Varying microphone patterns for meeting speech segmentation using spatial audio cues

被引:0
|
作者
Cheng, Eva [1 ]
Burnett, Ian [1 ]
Ritz, Christian [1 ]
机构
[1] Univ Wollongong, Whisper Labs, Sch Elect Comp & Telecommun Engn, Wollongong, NSW 2522, Australia
关键词
spatial audio cues; meeting audio analysis; microphone arrays;
D O I
暂无
中图分类号
TP18 [人工智能理论];
学科分类号
081104 ; 0812 ; 0835 ; 1405 ;
摘要
Meetings, common to many business environments, generally involve stationary participants. Thus, participant location information can be used to segment meeting speech recordings into each speaker's 'turn'. The authors' previous work proposed the use of spatial audio cues to represent the speaker locations. This paper studies the validity of using spatial audio cues for meeting speech segmentation by investigating the effect of varying microphone pattern on the spatial cues. Experiments conducted on recordings of a real acoustic environment indicate that the relationship between speaker location and spatial audio cues strongly depends on the microphone pattern.
引用
收藏
页码:221 / +
页数:2
相关论文
共 49 条
  • [21] LANGUAGE-RESOURCE INDEPENDENT SPEECH SEGMENTATION USING CUES FROM A SPECTROGRAM IMAGE
    Leow, Su Jun
    Chng, Eng Siong
    Lee, Chin-Hui
    [J]. 2015 IEEE INTERNATIONAL CONFERENCE ON ACOUSTICS, SPEECH, AND SIGNAL PROCESSING (ICASSP), 2015, : 5813 - 5817
  • [22] Spatial Audio Signal Processing Technology Using Multi-Channel 3D Microphone
    Lee, Taejin
    Kang, Kyeongok
    [J]. JOURNAL OF THE ACOUSTICAL SOCIETY OF KOREA, 2005, 24 (02): : 68 - 77
  • [23] Unsupervised Fuzzy Inference System for Speech Emotion Recognition using audio and text cues (Workshop Paper)
    Vashishtha, Srishti
    Susan, Seba
    [J]. 2020 IEEE SIXTH INTERNATIONAL CONFERENCE ON MULTIMEDIA BIG DATA (BIGMM 2020), 2020, : 394 - 403
  • [24] Automatic speech detection and segmentation of air traffic control audio using the parametric trajectory model
    Galligan, Shane
    [J]. 2007 IEEE AEROSPACE CONFERENCE, VOLS 1-9, 2007, : 1574 - 1591
  • [25] Bilateral and bimodal cochlear implant listeners can segregate competing speech using talker sex cues, but not spatial cues
    Willis, Shelby
    Xu, Kevin
    Thomas, Mathew
    Gopen, Quinton
    Ishiyama, Akira
    Galvin, John J., III
    Fu, Qian-Jie
    [J]. JASA EXPRESS LETTERS, 2021, 1 (01):
  • [26] Audio Classification Using Dominant Spatial Patterns in Time-Frequency Space
    Molla, Md. Khademul Islam
    Hirose, Keikichi
    [J]. 14TH ANNUAL CONFERENCE OF THE INTERNATIONAL SPEECH COMMUNICATION ASSOCIATION (INTERSPEECH 2013), VOLS 1-5, 2013, : 2914 - 2918
  • [27] Detecting Audio Adversarial Examples in Automatic Speech Recognition Systems Using Decision Boundary Patterns
    Zong, Wei
    Chow, Yang-Wai
    Susilo, Willy
    Kim, Jongkil
    Le, Ngoc Thuy
    [J]. JOURNAL OF IMAGING, 2022, 8 (12)
  • [28] Microphone array post-filter using incremental bayes learning to track the spatial distributions of speech and noise
    Seltzer, Michael L.
    Tashev, Ivan
    Acero, Alex
    [J]. 2007 IEEE INTERNATIONAL CONFERENCE ON ACOUSTICS, SPEECH, AND SIGNAL PROCESSING, VOL I, PTS 1-3, PROCEEDINGS, 2007, : 29 - 32
  • [29] Discriminating Divergent/Convergent Phases of Meeting Using Non-Verbal Speech Patterns
    Ichino, Junko
    [J]. ECSCW 2011: PROCEEDINGS OF THE 12TH EUROPEAN CONFERENCE ON COMPUTER SUPPORTED COOPERATIVE WORK, 2011, : 153 - 172
  • [30] Speech retrieval from unsegmented finnish audio using statistical morpheme-like units for segmentation, recognition, and retrieval
    Turunen, Ville T.
    Kurimo, Mikko
    [J]. ACM Transactions on Speech and Language Processing, 2011, 8 (01):