Detail výsledku

Multitask Speech Recognition and Speaker Change Detection for Unknown Number of Speakers

KUMAR, S.; MADIKERI, S.; NIGMATULINA, I.; VILLATORO-TELLO, E.; MOTLÍČEK, P.; PANDIA, K.; DUBAGUNTA, P.; GANAPATHIRAJU, A. Multitask Speech Recognition and Speaker Change Detection for Unknown Number of Speakers. ICASSP 2024 - 2024 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP). Seoul: IEEE Signal Processing Society, 2024. p. 12592-12596. ISBN: 979-8-3503-4485-1.
Typ
článek ve sborníku konference
Jazyk
anglicky
Autoři
KUMAR, S.
Madikeri Srikanth, FIT (FIT)
NIGMATULINA, I.
VILLATORO-TELLO, E.
Motlíček Petr, doc. Ing., Ph.D., UPGM (FIT)
PANDIA, K.
DUBAGUNTA, P.
GANAPATHIRAJU, A.
Abstrakt

Traditionally, automatic speech recognition (ASR) and speaker change detection (SCD) systems have been independently trained to generate comprehensive transcripts accompanied by speaker turns. Recently, joint training of ASR and SCD systems, by inserting speaker turn tokens in the ASR training text, has been shown to be successful. In this work, we present a multitask alternative to the joint training approach. Results obtained on the mix-headset audios of AMI corpus show that the proposed multitask training yields an absolute improvement of 1.8% in coverage and purity based F1 score on SCD task without ASR degradation. We also examine the trade-offs between the ASR and SCD performance when trained using multitask criteria. Additionally, we validate the speaker change information in the embedding spaces obtained after different transformer layers of a self-supervised pre-trained model, such as XLSR-53, by integrating an SCD classifier at the output of specific transformer layers. Results reveal that the use of different embedding spaces from XLSR-53 model for multitask ASR and SCD is advantageous.1

Klíčová slova

speaker change detection, speaker turn detection, speech recognition, multitask learning, F1 score

URL
Rok
2024
Strany
12592–12596
Sborník
ICASSP 2024 - 2024 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP)
Konference
2024 IEEE International Conference on Acoustics, Speech and Signal Processing IEEE
ISBN
979-8-3503-4485-1
Vydavatel
IEEE Signal Processing Society
Místo
Seoul
DOI
BibTeX
@inproceedings{BUT196785,
  author="KUMAR, S. and MADIKERI, S. and NIGMATULINA, I. and VILLATORO-TELLO, E. and MOTLÍČEK, P. and PANDIA, K. and DUBAGUNTA, P. and GANAPATHIRAJU, A.",
  title="Multitask Speech Recognition and Speaker Change Detection for Unknown Number of Speakers",
  booktitle="ICASSP 2024 - 2024 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP)",
  year="2024",
  pages="12592--12596",
  publisher="IEEE Signal Processing Society",
  address="Seoul",
  doi="10.1109/ICASSP48485.2024.10446130",
  isbn="979-8-3503-4485-1",
  url="https://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=10446130"
}
Soubory
Projekty
Soudobé metody zpracování, analýzy a zobrazování multimediálních a 3D dat, VUT, Vnitřní projekty VUT, FIT-S-23-8278, zahájení: 2023-03-01, ukončení: 2026-02-28, řešení
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Pracoviště
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