Word and syllable Boundary Determination in Continuous Bodo Speech

The idea of word boundary is very fundamental and one of the important factors as far as the study of any human language is concerned. In actual practice it seems, describing boundaries of word are somewhat easier to define, although it is a subject with limited spread. In this paper, we try to study the spoken Bodo language, we considered four common criteria for detection of boundaries of syllable or word namely quick initial speech, sluggish terminating speech, reset in pitch and pauses) and examined their existence in a fragment taken from a recorded database that contains approximately 23 similar units. The recorded speech was parsed by two linguistic experts and the result so obtained were examined acoustically to establish which were present at each separation of words. Later on the obtained result is compared with the result obtained from SVM classifier. It has been noticed that both approaches gives similar and comparative result. Further, it is found that only a few of the determined separation of words conformed to all cues. It is found that the sluggish terminating speech was most prevailing, followed by reset in pitch, then pauses, and finally quick initial speech. An intense study, involving large set of units and more speakers is still under process

Analytical Study of CV Type Bodo Words using Formant Frequency Measure

Words can be categorized into different types according to the position of occurrences of vowels and consonants in the word. Accordingly we have CV (Consonant-Vowel), VC (Vowel-Consonant), CVC (Consonant-Vowel-Consonant), CVCC (Consonant-Vowel-Consonant-Consonant), CVVC (Consonant-Vowel-Vowel-Consonant etc type of words in most of the languages. As a first step towards the recognition of any speech signal, it is very much important to study the different types of words using some of the available techniques. Some of the approach which produces reliable and good results are Formant Frequency measure, Mel-frequency cepstral coefficients (MFCC) etc.  In this paper, a step has been taken to measure the formant frequency of CV type Bodo words to identify the distinct features of it. Formant Frequency, based on Formant Tracking Model can be defined as the spectral peak of the sound spectrum |P(f)|.Keywords— MFCC, Formant Tracking Model, FFT, Formant Frequency, Resonance Frequenc

Automatic text summarization of konkani texts using pre-trained word embeddings and deep learning

Automatic text summarization has gained immense popularity in research. Previously, several methods have been explored for obtaining effective text summarization outcomes. However, most of the work pertains to the most popular languages spoken in the world. Through this paper, we explore the area of extractive automatic text summarization using deep learning approach and apply it to Konkani language, which is a low-resource language as there are limited resources, such as data, tools, speakers and/or experts in Konkani. In the proposed technique, Facebook’s fastText pre-trained word embeddings are used to get a vector representation for sentences. Thereafter, deep multi-layer perceptron technique is employed, as a supervised binary classification task for auto-generating summaries using the feature vectors. Using pre-trained fastText word embeddings eliminated the requirement of a large training set and reduced training time. The system generated summaries were evaluated against the ‘gold-standard’ human generated summaries with recall-oriented understudy for gisting evaluation (ROUGE) toolkit. The results thus obtained showed that performance of the proposed system matched closely to the performance of the human annotators in generating summaries

An In-depth Study on POS Tagging for Assamese Language

Abstract:  An automatic POS tagger is very essential component of any Natural Language Processing (NLP) work. It is one of the important steps towards the processing of Natural Language. There are various challenges in the tagging of POS and most of the time these are language-dependent. Assamese is one of the morphologically rich and free word order language. Because of this, the challenges are even more. In the present paper, the basic concept of the POS tagger and its importance in the NLP is discussed. In the later part of the paper, the overall characteristics of the Assamese language are discussed in short and its various challenges, that may raise towards the tagging of POS is discussed. The paper also discusses about the various POS techniques that are commonly used in the tagging of POS for the Assamese language

Study on Feature Extraction of Speech Emotion Recognition

Speech emotion recognition system aims at automatically identifying the emotion of the speaker from the speech. It is a modification of the speech recognition system which only identifies the speech. In this paper, we study the feature extraction algorithm such as pitch, formant frequency and MFCC.Keywords:Feature extraction, pitch, formant frequency, MFC

Double Stage chain routing Protocal in WSN

Wireless sensor networking is most popular fields in today’s world. In this paper, we have discussed the different energy optimization protocols of WSN. We have forwarded a new protocol “Double Stage Chain Routing Protocol†from WSN. Our main focus is on extending the residual energy and network’s life time at least more than LEACH, CCM and TSCP. The result of our protocol is represented with the help of graph with comparison with TSCP and it is found that DSCRP gives better network lifetime than LEACH. The proposed algorithm is acceptable in the network lifetime of DSCRP as well as in network life time

Sustainable flood risk assessment using deep learning-based algorithms with a blockchain technology

The couplings of convolutional neural networks (CNN) with random forest (RF), support vector machine (SVM), long short-term memory (LSTM), and extreme gradient boosting (XGBoost) ensemble algorithms were used to construct novel ensemble computational models (CNN-LSTM, CNN-XG, CNN-SVM, and CNN-RF) for flood hazard mapping in the monsoon-dominated catchment, Bangladesh. The results revealed that geology, elevation, the normalized difference vegetation index (NDVI), and rainfall are the most significant parameters in flash floods based on the Pearson correlation technique. Statistical method such as the area under the curve (AUC) was used to evaluate model performance. The CNN-RF model could be a promising tool for precisely predicting and mapping flash floods as it is outperformed the other models (AUC = 1.0). Furthermore, to meet sustainable development goals (SDGs), a blockchain-based technology is proposed to create a decentralized flood management tool for help seekers and help providers during and post floods. The suggested tool accelerates emergency rescue operations during flood events