous Separation of Arbitrary
    Numbers of Speakers. In: <i>Interspeech 2021</i>. ; 2021. doi:<a href="https://doi.org/10.21437/interspeech.2021-1177">10.21437/interspeech.2021-1177</a>'
  apa: 'von Neumann, T., Kinoshita, K., Boeddeker, C., Delcroix, M., &#38; Haeb-Umbach,
    R. (2021). Graph-PIT: Generalized Permutation Invariant Training for Continuous
    Separation of Arbitrary Numbers of Speakers. <i>Interspeech 2021</i>. Interspeech.
    <a href="https://doi.org/10.21437/interspeech.2021-1177">https://doi.org/10.21437/interspeech.2021-1177</a>'
  bibtex: '@inproceedings{von Neumann_Kinoshita_Boeddeker_Delcroix_Haeb-Umbach_2021,
    title={Graph-PIT: Generalized Permutation Invariant Training for Continuous Separation
    of Arbitrary Numbers of Speakers}, DOI={<a href="https://doi.org/10.21437/interspeech.2021-1177">10.21437/interspeech.2021-1177</a>},
    booktitle={Interspeech 2021}, author={von Neumann, Thilo and Kinoshita, Keisuke
    and Boeddeker, Christoph and Delcroix, Marc and Haeb-Umbach, Reinhold}, year={2021}
    }'
  chicago: 'Neumann, Thilo von, Keisuke Kinoshita, Christoph Boeddeker, Marc Delcroix,
    and Reinhold Haeb-Umbach. “Graph-PIT: Generalized Permutation Invariant Training
    for Continuous Separation of Arbitrary Numbers of Speakers.” In <i>Interspeech
    2021</i>, 2021. <a href="https://doi.org/10.21437/interspeech.2021-1177">https://doi.org/10.21437/interspeech.2021-1177</a>.'
  ieee: 'T. von Neumann, K. Kinoshita, C. Boeddeker, M. Delcroix, and R. Haeb-Umbach,
    “Graph-PIT: Generalized Permutation Invariant Training for Continuous Separation
    of Arbitrary Numbers of Speakers,” presented at the Interspeech, 2021, doi: <a
    href="https://doi.org/10.21437/interspeech.2021-1177">10.21437/interspeech.2021-1177</a>.'
  mla: 'von Neumann, Thilo, et al. “Graph-PIT: Generalized Permutation Invariant Training
    for Continuous Separation of Arbitrary Numbers of Speakers.” <i>Interspeech 2021</i>,
    2021, doi:<a href="https://doi.org/10.21437/interspeech.2021-1177">10.21437/interspeech.2021-1177</a>.'
  short: 'T. von Neumann, K. Kinoshita, C. Boeddeker, M. Delcroix, R. Haeb-Umbach,
    in: Interspeech 2021, 2021.'
conference:
  name: Interspeech
date_created: 2021-10-25T08:50:01Z
date_updated: 2023-11-15T12:14:40Z
ddc:
- '000'
department:
- _id: '54'
doi: 10.21437/interspeech.2021-1177
file:
- access_level: open_access
  content_type: video/mp4
  creator: tvn
  date_created: 2021-12-06T10:39:13Z
  date_updated: 2021-12-06T10:48:30Z
  file_id: '28327'
  file_name: Interspeech 2021 voiceover-002-compressed.mp4
  file_size: 9550220
  relation: supplementary_material
  title: Video for INTERSPEECH 2021
- access_level: open_access
  content_type: application/vnd.openxmlformats-officedocument.presentationml.presentation
  creator: tvn
  date_created: 2021-12-06T10:47:01Z
  date_updated: 2021-12-06T10:47:01Z
  file_id: '28328'
  file_name: Graph-PIT-poster-presentation.pptx
  file_size: 1337297
  relation: slides
  title: Slides from INTERSPEECH 2021
- access_level: open_access
  content_type: application/pdf
  creator: tvn
  date_created: 2021-12-06T10:48:21Z
  date_updated: 2021-12-06T10:48:21Z
  file_id: '28329'
  file_name: INTERSPEECH2021_Graph_PIT.pdf
  file_size: 226589
  relation: main_file
file_date_updated: 2021-12-06T10:48:30Z
has_accepted_license: '1'
keyword:
- Continuous speech separation
- automatic speech recognition
- overlapped speech
- permutation invariant training
language:
- iso: eng
oa: '1'
project:
- _id: '52'
  name: 'PC2: Computing Resources Provided by the Paderborn Center for Parallel Computing'
publication: Interspeech 2021
publication_status: published
quality_controlled: '1'
related_material:
  link:
  - relation: software
    url: https://github.com/fgnt/graph_pit
status: public
title: 'Graph-PIT: Generalized Permutation Invariant Training for Continuous Separation
  of Arbitrary Numbers of Speakers'
type: conference
user_id: '49870'
year: '2021'
...