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Shubham Asthana

Bio: Shubham Asthana is an academic researcher from LNM Institute of Information Technology. The author has contributed to research in topics: Interference (wave propagation) & Bit error rate. The author has an hindex of 4, co-authored 4 publications receiving 37 citations.

Papers
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Proceedings Article
01 Dec 2015
TL;DR: An ‘Infant Cry Sounds Database’ (ICSD), collected especially for the study of likely cause of an infant’s cry, consists of infant cry sounds due to six causes: pain, discomfort, emotional need, ailment, environmental factors and hunger/thirst.
Abstract: Infant cry is a mode of communication, for interacting and drawing attention. The infants cry due to physiological, emotional or some ailment reasons. Cry involves high pitch changes in the signal. In this paper we describe an ‘Infant Cry Sounds Database’ (ICSD), collected especially for the study of likely cause of an infant’s cry. The database consists of infant cry sounds due to six causes: pain, discomfort, emotional need, ailment, environmental factors and hunger/thirst. The ground truth cause of cry is established with the help of two medical experts and parents of the infants. Preliminary analysis is carried out using the sound production features, the instantaneous fundamental frequency and frame energy derived from the cry acoustic signal, using auto correlation and linear prediction (LP) analysis. Spectrograms give the base reference. The infant cry sounds due to pain and discomfort are distinguished. The database should be helpful towards automated diagnosis of the causes of infant cry.

17 citations

Proceedings ArticleDOI
01 Dec 2014
TL;DR: A database collected for the analysis of infant cries vis-a-vis their causes, using spectrograms is described and an attempt is made to classify the infant cries into six categories such as pain, discomfort, ailments, emotional need for attention, hunger and cry due to manipulation.
Abstract: Infant crying comprises a rhythmic pattern of cry sounds and inhalation. Unlike in adults, crying is the only means of communication for an infant. Most signal processing tools that work well for adults are not adequate in the case of infant cry sounds. Hence there is a need to develop methods for extracting features from these sounds, for better understanding. This paper describes a database collected for the analysis of infant cries vis-a-vis their causes, using spectrograms. The fundamental frequency, limited to adults, can go much higher in the case of infant cries, along with rapid changes in F0. Signal processing methods like autocorrelation and linear prediction analysis are used for analyzing the infant cry sounds and extract features like fundamental frequency, energy etc. Spectrograms providing the ground truth and information about the fundamental frequency with harmonics are examined in this preliminary analysis. An attempt is made to classify the infant cries into six categories such as pain, discomfort, ailments, emotional need for attention, hunger and cry due to manipulation.

12 citations

Proceedings ArticleDOI
27 Apr 2015
TL;DR: Objective is to classify the infant cry sounds into different categories of causes, based on the features derived from the infantcry signal, and the results of the limited analysis are encouraging.
Abstract: Infant cry is a biological signal through which an infant communicates with its care-giving environment. It also contains valuable information about the state of the infant. Infants produce this sound in response to a stimuli, which could be pain, discomfort, emotional need of attention, ailment, environmental factors or hunger/thirst. Signal processing methods that work well for adults are not adequate in the case of infants. In order to analyze the infant cry signals, these methods require some modifications. Signal processing methods such as short-time Fourier transform, auto-correlation and linear prediction analysis are modified and used. Features such as frame-energy and fundamental frequency are extracted from the cry signal. An Infant Cry and Causes (ICC) database especially collected for the study is used. Ground truth information about the fundamental frequency (F 0 ) is obtained using the spectrograms. The fluctuations in F 0 are examined using mean and standard deviation, for different causes of cry. The results about fluctuations in F 0 obtained from three different signal processing methods are compared. Objective is to classify the infant cry sounds into different categories of causes, based on the features derived from the infant cry signal. The results of the limited analysis are encouraging.

8 citations

Proceedings ArticleDOI
27 Apr 2015
TL;DR: A Multi-user Multiple-Input Multiple-Output (MU-MIMO) based Cognitive Radio network where the unlicensed secondary uses (SU) can simultaneously use the spectrum which is used by a licensed primary user (PU) has been cancelled.
Abstract: In this paper, we propose a Multi-user Multiple-Input Multiple-Output (MU-MIMO) based Cognitive Radio network where the unlicensed secondary uses (SU) can simultaneously use the spectrum which is used by a licensed primary user (PU). The interference caused by the secondary user to the primary user has been cancelled. This is done by using Block Diagonalization (BD) followed by QR-MRL in order to cancel the interference caused by PU antennas. Previous works, such as ZF (Zero Forcing)-BD and MMSE (Minimum Mean Squared Error)-BD are succeed to cancel the interference among multiple users. Here, the performance comparison has been made in terms of Bit Error Rate (BER) plots for ZF-BD, MMSE-BD and QR-MRL-BD. Also, these techniques have been compared with BER plot obtained when SUs interfere with the PUs. The results show that the BD method is able to cancel the interference caused by the SUs successfully and the QR-MRL method which is an ordered successive interference cancellation(OSIC) method effectively cancels the interference caused among user's antennas. A significant improvement in BER plot for QR-MRL-BD is observed. Also, a simulink model for ZF-BD has been discussed for future hardware implementation.

4 citations


Cited by
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Proceedings ArticleDOI
01 Oct 2016
TL;DR: Larger fluctuations in the features F0, SoE and E are observed for infant cry due to pain, than due to discomfort, and features that may help towards developing automated diagnostic systems are explored.
Abstract: Infant cry signal is a biomedical acoustic signal that is usually high-pitched. Infant cry is his only means of communication, production of which involves significant changes in its characteristics. Possibly rapid changes in its short-time segments carry information about the cause of cry, that a mother can perceive. The instantaneous fundamental frequency (Fo) of infant cries is much higher than for adults, necessitating different signal processing methods for infant cry signals' analyses. In this paper, the production characteristics of infant cry signals due to pain vs. discomfort are discriminated, exploring features that may help towards developing automated diagnostic systems. Production features the F 0 , strength of excitation (SoE) and signal energy (E) are used, for analysing ‘Infant Cry Signals Database’ collected for the study. The excitation source characteristics are derived using a modified zero-frequency filtering method. Spectrograms of the acoustic signal and the excitation source characteristics are compared to validate the changes in the features. Larger fluctuations in the features F 0 , SoE and E are observed for infant cry due to pain, than due to discomfort.

15 citations

Journal ArticleDOI
04 Dec 2019
TL;DR: In this paper, the authors present a set of criteria to report experimental studies to ensure the validity of their methods and results, including participant information, data collection, methods, and data analysis.
Abstract: Infant cry is evolutionarily, psychologically, and clinically significant. Over the last half century, several researchers and clinicians have investigated acoustical properties of infant cry for medical purposes. However, this literature suffers a lack of standardization in conducting and reporting cry-based studies. In this work, methodologies and procedures employed to analyze infant cry are reviewed and best practices for reporting studies are provided. First, available literatures on vocal and audio acoustic analysis are examined to identify critical aspects of participant information, data collection, methods, and data analysis. Then, 180 peer-reviewed research articles have been assessed to certify the presence of critical information. Results show a general lack of critical description. Researchers in the field of infant cry need to develop a consensual standard set of criteria to report experimental studies to ensure the validity of their methods and results.

15 citations

Proceedings ArticleDOI
14 Jul 2019
TL;DR: This paper proposes a novel method through generating weighted prosodic features combined with acoustic features to form a merged feature matrix to classify asphyxiated baby crying effectively and has the benefits of keeping the robustness and resolution of the classification model simultaneously.
Abstract: Asphyxia is a respiratory injury that leads to a serious damage for infants. Early detection of asphyxia using Artificially Intelligent technology helps in reducing infant mortality rate when compared to traditional medical diagnosis, which is time consuming. In this paper, we propose a novel method through generating weighted prosodic features combined with acoustic features to form a merged feature matrix to classify asphyxiated baby crying effectively. The weights of the prosodic features are trained at the frame level with labeled data and can be optimized using deep learning approach with neural networks. The novel merged feature matrix is established with both acoustic and weighted prosodic features. The matrix has good ability to capture the diversity of variations within infant cries, especially for asphyxiated samples. Our method has the benefits of keeping the robustness and resolution of the classification model simultaneously. The effectiveness of this approach is evaluated on Baby Chillanto Database. Our method yields a significant reduction of 3.11%, 3.23%, and 1.43% absolute classification error rate compared with the results using single acoustic features, single prosodic features, and both acoustic and prosodic features, respectively. The testing accuracy in our method reaches 96.74%, which outperforms all other related studies on asphyxiated baby crying classification.

13 citations

01 Jan 2007
TL;DR: In this article, a maximum likelihood estimator for digital sequences disturbed by Gaussian noise, intersymbol interference (ISI) and interchannel interference (ICI) is derived.
Abstract: A maximum likelihood (ML) estimator for digital sequences disturbed by Gaussian noise, intersymbol interference (ISI) and interchannel interference (ICI) is derived. It is shown that the sampled outputs of the multiple matched filter (MMF) form a set of sufficient statistics for estimating the input vector sequence. Two ML vector sequence estimation algorithms are presented. One makes use of the sampled output data of the multiple whitened matched filter and is called the vector Viterbi algorithm. The other one is modification of the vector Viterbi algorithm and uses directly the sampled output of the MMF. It appears that, under a certain condition, the error performance is asymptotically as good as if both ISI and ICI were absent.

13 citations

Proceedings ArticleDOI
13 Sep 2016
TL;DR: The excitation source features F0 and strength of excitation (SoE) are derived using a recently proposed modified zerofrequency filtering method and can help in developing further the clinical assistive technologies for discriminating different infant cry types and initiating the remedial measures automatically.
Abstract: Cry is a means of communication for an infant. Infant cry signal is usually perceived as a high-pitched sound. Intuitively, significant changes seem to occur in the production source characteristics of cry sounds. Since the instantaneous fundamental frequency (F0) of infant cry is much higher than for adults and changes rapidly, the signal processing methods that work well for adults may fail in analyzing these signals. Hence, in this paper, we derive the excitation source features F0 and strength of excitation (SoE) using a recently proposed modified zerofrequency filtering method. Changes in the production characteristics of acoustic signals of infant cries due to pain and discomfort are examined using the features F0, SoE and signal energy. These changes are validated by visually comparing their spectrograms with the spectrograms of the acoustic signals. Effectiveness of these discriminating features is examined for different pain/discomfort cry sounds pairs in an ‘Infant Cry Signals Database (IIIT-S ICSD)’, especially collected for this study. Fluctuations in the features F0, SoE and energy are observed to be larger in the case of infant cry due to pain, than for discomfort. These features can help in developing further the clinical assistive technologies for discriminating different infant cry types and initiating the remedial measures automatically.

11 citations