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Online Speaker Diarization Using Optimized SE-ResNet Architecture

The result's identifiers

  • Result code in IS VaVaI

    <a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F46747885%3A24220%2F23%3A00011570" target="_blank" >RIV/46747885:24220/23:00011570 - isvavai.cz</a>

  • Result on the web

    <a href="https://dl.acm.org/doi/10.1007/978-3-031-40498-6_16" target="_blank" >https://dl.acm.org/doi/10.1007/978-3-031-40498-6_16</a>

  • DOI - Digital Object Identifier

    <a href="http://dx.doi.org/10.1007/978-3-031-40498-6_16" target="_blank" >10.1007/978-3-031-40498-6_16</a>

Alternative languages

  • Result language

    angličtina

  • Original language name

    Online Speaker Diarization Using Optimized SE-ResNet Architecture

  • Original language description

    A new approach to speaker diarization (SD) suitable for real-time processing of streamed data is presented in this work. It utilizes a modified residual network with squeeze-and-excitation blocks (SE-ResNet-34) for extraction of speaker embeddings. These speaker embeddings are calculated in an optimized way by using cached buffers and are subsequently used for voice activity detection (VAD) as well as for block-online k-means clustering with a look-ahead mechanism. All these processing steps are first evaluated separately on a development set compiled from recordings of Czech broadcast programs. The whole scheme is then compared to an offline reference approach on various speech databases that are publicly available and include data in various languages. On this data, our method yields results similar to the reference system while operating on a CPU with a low real-time factor (RTF) below 0.1 and a latency of around 5.5 s.

  • Czech name

  • Czech description

Classification

  • Type

    D - Article in proceedings

  • CEP classification

  • OECD FORD branch

    10201 - Computer sciences, information science, bioinformathics (hardware development to be 2.2, social aspect to be 5.8)

Result continuities

  • Project

    <a href="/en/project/TO01000027" target="_blank" >TO01000027: NORDTRANS - Technology for automatic speech transcription in selected Nordic languages</a><br>

  • Continuities

    P - Projekt vyzkumu a vyvoje financovany z verejnych zdroju (s odkazem do CEP)<br>S - Specificky vyzkum na vysokych skolach

Others

  • Publication year

    2023

  • Confidentiality

    S - Úplné a pravdivé údaje o projektu nepodléhají ochraně podle zvláštních právních předpisů

Data specific for result type

  • Article name in the collection

    Lecture Notes in Computer Science

  • ISBN

    978-303140497-9

  • ISSN

    03029743

  • e-ISSN

  • Number of pages

    12

  • Pages from-to

    176-187

  • Publisher name

    Springer

  • Place of publication

    Německo

  • Event location

    Plzeň, ČR

  • Event date

    Jan 1, 2023

  • Type of event by nationality

    WRD - Celosvětová akce

  • UT code for WoS article