Kannada Continuous Speech Recognition Using Deep Learning

被引：0

作者：

Paul, Shubhojeet ^{[1
]}

Bhattacharjee, Vandana ^{[1
]}

Saha, Sujan Kumar ^{[2
]}

机构：

[1] Birla Inst Technol, Ranchi, Mesra, India

[2] Natl Inst Technol, Durgapur, India

来源：

ADVANCED NETWORK TECHNOLOGIES AND INTELLIGENT COMPUTING, ANTIC 2023, PT IV | 2024年 / 2093卷

关键词：

Kannada; Automatic Speech Recognition; Continuous Speech Recognition; Deep Learning;

D O I：

10.1007/978-3-031-64067-4_17

中图分类号：

TP18 [人工智能理论];

学科分类号：

081104 ; 0812 ; 0835 ; 1405 ;

摘要：

Automatic Speech Recognition (ASR) is a prevalent approach for attaining human-machine interaction by enabling machines to transcribe speech data. We propose a Continuous Speech Recognition model in the Kannada language using deep learning techniques such as Convolutional Neural Networks (CNN) and Bidirectional Gated Recurrent Units (Bi-GRU). The model was trained and validated using 100 and 20 h of data, respectively. The experiment has generated encouraging results with a Character Error Rate (CER) of 15.62% and a Word Error Rate of 34.47% (WER).

引用

页码：258 / 269

页数：12

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