Pukhraj P. Shrishrimal

Indian Language Speech Database: A Review

is the most prominent and natural form of communication between humans. Human beings have long been motivated to create computer that can understand and talk like human. When the research tries to develop certain recognition system they require certain previously stored data i.e. database for respective recognition system. There are various speech databases available for European Language but very less for Indian Language. In this paper we discuss the various Speech Database developed in different Indian Languages for speech recognition system & Text to Speech System.

A Comparative Study of Feature Extraction Techniques for Speech Recognition System

The automatic recognition of speech means enabling a natural and easy mode of communication between human and machine. Speech processing has vast applications in voice dialing, telephone communication, call routing, domestic appliances control, Speech to Text conversion, Text to Speech conversion, lip synchronization, automation systems etc. Here we have discussed some mostly used feature extraction techniques like Mel frequency Cepstral Co-efficient (MFCC), Linear Predictive Coding (LPC) Analysis, Dynamic Time Wrapping (DTW), Relative Spectra Processing (RASTA) and Zero Crossings with Peak Amplitudes (ZCPA).Some parameters like RASTA and MFCC considers the nature of speech while it extracts the features, while LPC predicts the future features based on previous features.

A Review on Different Approaches for Speech Recognition System

This paper presents the basic idea of speech recognition, proposed types of speech recognition, issues in speech recognition, different useful approaches for feature extraction of the speech signal with its advantage and disadvantage and various pattern matching approaches for recognizing the speech of the different speaker. Now day’s research in speech recognition system is motivated for ASR system with a large vocabulary that supports speaker independent operations and continuous speech in different language.

Effect of Distance Measures on the Performance of Face Recognition Using Principal Component Analysis

We examined effect of distance measures on the performance of face recognition using Principal Component Analysis. We tested commonly used 4 distance measures: City block, Euclidean, Cosine and Mahalanobis. The study was done on 400 images from ORL face database. We achieved the best recognition performance using Cosine and City block distance measures. It was observed that fewer images need to be extracted for achieving 100% cumulative recognition using Cosine metrics than using any other distance measure. The performance of Mahalanobis distance measure was poor compared to other distance measures. Our results show the importance of using appropriate distance measure for face recognition.

Development of Isolated Marathi Words Emotional Speech Database

ABSTRACT The research work describes the procedure and the development of Isolated Marathi Emotional Speech Database. The database consists of samples, collected from 50 speakers including males and females who simulated the emotions producing by the Marathi utterances which are used in everyday communication and are interpretable in all applied emotions. The speech samples were enhanced by spectral subtraction method and distinguished by the various real life situations. The recorded speech samples were categorized in three basic categories i.e. Happy, Sad and Angry. General Terms development of isolated Marathi emotional speech database. Speech Signal Processing, Speech Recognition, Emotion Recognition, Spectral Subtraction, Emotional we have discussed the selection of emotion for the Speech Database. Keywords Section V describes the speech data collection; the recording Speech Databases, Emotion, Speech, Emotion Recognition, Human Computer Interaction.

Development of Isolated Numeric Speech Corpus for Swahili Language for Development of Automatic Speech Recognition System

ABSTRACT Speech corpus being the basic requirement for the development of Automatic speech recognition (ASR) system, it should be done with much accuracy in order to enhance the performance of the system. This paper describes the proposed procedure to abide while collecting the speech corpus of Swahili language from the native and non native speaker for the development of Automatic Speech Recognition system in Swahili language. General Terms Speech Database, Speech Recognition, Natural Language Processing, Human Computer Interaction Keywords Swahili, Swahili Text corpus, Phonetics, Text Corpus and Speech Corpus, Automatic Speech Recognition 1. INTRODUCTION Speech is the most prominent and natural form of communication between humans. Communication among the human being is dominated by spoken languages; therefore the researchers are trying to build the speech interfaces for computer [1]. Speech has potential of being used as a mode of interaction with computer. Human beings have long been motivated to create systems that can understand and talk like human. In this direction, researchers have tried to develop system for analysis and classification of the speech signals. Since, 1960s computer scientists have been researching ways and means to make computer record, interpret and understand human speech. Speech processing has become increasingly important in daily life, as the number of web enabled mobile phone users in rural as well as in urban area is increasing. Most of the researches efforts are in the field are of natural language processing (NLP) for African Language where Swahili is included and has majorly rooted in the rule based paradigm. The rule based approach has some merits as well as demerits. The merit of Swahili is in term of its design transparency and the demerits are that it’s highly language dependency and costly to develop as it typically involves a lot of manual effort of experts from Natural Language Processing field. unlike adaptations of the Arabic script for other languages, The system are decidedly competence based which is often tweaked and tuned towards a small sets of ideal sample words or sentences neglecting the real-world language technology application. In Language technologies for many African languages the researchers are getting tired of publication on real-world data or reports. Currently with the increased need of digital resource usage in the continent of Africa, there is a great need for more empirical approaches such as data driven and corpus based approach for language technologies. The main advantages of these approaches are: language impendence, development speed, robustness and empiricism. There is scarcity of sources in the sense that the digital text resources are few. The recent effort on the same is handled carefully with selected procedure for Swahili [2, 3]. For language technology applications such as speech recognition system, text-to-speech synthesis, machine aided translation and web related issues there is a great need for translation and usability of the Swahili language. There is a great need of work to be done in semantics and syntactic of Swahili language as the biggest online web Text resources which are available on Google, Yahoo and Wikipedia are not that correct. The major need is the extraction of information which enhances and refocuses on embarking on Swahili as a language, the corpus availability needs to be syntactically & semantically correct. This paper focuses on the procedure to be followed for the development of isolated numeric speech corpus. The information about Swahili language is described in the Section 2. Section 3 describes the Swahili text Corpus selected. Section 4 describes the procedure to be followed for developing the speech corpus. Section 5 describes the recording procedure to be followed. The Conclusion and the Future work are discussed in Section 6.

Granulation of financial time series for trend analysis and recognition

Time series in finance are characterized by upside and downside movements that can be or not part of a larger trend. Trends become more obvious when we look at data points as granules and we study the relationship between them. In this paper we discuss which role granulation can have in describing the behavior of time series. In particular we investigate granules obtained by means of Ruspini partitions and we provide some examples of application.

Face verification using scale invariant feature transform with template security

Biometrie is a reliable and convenient way for person authentication. Template security is a major concern in practical implementation of biometric system. This work proposes cryptosystem for face verification with fuzzy vault. Here, a secrete value k is locked using fuzzy vault with a set of points. Fuzzy vault scheme is order invariant and applied for point set, hence SIFT is suitable feature extraction method. SIFT is distinctive invariant feature extraction method. As there is a trade-off between accuracy and security, this is a challenge to implement biometric template protection scheme which will give better accuracy of the biometric system.

Deploying Access Control using Extended XACML in Open Web Service Environment

Now a days web services have a greater role in development of software systems. Generally, web server wants to determine which access can be granted and communicate with requesterfor open web service environment. These systems are designed to be open and web servers does not have determined conditions for communicate to the access requester. Such consideration makes traditional access control not applicable, which depends upon requester identification and authentication. Typically, XACML language is proposed for define the access control policy. It does not support novel features and not suitable in practice. In this paper, we extend the current XACML by providing novel features for controlling access in interoperable and flexible way, and then illustrate how such concepts can be deployed. Also, extend the standard XACML architecture to incorporate the new features for open web service systems