PERFORMANCE OF DIFFERENT CLASSIFIERS IN SPEECH RECOGNITION

Speech is the most natural means of communication among human beings and speech processing and recognition are intensive areas of research for the last five decades. Since speech recognition is a pattern recognition problem, classification is an important part of any speech recognition system. In this work, a speech recognition system is developed for recognizing speaker independent spoken digits in Malayalam. Voice signals are sampled directly from the microphone. The proposed method is implemented for 1000 speakers uttering 10 digits each. Since the speech signals are affected by background noise, the signals are tuned by removing the noise from it using wavelet denoising method based on Soft Thresholding. Here, the features from the signals are extracted using Discrete Wavelet Transforms (DWT) because they are well suitable for processing non-stationary signals like speech. This is due to their multi- resolutional, multi-scale analysis characteristics. Speech recognition is a multiclass classification problem. So, the feature vector set obtained are classified using three classifiers namely, Artificial Neural Networks (ANN), Support Vector Machines (SVM) and Naive Bayes classifiers which are capable of handling multiclasses. During classification stage, the input feature vector data is trained using information relating to known patterns and then they are tested using the test data set. The performances of all these classifiers are evaluated based on recognition accuracy. All the three methods produced good recognition accuracy. DWT and ANN produced a recognition accuracy of 89%, SVM and DWT combination produced an accuracy of 86.6% and Naive Bayes and DWT combination produced an accuracy of 83.5%. ANN is found to be better among the three methods.

Speech Recognition of Malayalam Numbers

Digit speech recognition is important in many applications such as automatic data entry, PIN entry, voice dialing telephone, automated banking system, etc. This paper presents speaker independent speech recognition system for Malayalam digits. The system employs Mel frequency cepstrum coefficient (MFCC) as feature for signal processing and Hidden Markov model (HMM) for recognition. The system is trained with 21 male and female voices in the age group of 20 to 40 years and there was 98.5% word recognition accuracy (94.8% sentence recognition accuracy) on a test set of continuous digit recognition task.

Automated Transcription System for Malayalam Language

Malayalam is one of the 22 scheduled languages in India with more than 130 million speakers. This paper presents a report on the development of a speaker independent, continuous transcription system for Malayalam. The system employs Hidden Markov Model (HMM) for acoustic modeling and Mel Frequency Cepstral Coefficient (MFCC) for feature extraction. It is trained with 21 male and female speakers in the age group ranging from 20 to 40 years. The system obtained a word recognition accuracy of 87.4% and a sentence recognition accuracy of 84%, when tested with a set of continuous speech data.

Malayalam Isolated Digit Recognition using HMM and PLP cepstral coefficient

Development of Malayalam speech recognition system is in its infancy stage; although many works have been done in other Indian languages. In this paper we present the first work on speaker independent Malayalam isolated speech recognizer based on PLP (Perceptual Linear Predictive) Cepstral Coefficient and Hidden Markov Model (HMM). The performance of the developed system has been evaluated with different number of states of HMM (Hidden Markov Model). The system is trained with 21 male and female speakers in the age group ranging from 19 to 41 years. The system obtained an accuracy of 99.5% with the unseen data

Connected digit speech recognition system for Malayalam language

A connected digit speech recognition is important in many applications such as automated banking system, catalogue-dialing, automatic data entry, automated banking system, etc. This paper presents an optimum speaker-independent connected digit recognizer forMalayalam language. The system employs Perceptual Linear Predictive (PLP) cepstral coefficient for speech parameterization and continuous density Hidden Markov Model (HMM) in the recognition process. Viterbi algorithm is used for decoding. The training data base has the utterance of 21 speakers from the age group of 20 to 40 years and the sound is recorded in the normal office environment where each speaker is asked to read 20 set of continuous digits. The system obtained an accuracy of 99.5 % with the unseen data.

A Hybrid Architecture for Recognising Speech Signals in Malayalam

Speech is the primary, most prominent and convenient means of communication in audible language. Through speech, people can express their thoughts, feelings or perceptions by the articulation of words. Human speech is a complex signal which is non stationary in nature. It consists of immensely rich information about the words spoken, accent, attitude of the speaker, expression, intention, sex, emotion as well as style. The main objective of Automatic Speech Recognition (ASR) is to identify whatever people speak by means of computer algorithms. This enables people to communicate with a computer in a natural spoken language. Automatic recognition of speech by machines has been one of the most exciting, significant and challenging areas of research in the field of signal processing over the past five to six decades. Despite the developments and intensive research done in this area, the performance of ASR is still lower than that of speech recognition by humans and is yet to achieve a completely reliable performance level. The main objective of this thesis is to develop an efficient speech recognition system for recognising speaker independent isolated words in Malayalam.

Improved Biometric Authentication System Using Multimodal Cue Integration

Biometrics is an efficient technology with great possibilities in the area of security system development for official and commercial applications. The biometrics has recently become a significant part of any efficient person authentication solution. The advantage of using biometric traits is that they cannot be stolen, shared or even forgotten. The thesis addresses one of the emerging topics in Authentication System, viz., the implementation of Improved Biometric Authentication System using Multimodal Cue Integration, as the operator assisted identification turns out to be tedious, laborious and time consuming. In order to derive the best performance for the authentication system, an appropriate feature selection criteria has been evolved. It has been seen that the selection of too many features lead to the deterioration in the authentication performance and efficiency. In the work reported in this thesis, various judiciously chosen components of the biometric traits and their feature vectors are used for realizing the newly proposed Biometric Authentication System using Multimodal Cue Integration. The feature vectors so generated from the noisy biometric traits is compared with the feature vectors available in the knowledge base and the most matching pattern is identified for the purpose of user authentication. In an attempt to improve the success rate of the Feature Vector based authentication system, the proposed system has been augmented with the user dependent weighted fusion technique.

Evaluation of Auditory Displays Supporting Aircraft Approach and Landing

Abstract: The paper describes an auditory interface using directional sound as a possible support for pilots during approach in an instrument landing scenario. Several ways of producing directional sounds are illustrated. One using speaker pairs and controlling power distribution between speakers is evaluated experimentally. Results show, that power alone is insufficient for positioning single isolated sound events, although discrimination in the horizontal plane performs better than in the vertical. Additional sound parameters to compensate for this are proposed.

PowerPoint - basic skills training

This step-by-step guided worksheet and accompanying PowerPoint file introduce some key skills: - reorganising slides and bullets - creating speaker notes - printing slide handouts - including hyperlinks - adding images Simple stuff, but many find it useful - it uses Office 2004 (XP)

WAIS seminar: Publication Workflows for Scientific Data

Wednesday 23rd April 2014 Speaker(s): Willi Hasselbring Organiser: Leslie Carr Time: 23/04/2014 11:00-11:50 Location: B32/3077 File size: 669 Mb Abstract For good scientific practice, it is important that research results may be properly checked by reviewers and possibly repeated and extended by other researchers. This is of particular interest for "digital science" i.e. for in-silico experiments. In this talk, I'll discuss some issues of how software systems and services may contribute to good scientific practice. Particularly, I'll present our PubFlow approach to automate publication workflows for scientific data. The PubFlow workflow management system is based on established technology. We integrate institutional repository systems (based on EPrints) and world data centers (in marine science). PubFlow collects provenance data automatically via our monitoring framework Kieker. Provenance information describes the origins and the history of scientific data in its life cycle, and the process by which it arrived. Thus, provenance information is highly relevant to repeatability and trustworthiness of scientific results. In our evaluation in marine science, we collaborate with the GEOMAR Helmholtz Centre for Ocean Research Kiel.

WAIS seminar: Application Performance Monitoring and Architecture Discovery with Kieker

Wednesday 23rd April 2014 Speaker(s): Willi Hasselbring Organiser: Leslie Carr Time: 23/04/2014 14:00-15:00 Location: B32/3077 File size: 802Mb Abstract The internal behavior of large-scale software systems cannot be determined on the basis of static (e.g., source code) analysis alone. Kieker provides complementary dynamic analysis capabilities, i.e., monitoring/profiling and analyzing a software system's runtime behavior. Application Performance Monitoring is concerned with continuously observing a software system's performance-specific runtime behavior, including analyses like assessing service level compliance or detecting and diagnosing performance problems. Architecture Discovery is concerned with extracting architectural information from an existing software system, including both structural and behavioral aspects like identifying architectural entities (e.g., components and classes) and their interactions (e.g., local or remote procedure calls). In addition to the Architecture Discovery of Java systems, Kieker supports Architecture Discovery for other platforms, including legacy systems, for instance, inplemented in C#, C++, Visual Basic 6, COBOL or Perl. Thanks to Kieker's extensible architecture it is easy to implement and use custom extensions and plugins. Kieker was designed for continuous monitoring in production systems inducing only a very low overhead, which has been evaluated in extensive benchmark experiments. Please, refer to http://kieker-monitoring.net/ for more information.

WAIS seminar: Computer Science, the Revolution in Schools

Tuesday 22nd April 2014 Speaker(s): Sue Sentance Organiser: Leslie Carr Time: 22/04/2014 15:00-16:00 Location: B32/3077 File size: 698 Mb Abstract Until recently, "computing" education in English schools mainly focused on developing general Digital Literacy and Microsoft Office skills. As of this September, a new curriculum comes into effect that provides a strong emphasis on computation and programming. This change has generated some controversy in the news media (4-year-olds being forced to learn coding! boss of the government’s coding education initiative cannot code shock horror!!!!) and also some concern in the teaching profession (how can we possibly teach programming when none of the teachers know how to program)? Dr Sue Sentance will explain the work of Computing At School, a part of the BCS Academy, in galvanising universities to help teachers learn programming and other computing skills. Come along and find out about the new English Computing Revolution - How will your children and your schools be affected? - How will our University intake change? How will our degrees have to change? - What is happening to the national perception of Computer Science?

WAIS seminar: Linked Cultural Media

Wednesday 9th April 2014 Speaker(s): Guus Schreiber Time: 09/04/2014 11:00-11:50 Location: B32/3077 File size: 546Mb Abstract In this talk I will discuss linked data for museums, archives and libraries. This area is known for its knowledge-rich and heterogeneous data landscape. The objects in this field range from old manuscripts to recent TV programs. Challenges in this field include common metadata schema's, inter-linking of the omnipresent vocabularies, cross-collection search strategies, user-generated annotations and object-centric versus event-centric views of data. This work can be seen as part of the rapidly evolving field of digital humanities. Speaker Biography Guus Schreiber Guus is a professor of Intelligent Information Systems at the Department of Computer Science at VU University Amsterdam. Guus’ research interests are mainly in knowledge and ontology engineering with a special interest for applications in the field of cultural heritage. He was one of the key developers of the CommonKADS methodology. Guus acts as chair of W3C groups for Semantic Web standards such as RDF, OWL, SKOS and REFa. His research group is involved in a wide range of national and international research projects. He is now project coordinator of the EU Integrated project No Tube concerned with integration of Web and TV data with the help of semantics and was previously Scientific Director of the EU Network of Excellence “Knowledge Web”.

WAIS seminar: Provenance Analytics and Crowdsourcing

Wednesday 26th March 2014 Speaker(s): Dr Trung Dong Huynh Organiser: Dr Tim Chown Time: 26/03/2014 11:00-11:50 Location: B32/3077 File size: 349Mb Abstract Understanding the dynamics of a crowdsourcing application and controlling the quality of the data it generates is challenging, partly due to the lack of tools to do so. Provenance is a domain-independent means to represent what happened in an application, which can help verify data and infer their quality. It can also reveal the processes that led to a data item and the interactions of contributors with it. Provenance patterns can manifest real-world phenomena such as a significant interest in a piece of content, providing an indication of its quality, or even issues such as undesirable interactions within a group of contributors. In this talk, I will present an application-independent methodology for analysing provenance graphs, constructed from provenance records, to learn about such patterns and to use them for assessing some key properties of crowdsourced data, such as their quality, in an automated manner. I will also talk about CollabMap (www.collabmap.org), an online crowdsourcing mapping application, and show how we applied the approach above to the trust classification of data generated by the crowd, achieving an accuracy over 95%.

WAIS seminar: Research Discussion: Lab of Things? What Things?

Wednesday 19th March 2014 Speaker(s): Kirk Martinez, Dr Jonathon S Hare and Dr Enrico Costanza Organiser: Dr Tim Chown Time: 19/03/2014 11:00-11:50 Location: B32/3077 File size: 676 Mb Abstract The new WAIS seminar series features classic seminars, research discussions, tutorial-style presentations, and research debates. This seminar takes the form of a research discussion which will focus on the Internet of Things (IoT) research being undertaken in WAIS and other research groups in ECS. IoT is a significant emerging research area, with funding for research available from many channels including new H2020 programmes and the TSB. We have seen examples of IoT devices being built in WAIS and other ECS groups, e.g. in sensor networking, energy monitoring via Zigbee devices, and of course Erica the Rhino (a Big Thing!). The goal of the session is to briefly present such examples of existing Things in our lab with the intent of seeding discussion on open research questions, and therefore future work we could do towards new Things being deployed for experimentation in Building 32 or its environs. The session will discuss what 'things' we have, how they work, what new 'things' might we want to create and deploy, what components we might need to enable this, and how we might interact with these objects.