Towards improving Disfluency Detection from Speech using Shifted Delta Cepstral Coefficients-Reference-Cited by-同舟云学术

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Towards improving Disfluency Detection from Speech using Shifted Delta Cepstral Coefficients

Published:2022-08-04 Issue: Volume: Page:
ISSN:
Container-title:Proceedings of the 2022 Fourteenth International Conference on Contemporary Computing
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Author:

Mehrotra Utkarsh¹,Garg Sparsh¹,Gurugubelli Krishna¹,Vuppala Anil Kumar¹

Affiliation:

1. IIIT Hyderabad, India

Publisher

ACM

Link

https://dl.acm.org/doi/pdf/10.1145/3549206.3549269

Reference35 articles.

1. Classification of speech dysfluencies with MFCC and LPCC features

2. A Lightly Supervised Approach to Detect Stuttering in Children's Speech

3. KNRK Raju Alluri Sivanand Achanta Sudarsana Reddy Kadiri Suryakanth V Gangashetty and Anil Kumar Vuppala. 2017. Detection of Replay Attacks Using Single Frequency Filtering Cepstral Coefficients.. In Interspeech. 2596–2600. KNRK Raju Alluri Sivanand Achanta Sudarsana Reddy Kadiri Suryakanth V Gangashetty and Anil Kumar Vuppala. 2017. Detection of Replay Attacks Using Single Frequency Filtering Cepstral Coefficients.. In Interspeech. 2596–2600.

4. Normative Disfluency Data for Early Childhood Stuttering

5. Single Frequency Filtering Approach for Discriminating Speech and Nonspeech

Cited by 1 articles. 订阅此论文施引文献订阅此论文施引文献，注册后可以免费订阅5篇论文的施引文献，订阅后可以查看论文全部施引文献

1. StutterNet: Stuttering Disfluencies Detection in Synthetic Speech Signals via Mel Frequency Cepstral Coefficients Features Using Deep Learning;IEEE Access;2024

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