article

Automatic speech recognition and speech variability: A review

Authors:

Stephane Dupont,

C. WellekensAuthors Info & Claims

Speech Communication, Volume 49, Issue 10-11

Pages 763 - 786

https://doi.org/10.1016/j.specom.2007.02.006

Published: 01 October 2007 Publication History

Abstract

Major progress is being recorded regularly on both the technology and exploitation of automatic speech recognition (ASR) and spoken language systems. However, there are still technological barriers to flexible solutions and user satisfaction under some circumstances. This is related to several factors, such as the sensitivity to the environment (background noise), or the weak representation of grammatical and semantic knowledge. Current research is also emphasizing deficiencies in dealing with variation naturally present in speech. For instance, the lack of robustness to foreign accents precludes the use by specific populations. Also, some applications, like directory assistance, particularly stress the core recognition technology due to the very high active vocabulary (application perplexity). There are actually many factors affecting the speech realization: regional, sociolinguistic, or related to the environment or the speaker herself. These create a wide range of variations that may not be modeled correctly (speaker, gender, speaking rate, vocal effort, regional accent, speaking style, non-stationarity, etc.), especially when resources for system training are scarce. This paper outlines current advances related to these topics.

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Cited By

Petsolari MIbrahim SSlovak P(2024)Socio-technical Imaginaries: Envisioning and Understanding AI Parenting Supports through Design FictionProceedings of the 2024 CHI Conference on Human Factors in Computing Systems10.1145/3613904.3642619(1-27)Online publication date: 11-May-2024
https://dl.acm.org/doi/10.1145/3613904.3642619
Shanthamallappa M(2024)Robust Speech Enhancement Using Dabauchies Wavelet Based Adaptive Wavelet Thresholding for the Development of Robust Automatic Speech Recognition: A Comprehensive ReviewWireless Personal Communications: An International Journal10.1007/s11277-024-11448-x137:4(2085-2119)Online publication date: 1-Aug-2024
https://dl.acm.org/doi/10.1007/s11277-024-11448-x
Shabber SBansal M(2024)Temporal feature-based approaches for enhancing phoneme boundary detection and masking in speechInternational Journal of Speech Technology10.1007/s10772-024-10117-527:2(425-436)Online publication date: 1-Jun-2024
https://dl.acm.org/doi/10.1007/s10772-024-10117-5
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Index Terms

Automatic speech recognition and speech variability: A review
1. Computing methodologies
  1. Artificial intelligence
    1. Natural language processing
      1. Speech recognition
2. Hardware
  1. Communication hardware, interfaces and storage
    1. Signal processing systems

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cover image Speech Communication

Speech Communication Volume 49, Issue 10-11

October, 2007

101 pages

ISSN:0167-6393

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Copyright © Elsevier B.V. © 2007.

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Elsevier Science Publishers B. V.

Netherlands

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Published: 01 October 2007

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Cited By

Petsolari MIbrahim SSlovak P(2024)Socio-technical Imaginaries: Envisioning and Understanding AI Parenting Supports through Design FictionProceedings of the 2024 CHI Conference on Human Factors in Computing Systems10.1145/3613904.3642619(1-27)Online publication date: 11-May-2024
https://dl.acm.org/doi/10.1145/3613904.3642619
Shanthamallappa M(2024)Robust Speech Enhancement Using Dabauchies Wavelet Based Adaptive Wavelet Thresholding for the Development of Robust Automatic Speech Recognition: A Comprehensive ReviewWireless Personal Communications: An International Journal10.1007/s11277-024-11448-x137:4(2085-2119)Online publication date: 1-Aug-2024
https://dl.acm.org/doi/10.1007/s11277-024-11448-x
Shabber SBansal M(2024)Temporal feature-based approaches for enhancing phoneme boundary detection and masking in speechInternational Journal of Speech Technology10.1007/s10772-024-10117-527:2(425-436)Online publication date: 1-Jun-2024
https://dl.acm.org/doi/10.1007/s10772-024-10117-5
Nguyen Doan THuynh SNguyen ALe APhan Thi Thuy AHuynh DNguyen B(2024)Vietnamese Automatic Speech Recognition for Financial Conversation DataIntelligent Information and Database Systems10.1007/978-981-97-4985-0_29(372-383)Online publication date: 15-Apr-2024
https://dl.acm.org/doi/10.1007/978-981-97-4985-0_29
Pande AMishra DNachenahalli Bhuthegowda B(2024)NAO vs. Pepper: Speech Recognition Performance AssessmentHuman-Computer Interaction10.1007/978-3-031-60412-6_12(156-167)Online publication date: 29-Jun-2024
https://dl.acm.org/doi/10.1007/978-3-031-60412-6_12
Venkata Lakshmi SSujatha KJanet J(2023)A hybrid discriminant fuzzy DNN with enhanced modularity bat algorithm for speech recognitionJournal of Intelligent & Fuzzy Systems: Applications in Engineering and Technology10.3233/JIFS-21294544:3(4079-4091)Online publication date: 1-Jan-2023
https://dl.acm.org/doi/10.3233/JIFS-212945
Zhao RYu JZhao HNgai E(2023)Radio2TextProceedings of the ACM on Interactive, Mobile, Wearable and Ubiquitous Technologies10.1145/36108737:3(1-28)Online publication date: 27-Sep-2023
https://dl.acm.org/doi/10.1145/3610873
Heck MJeong JBecker C(2023)Evaluating the Potential of Caption Activation to Mitigate Confusion Inferred from Facial Gestures in Virtual MeetingsProceedings of the 25th International Conference on Multimodal Interaction10.1145/3577190.3614142(243-252)Online publication date: 9-Oct-2023
https://dl.acm.org/doi/10.1145/3577190.3614142
Kuhn KKersken VZimmermann G(2023)Accuracy of AI-generated Captions With Collaborative Manual Corrections in Real-TimeExtended Abstracts of the 2023 CHI Conference on Human Factors in Computing Systems10.1145/3544549.3585724(1-7)Online publication date: 19-Apr-2023
https://dl.acm.org/doi/10.1145/3544549.3585724
Li DChen TZadikian ATung AChilton L(2023)Improving Automatic Summarization for Browsing Longform Spoken DialogProceedings of the 2023 CHI Conference on Human Factors in Computing Systems10.1145/3544548.3581339(1-20)Online publication date: 19-Apr-2023
https://dl.acm.org/doi/10.1145/3544548.3581339
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