This paper presents a machine learning method, Gaussian Mixture Hidden Markov Model
(GMM-HMM), for device-free activity recognition using WiFi channel state information (CSI) …

Automatic speech recognition is the computer driven conversion of spoken language into its
corresponding text format. Hidden Markov Models (HMMs) are widely used statistical …

Phoneme recognition is an essential step in the development of a speech recognition
system (SRS), as phonemes are fundamental building blocks in a spoken language. This …

Speech is the standard vocalized communication media. Speech is one of the comfortable
way for humans to communicate with each other. Similarly, speech recognition system is …

This paper aims to build an automatic speech recognition system (ASR) to recognize
Kannada words spoken continuously, using an open source speech recognition tool, HTK …

This paper describes a comparative study of continuous live speech recognition for selected
commonly used words and phrase in the Kannada language using the HTK Toolkit, Julia …

Automatic phoneme boundary detection is a key problem in speech processing and
applications. The accurate phoneme segmentation in continuous speech contributes to the …

With the rapid development of the information age, the main body of public opinion
information is no longer just structured data such as text and numbers, but the proportion of …

Aiming at the problems of difficulty in extracting key features and low prediction accuracy of
traditional convolutional neural networks in Chinese speech recognition, we analyze the …

The Recurrent Neural Network Transducer (RNN-T) extends Connectionist Temporal
Classification (CTC) by jointly modeling both input-output and output-output dependencies …