Fully automatic speaker separation system, with automatic enrolling of recurrent speakers

Raphael Cohen; Orgad Keller; Jason Levy; Amit Ashkenazi; Russell Levy; Micha Breakstone

doi:10.21437/Interspeech.2018-3034

Fully automatic speaker separation system, with automatic enrolling of recurrent speakers

Raphael Cohen, Orgad Keller, Jason Levy, Amit Ashkenazi, Russell Levy, Micha Breakstone

Chorus.ai

Research output: Contribution to journal › Conference article › peer-review

Abstract

We present a system to enable speaker separation and identification, designed to operate without requiring any effort from the end-user. In the system, single channel conversations are transformed into i-vectors, clustered into speakers and matched to a database of known speakers. Enrollment is automatic and a voice print is constructed for the recording user, taking advantage of the meta-data identifying that user's conversations. Further information is used when available from other information sources such as video and the ASR transcribed content to identify speakers. We describe the system architecture, novel unsupervised enrollment algorithm and describe the difficulties encountered in solving this problem.

Original language	English
Pages (from-to)	1964-1965
Number of pages	2
Journal	Proceedings of the Annual Conference of the International Speech Communication Association, INTERSPEECH
Volume	2018-September
DOIs	https://doi.org/10.21437/Interspeech.2018-3034
State	Published - 2018
Externally published	Yes
Event	19th Annual Conference of the International Speech Communication, INTERSPEECH 2018 - Hyderabad, India Duration: 2 Sep 2018 → 6 Sep 2018

Bibliographical note

Publisher Copyright:
© 2018 International Speech Communication Association. All rights reserved.

Keywords

Diarization
Speaker separation
Speech recognition

Access to Document

10.21437/Interspeech.2018-3034

Cite this

@article{8664917cbd8549d38614d4a2eae6e48a,

title = "Fully automatic speaker separation system, with automatic enrolling of recurrent speakers",

abstract = "We present a system to enable speaker separation and identification, designed to operate without requiring any effort from the end-user. In the system, single channel conversations are transformed into i-vectors, clustered into speakers and matched to a database of known speakers. Enrollment is automatic and a voice print is constructed for the recording user, taking advantage of the meta-data identifying that user's conversations. Further information is used when available from other information sources such as video and the ASR transcribed content to identify speakers. We describe the system architecture, novel unsupervised enrollment algorithm and describe the difficulties encountered in solving this problem.",

keywords = "Diarization, Speaker separation, Speech recognition",

author = "Raphael Cohen and Orgad Keller and Jason Levy and Amit Ashkenazi and Russell Levy and Micha Breakstone",

note = "Publisher Copyright: {\textcopyright} 2018 International Speech Communication Association. All rights reserved.; 19th Annual Conference of the International Speech Communication, INTERSPEECH 2018 ; Conference date: 02-09-2018 Through 06-09-2018",

year = "2018",

doi = "10.21437/Interspeech.2018-3034",

language = "אנגלית",

volume = "2018-September",

pages = "1964--1965",

journal = "Proceedings of the Annual Conference of the International Speech Communication Association, INTERSPEECH",

issn = "2308-457X",

publisher = "International Speech Communication Association",

}

Fully automatic speaker separation system, with automatic enrolling of recurrent speakers. / Cohen, Raphael; Keller, Orgad; Levy, Jason et al.
In: Proceedings of the Annual Conference of the International Speech Communication Association, INTERSPEECH, Vol. 2018-September, 2018, p. 1964-1965.

Research output: Contribution to journal › Conference article › peer-review

TY - JOUR

T1 - Fully automatic speaker separation system, with automatic enrolling of recurrent speakers

AU - Cohen, Raphael

AU - Keller, Orgad

AU - Levy, Jason

AU - Ashkenazi, Amit

AU - Levy, Russell

AU - Breakstone, Micha

PY - 2018

Y1 - 2018

N2 - We present a system to enable speaker separation and identification, designed to operate without requiring any effort from the end-user. In the system, single channel conversations are transformed into i-vectors, clustered into speakers and matched to a database of known speakers. Enrollment is automatic and a voice print is constructed for the recording user, taking advantage of the meta-data identifying that user's conversations. Further information is used when available from other information sources such as video and the ASR transcribed content to identify speakers. We describe the system architecture, novel unsupervised enrollment algorithm and describe the difficulties encountered in solving this problem.

AB - We present a system to enable speaker separation and identification, designed to operate without requiring any effort from the end-user. In the system, single channel conversations are transformed into i-vectors, clustered into speakers and matched to a database of known speakers. Enrollment is automatic and a voice print is constructed for the recording user, taking advantage of the meta-data identifying that user's conversations. Further information is used when available from other information sources such as video and the ASR transcribed content to identify speakers. We describe the system architecture, novel unsupervised enrollment algorithm and describe the difficulties encountered in solving this problem.

KW - Diarization

KW - Speaker separation

KW - Speech recognition

UR - https://www.scopus.com/pages/publications/85054993572

U2 - 10.21437/Interspeech.2018-3034

DO - 10.21437/Interspeech.2018-3034

M3 - ???researchoutput.researchoutputtypes.contributiontojournal.conferencearticle???

AN - SCOPUS:85054993572

SN - 2308-457X

VL - 2018-September

SP - 1964

EP - 1965

JO - Proceedings of the Annual Conference of the International Speech Communication Association, INTERSPEECH

JF - Proceedings of the Annual Conference of the International Speech Communication Association, INTERSPEECH

T2 - 19th Annual Conference of the International Speech Communication, INTERSPEECH 2018

Y2 - 2 September 2018 through 6 September 2018

ER -

Fully automatic speaker separation system, with automatic enrolling of recurrent speakers

Abstract

Bibliographical note

Keywords

Access to Document

Other files and links

Fingerprint

Cite this