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This paper presents a novel method to control the number of crossvalidation repetitions in sequential forward feature selection algorithms. The criterion for selecting a feature is the probability of correct classification achieved by the Bayes classifier when the class feature probability density function is modeled by a single multivariate Gaussian density. Let the probability of correct classification...
In this paper, we present a framework for predicting and correcting classification decision errors based on modality reliability measures in a multimodal biometric system. In our experiments we use face and speech experts based on a recently proposed framework which uses Bayesian networks. The expert decisions and the accompanying information on their reliability are combined in a decision module...
Part Of Speech tagging (POS) is the basic process for almost all natural language processing (NLP) applications. The typical methods for combining different taggers, the program doing POS tagging, are voting or stacking techniques. We propose here a Master-Slaves Technique, which can combine Hidden Markov Model (HMM) tagger as master and any number of other taggers of any type as slaves. We describe...
Speech-based test is a one of the best ways to train students' level of proficiency. However, in e-learning it is difficult for students to maintain their concentration when speaking to a monitor. We propose speech-based online test system employing a human-likely embodied graphical agent as a listener. The developed system consists of three modules, user recognition, agent's non-verbal behavior realization,...
This paper investigates the use of MultiDimensional Voice Program (MDVP) parameters to automatically detect voice pathology in Arabic voice pathology database (AVPD). MDVP parameters are very popular among the physician / clinician to detect voice pathology; however, MDVP is a commercial software. AVPD is a newly developed speech database designed to suit a wide range of experiments in the field of...
The aim of clustering is to discover the clusters based on the similarity features of objects. The present algorithm of visual access tendency (VAT) can access an exact number of clusters by its VAT image. The VAT image displays the squared shaped dark blocks along the diagonal; number of cluster information is accessed by counting the number of obtaining square blocks. Other extended versions are...
In the storyteller speech, pauses plays a significant role in introducing suspense and climax. Pauses are used to emphasize keywords, emotion-salient words and separate the phrases in the utterance. The objective of this work is to predict the position and duration of the pauses in the synthesized speech from the text-to-speech system. We analyzed the pause patterns in storyteller speech and classified...
A whispered speech resembles an unvoiced speech due to the lack of vocal fold vibration unlike the neutral speech. Since information about the gender of a speaker typically lies in the pitch resulted from the vocal fold vibration (or source signal), identifying gender from the whispered speech is more challenging compared to that from the neutral speech. In the absence of the pitch, we study the use...
This paper presents a speaker based Language Independent Isolated Speech Recognition System (LIISRS). The most popular feature extraction technique Mel Frequency Cepstral Coefficients (MFCC) is used for training the system. Representative specific features are identified using K-Means algorithm. Distortion measure is calculated using Euclidian distance function. Pitch contour characteristics are used...
This paper motivates the use of combination of mel frequency cepstral coefficients (MFCC) and its delta derivatives (DMFCC and DDMFCC) calculated using mel spaced Gaussian filter banks for text independent speaker recognition. MFCC modeled on the human auditory system shows robustness against noise and session changes and hence has become synonymous with speaker recognition. Our main aim is to test...
In this paper, we propose a two-stage phone recognition system using articulatory and spectral features. In the first stage, articulatory features are predicted from spectral features using FeedForward Neural Networks (FFNNs). In the second stage, phone recognition is carried out using the predicted articulatory features and spectral features together. FFNNs and Hidden Markov Models are explored for...
The goal of this work is to improve phone recognition accuracy using combination of source and system features. As speech is produced by exciting time varying vocal tract system with time varying excitation, we want to explore both source and system components of speech production system for phone recognition. The excitation source information is derived by processing linear prediction residual of...
Microblogging sites such as Twitter and Weibo are increasingly being used to enhance situational awareness during various natural and man-made disaster events such as floods, earthquakes, and bomb blasts. During any such event, thousands of microblogs (tweets) are posted in short intervals of time. Typically, only a small fraction of these tweets contribute to situational awareness, while the majority...
A switch-to-speech interface can provide a means of interactive communication as a support system for people with disabilities with voluntary movements. Any motion of a part of the body, such as eye movements, can be used for the switch input. The number of possible switch operations varies from person to person, but the bandwidth is generally quite limited. Therefore, efficient input protocols are...
An electrolarynx is a device that artificially generates excitation sounds to produce electrolaryngeal (EL) speech. Although proficient laryngectomees can produce intelligible EL speech by using this device, it sounds quite unnatural due to the mechanical excitation. To address this issue, we have proposed several EL speech enhancement methods using statistical voice conversion and showed that statistical...
Unsupervised speaker adaptation of Deep Neural Network (DNN) is investigated for lecture transcription tasks, in which a single speaker gives a long speech and thus speaker adaptation is important. The proposed method selects similar speakers to the test data (test speaker) from the training database, which are used for retraining the baseline DNN. Several speaker characteristic features are defined...
This paper presents the technique for feature extraction to classify speech and music audio data. The combination of image processing and signal processing is used to classify audio data. There are three main steps. First, the audio data is segments and transformed to spectrogram image and then apply image processing methods to find the salient characteristics on the spectrogram image. The next step...
In order to overcome a problem existing in a classical automatic speech recognition (e.g. ambient noise and loss of privacy), Electromyography (EMG) from speech production muscles was used in place of a human speech signal. We aim to investigate the EMG speech recognition based on Thai language. The earlier work, we used five channels of the EMG from the facial and neck muscles to classify 11 Thai...
We proposed and evaluated an estimation method for the forced selection Japanese Diagnostic Rhyme Test (DRT). The proposed measure takes into account the forced selection manner of the DRT from a pair of rhyming words. The objective distance measure used here was based on the Articulation index Band Correlation (ABC), which showed favorable results for the English Modified Rhyme Test (MRT). The correlation...
Human computer interaction with the time has extended its branches to many different other fields like engineering, cognition, medical etc. Speech analysis has also become an important area of concern. People involved are using this mode for the interaction with the machines to bridge the gap between physical and digital world. Speech emotion recognition has become an integral subfield in the domain...
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