Speech Recognition Systems(SRS) have been implemented by various processors including the digital signal processors(DSPs) and field programmable gate arrays(FPGAs) and their performance has been reported in literature. The fundamental purpose of speech is communication, i.e., the transmission of messages.In the case of speech, the fundamental analog form of the message is an acoustic waveform, which we call the speech signal. Speech signals can be converted to an electrical waveform by a microphone, further manipulated by both analog and digital signal processing, and then converted back to acoustic form by a loudspeaker, a telephone handset or headphone, as desired.The recognition of speech requires feature extraction and classification. The systems that use speech as input require a microcontroller to carry out the desired actions. In this paper, Cypress Programmable System on Chip (PSoC) has been studied and used for implementation of SRS. From all the available PSoCs, PSoC5 containing ARM Cortex-M3 as its CPU is used. The noise signals are firstly nullified from the speech signals using LogMMSE filtering. These signals are then sent to the PSoC5 wherein the speech is recognized and desired actions are performed.
Speech is the vocalizer form of human communication,and based upon the syntactic combination of lexical and vocabularies. The aim of speech coding is to compress the speech signal to the highest possible compression ratio bu t maintaining user acceptability.There are many methods for speech compression like Linear Pre dictive coding (LPC),Code Excited Linear Predictive coding (CELP),Sub-band coding,T ransform coding:- Fast Fourier Transform (FFT),Discrete Cosine Transform (DCT),Continuous Wavelet Transform (CWT),Discrete Wavelet Transform (DWT),Variance Fractal Compression (VFC),Discrete Cosine Transform (DCT),Psychoacoustics and etc. Few of them are discus in this paper.
Audio Compression Techniques
a type of lossy or lossless compression in which the amount of data in a recorded waveform is reduced to differing extents for transmission respectively with or without some loss of quality, used in CD and MP3 encoding, Internet radio.
Dynamic range compression, also called audio level compression, in which the dynamic range, the difference between loud and quiet, of an audio waveform is reduced
Speech is the vocalizer form of human communication,and based upon the syntactic combination of lexical and vocabularies. The aim of speech coding is to compress the speech signal to the highest possible compression ratio bu t maintaining user acceptability.There are many methods for speech compression like Linear Pre dictive coding (LPC),Code Excited Linear Predictive coding (CELP),Sub-band coding,T ransform coding:- Fast Fourier Transform (FFT),Discrete Cosine Transform (DCT),Continuous Wavelet Transform (CWT),Discrete Wavelet Transform (DWT),Variance Fractal Compression (VFC),Discrete Cosine Transform (DCT),Psychoacoustics and etc. Few of them are discus in this paper.
Audio Compression Techniques
a type of lossy or lossless compression in which the amount of data in a recorded waveform is reduced to differing extents for transmission respectively with or without some loss of quality, used in CD and MP3 encoding, Internet radio.
Dynamic range compression, also called audio level compression, in which the dynamic range, the difference between loud and quiet, of an audio waveform is reduced
Esrtrategias para la diferenciación de la enseñanza.
ALINEACIÓN DE ESTRATEGIAS DE EDUCACIÓN DIFERENCIADA Y POSIBLES ACOMODOS PARA LOS DIFERENTES SUBGRUPOS.
AN ANALYSIS OF SPEECH RECOGNITION PERFORMANCE BASED UPON NETWORK LAYERS AND T...IJCSEA Journal
Speech is the most natural way of information exchange. It provides an efficient means of means of manmachine communication using speech interfacing. Speech interfacing involves speech synthesis and speech recognition. Speech recognition allows a computer to identify the words that a person speaks to a microphone or telephone. The two main components, normally used in speech recognition, are signal processing component at front-end and pattern matching component at back-end. In this paper, a setup that uses Mel frequency cepstral coefficients at front-end and artificial neural networks at back-end has been developed to perform the experiments for analyzing the speech recognition performance. Various experiments have been performed by varying the number of layers and type of network transfer function, which helps in deciding the network architecture to be used for acoustic modelling at back end.
Design and implementation of different audio restoration techniques for audio...eSAT Journals
Abstract
Audio signals are corrupted with many types of distortions. Major audio distortions are categorized into Globalized and
Localized distortions. Localized distortion includes clipping and clicks where only certain samples are affected and globalized
distortions include broadband noise where complete bandwidth is consumed by noise. Audio restoration is a technique for giving
back the audio signals from these distortions. In this paper, audio restoration techniques for removing clipping, clicks and
broadband noise are put forwarded. Recent approaches to solving audio restoration problem is with respect to sparse
representation algorithms. Clipping distortion is addressed with a Sparse representation framework, it is treated as a reverse
problem, where the distorted samples is estimated from the surrounding undistorted samples, they are embedded in frame based
scheme, and reconstructed by using an overlap add method in conjunction with OMP algorithm and Gabor/DCT dictionary for
modelling audio signals. Broadband denoising is done by using spectral subtraction and Click removal is done by using an
adaptive filter method as the first step. Performance measures are done based on perception, average SNR calculation and
defined parameter variations. This paper also targeting towards the software and hardware implementation of the restoration
methods using TMS320C6713 DSK kit with help of tools mainly MATLAB and Code Composer studio.
Key Words: Audio Distortions, OMP algorithm, Gabor/DCT dictionary, TMS320C6713DSK
Speech compression analysis using matlabeSAT Journals
Abstract The growth of the cellular technology and wireless networks all over the world has increased the demand for digital information by manifold. This massive demand poses difficulties for handling huge amounts of data that need to be stored and transferred. To overcome this problem we can compress the information by removing the redundancies present in it. Redundancies are the major source of generating errors and noisy signals. Coding in MATLAB helps in analyzing compression of speech signals with varying bit rate and remove errors and noisy signals from the speech signals. Speech signal’s bit rate can also be reduced to remove error and noisy signals which is suitable for remote broadcast lines, studio links, satellite transmission of high quality audio and voice over internet This paper focuses on speech compression process and its analysis through MATLAB by which processed speech signal can be heard with clarity and in noiseless mode at the receiver end . Keywords: Speech compression, bit rate, filter, MPEG, DCT.
IJRET : International Journal of Research in Engineering and Technology is an international peer reviewed, online journal published by eSAT Publishing House for the enhancement of research in various disciplines of Engineering and Technology. The aim and scope of the journal is to provide an academic medium and an important reference for the advancement and dissemination of research results that support high-level learning, teaching and research in the fields of Engineering and Technology. We bring together Scientists, Academician, Field Engineers, Scholars and Students of related fields of Engineering and Technology
Speaker Recognition System using MFCC and Vector Quantization Approachijsrd.com
This paper presents an approach to speaker recognition using frequency spectral information with Mel frequency for the improvement of speech feature representation in a Vector Quantization codebook based recognition approach. The Mel frequency approach extracts the features of the speech signal to get the training and testing vectors. The VQ Codebook approach uses training vectors to form clusters and recognize accurately with the help of LBG algorithm.
One of the common and easier techniques of feature extraction is Mel Frequency Cestrum Coefficient (MFCC) which allows the signals to extract the feature vector. It is used by Dynamic Feature Extraction and provide high performance rate when compared to previous technique like LPC. But one of the major drawbacks in this technique is robustness. Another feature extraction technique is Relative Spectral (RASTA). In effect the RASTA filter band passes each feature coefficient and in both the log spectral and the Spectral domains appear linear channel distortions as an additive constant. The high-pass portions of the equivalent band pass filter effect the convolution noise introduced in the channel. The low-pass filtering helps in smoothing frame to frame spectral changes. Compared to MFCC feature extraction technique, RASTA filtering reduces the impact of the noise in signals and provides high robustness
IJRET : International Journal of Research in Engineering and Technology is an international peer reviewed, online journal published by eSAT Publishing House for the enhancement of research in various disciplines of Engineering and Technology. The aim and scope of the journal is to provide an academic medium and an important reference for the advancement and dissemination of research results that support high-level learning, teaching and research in the fields of Engineering and Technology. We bring together Scientists, Academician, Field Engineers, Scholars and Students of related fields of Engineering and Technology
REAL TIME SPECIAL EFFECTS GENERATION AND NOISE FILTRATION OF AUDIO SIGNAL USI...ijcsa
Digital signal processing is being increasingly used for audio processing applications. Digital audio effects
refer to all those algorithms that are used for enhancing sound in any of the steps of a processing chain of
music production. Real time audio effects generation is a highly challenging task in the field of signal
processing. Now a day, almost every high end multimedia audio device does digital signal processing in
one form or another. For years musicians have used different techniques to give their music a unique
sound. Earlier, these techniques were implemented after a lot of work and experimentation. However, now
with the emergence of digital signal processing this task is simplified to a great extent. In this article, the
generations of special effects like echo, flanging, reverberation, stereo, karaoke, noise filtering etc are
successfully implemented using MATLAB and an attractive GUI has been designed for the same.
GENDER RECOGNITION SYSTEM USING SPEECH SIGNALIJCSEIT Journal
In this paper, a system, developed for speech encoding, analysis, synthesis and gender identification is
presented. A typical gender recognition system can be divided into front-end system and back-end system.
The task of the front-end system is to extract the gender related information from a speech signal and
represents it by a set of vectors called feature. Features like power spectrum density, frequency at
maximum power carry speaker information. The feature is extracted using First Fourier Transform (FFT)
algorithm. The task of the back-end system (also called classifier) is to create a gender model to recognize
the gender from his/her speech signal in recognition phase. This paper also presents the digital processing
of a speech signals (pronounced “A” and “B”) which are taken from 10 persons, 5 of them are Male and
the rest of them are Female. Power Spectrum Estimation of the signal is examined .The frequency at
maximum power of the English Phonemes is extracted from the estimated power spectrum. The system uses
threshold technique as identification tool. The recognition accuracy of this system is 80% on average.
Similar to PSoC BASED SPEECH RECOGNITION SYSTEM (20)
Cars are a very important part of this modern world because they give luxury and comfort. Even
though they are comfortable, some problems always keep arising on the safety side. After a lot of research they
rectified certain problems using air bags, auto parking, turbo charger, pedal shift…, etc.
And now we are going to discuss about one such problem that arises on the safety side. An unsuspected
accident occurs when people smash their fingers in between the car doors. Due to this kind of accident around
120,000 people are injured every year. But this was not taken as a very major safety concern for the customer.
To avoid this kind accident due to car doors, we are introducing “SAFETY DOOR LOCK SYSTEM”
with the help of “HYDRAULIC PISTON AND IR SENSORS”.
The major working process of the “SAFETY DOOR LOCK SYSTEM”is, when a person places his/her
hand or fingers in the gap between the door and the outer panel, at the time when the closing action of the door
takes place, the Sensors start to transmit the Infra Red Rays to the Receivers at the
other end, and so even if someone closes the door without anybody‟s knowledge the hydraulic piston will
automatically come out and stop the door from closing and prevent the person from the unsuspected accident
and minor injuries by the car door and ensure maximum safety to the customer.
Extrusion can be defined as the process of subjecting a material to compression so that it is forced to
flow through an opening of a die and takes the shape of the hole. Multi-hole extrusion is the process of
extruding the products through a die having more than one hole. Multi-hole extrusion increases the production
rate and reduces the cost of production. In this study the ram force has calculated experimentally for single hole
and multi-hole extrusion. The comparison of ram forces between the single hole and multi-hole extrusion
provides the inverse relation between the numbers of holes in a die and ram force. The experimental lengths of
the extruded products through the various holes of multi-hole die are different. It indicates that the flow pattern
is dependent on the material behavior. The micro-hardness test has done for the extruded products of lead
through multi-hole die. It is observed that the hardness of the extruded lead products from the central hole is
found to be more than that of the products extruded from other holes. The study suggests that multi-hole
extrusion can be used for obtaining the extruded products of lead with varying hardness. The micro-structure
study has done for the lead material before and after extrusion. It is observed that the size of grains of lead
material after extrusion is smaller than the original lead.
Analysis of Agile and Multi-Agent Based Process Scheduling Modelirjes
As an answer of long growing frustration of waterfall Software development life cycle concepts,
agile software development concept was evolved in 90’s. The most popular agile methodologies is the Extreme
Programming (XP). Most software companies nowadays aim to produce efficient, flexible and valuable
Software in short time period with minimal costs, and within unstable, changing environments. This complex
problem can be modeled as a multi-agent based system, where agents negotiate resources. Agents can be used to
represent projects and resources. Crucial for the multi-agent based system in project scheduling model, is the
availability of an effective algorithm for prioritizing and scheduling of task. To evaluate the models, simulations
were carried out with real life and several generated data sets. The developed model (Multi-agent based System)
provides an optimized and flexible agile process scheduling and reduces overheads in the software process as it
responds quickly to changing requirements without excessive work in project scheduling.
Effects of Cutting Tool Parameters on Surface Roughnessirjes
This paper presents of the influence on surface roughness of Co28Cr6Mo medical alloy machined
on a CNC lathe based on cutting parameters (rotational speed, feed rate, depth of cut and nose radius).The
influences of cutting parameters have been presented in graphical form for understanding. To achieve the
minimum surface roughness, the optimum values obtained for rpm, feed rate, depth of cut and nose radius were
respectively, 318 rpm, 0,1 mm/rev, 0,7 mm and 0,8 mm. Maximum surface roughness has been revealed the
values obtained for rpm, feed rate, depth of cut and nose radius were respectively, 318 rpm, 0,25 mm/rev, 0,9
mm and 0,4 mm.
Possible limits of accuracy in measurement of fundamental physical constantsirjes
The measurement uncertainties of Fundamental Physical Constants should take into account all
possible and most influencing factors. One from them is the finiteness of the model that causes the existence of
a-priori error. The proposed formula for calculation of this error provides a comparison of its value with the
actual experimental measurement error that cannot be done an arbitrarily small. According to the suggested
approach, the error of the researched Fundamental Physical Constant, measured in conventional field studies,
will always be higher than the error caused by the finite number of dimensional recorded variables of physicalmathematical
models. Examples of practical application of the considered concept for measurement of fine
structure constant, speed of light and Newtonian constant of gravitation are discussed.
Performance Comparison of Energy Detection Based Spectrum Sensing for Cogniti...irjes
With the rapid deployment of new wireless devices and applications, the last decade has witnessed a growing
demand for wireless radio spectrum. However, the policy of fixed spectrum assignment produces a bottleneck for more
efficient spectrum utilization, such that a great portion of the licensed spectrum is severely under-utilized. So the concept of
cognitive radio was introduced to address this issue.The inefficient usage of the limited spectrum necessitates the
development of dynamic spectrum access techniques, where users who have no spectrum licenses, also known as secondary
users, are allowed to use the temporarily unused licensed spectrum. For this purpose we have to know the presence or
absence of primary users for spectrum usage. So spectrums sensing is one of the major requirements of cognitive radio.Many
spectrum sensing techniques have been developed to sense the presence or absence of a licensed user. This paper evaluates
the performance of the energy detection based spectrum sensing technique in noisy and fading environments.The
performance of the energy detection technique will be evaluated by use of Receiver Operating Characteristics (ROC) curves
over additive white Gaussian noise (AWGN) and fading channels.
Comparative Study of Pre-Engineered and Conventional Steel Frames for Differe...irjes
In this paper, the conventional steel frames having triangular Pratt truss as a roofing system of 60 m
length, span 30m and varying bay spacing 4m, 5m and 6m respectively having eaves level for all the portals is at
10m and the EOT crane is supported at the height of 8m from ground level and pre-engineered steel frames of
same dimensions are analyzed and designed for wind zones (wind zone 2, wind zone 3, wind zone 4 and wind
zone 5) by using STAAD Pro V8i. The study deals with the comparative study of both conventional and preengineered
with respect to the amount of structural steel required, reduction in dead load of the structure.
Flip bifurcation and chaos control in discrete-time Prey-predator model irjes
The dynamics of discrete-time prey-predator model are investigated. The result indicates that the
model undergo a flip bifurcation which found by using center manifold theorem and bifurcation theory.
Numerical simulation not only illustrate our results, but also exhibit the complex dynamic behavior, such as the
periodic doubling in period-2, -4 -8, quasi- periodic orbits and chaotic set. Finally, the feedback control method
is used to stabilize chaotic orbits at an unstable interior point.
Energy Awareness and the Role of “Critical Mass” In Smart Citiesirjes
A Smart City could be depicted as a place, logical and physical, in which a crowd of heterogeneous
entities is related in time and space through different types of interactions. Any type of entity, whether it is a
device or a person, clustered in communities, becomes a source of context-based data.
Energy awareness is able to drive the process of bringing our society to limit energy waste and to optimize
usage of available resources, causing a strong environmental and social impact. Then, following social network
analysis methodologies related to the dynamics of complex systems, it is possible to find out, emergent and
sometimes hidden new habits of electricity usage. Through an initial Critical Mass, involving a multitude of
consumers, each related to more contexts, we evaluate the triggering and spreading of a collective attitude. To
this aim, in this paper, we propose a novel analytical model defining a new concept of critical mass, which
includes centrality measures both in a single layer and in a multilayer social network.
A Firefly Algorithm for Optimizing Spur Gear Parameters Under Non-Lubricated ...irjes
Firefly algorithm is one of the emerging evolutionary approaches for complex and non-linear
optimization problems. It is inspired by natural firefly‟s behavior such as movement of fireflies based on
brightness and by overcoming the constraints such as light absorption, obstacles, distance, etc. In this research,
firefly‟s movement had been simulated computationally to identify the best parameters for spur gear pair by
considering the design and manufacturing constraints. The proposed algorithm was tested with the traditional
design parameters and found the results are at par in less computational time by satisfying the constraints.
The Effect of Orientation of Vortex Generators on Aerodynamic Drag Reduction ...irjes
One of the main reasons for the aerodynamic drag in automotive vehicles is the flow separation
near the vehicle’s rear end. To delay this flow separation, vortex generators are used in recent vehicles. The
vortex generators are commonly used in aircrafts to prevent flow separation. Even though vortex generators
themselves create drag, but they also reduce drag by delaying flow separation at downstream. The overall effect
of vortex generators is more beneficial and proved by experimentation. The effect depends on the shape,size and
orientation of vortex generators. Hence optimized shape with proper orientation is essential for getting better
results.This paper presents the effect of vortex generators at different orientation to the flow field and the
mechanism by which these effects takes place.
An Assessment of The Relationship Between The Availability of Financial Resou...irjes
The availability of financial resources is an important element in impacting the success of a planning
process for an effective physical planning. The extent to which however, they are articulated in the process
remained elusive both in scholarly and public discourse. The objective of this study wastherefore, to examine
the extent to which financial resources affect physical planning. In doing so, the study examinedwhether
financial resources were adequate or not to facilitate planning processes in Paidha. According to the study
findings,budget prioritization and ceilings are still a challenge in Paidha Town Council. This is partly due
limited level of knowledge of physical planning among the officials of Paidha Town Council. As a result, there
were no dedicated budget line for routine inspection of physical development plan compliance and enforcement
tools in Paidha. In conclusion, in addressing uncoordinated patterns of physical development that characterize
Uganda‟s urban centres, a critical starting point ought to be the analysis of physical planning process. The
research of this kind is not only significant to other emerging urban centres facing poor a road network,
mushrooming informal settlements and poor social services including poor pattern of residential and commercial
developments but also to all institutions that are involved in planning these towns. Knowing the extent of need
for financial influences in planning may assist local authorities to take the processes of planning seriously which
will help enhance the sustainable development of emerging urban centres including Paidha.
The Choice of Antenatal Care and Delivery Place in Surabaya (Based on Prefere...irjes
- Person's desire to do a pregnancy examination is determined by the service place that suits the tastes
and facilities owned by it. Until now, the utilization of antenatal care by pregnant women is still low (Mardiana,
2014). The purpose of the study is to analyze factors affecting the utilization of antenatal care and delivery place
in Surabaya city based on the preferences and choice theory.
Type of survey research is cross sectional approach, the population is mothers who have children aged 1-
12 months in Surabaya. The large sample of 250 mothers who have children aged 1-12 months in 2013 is taken
by simple random sampling technique. Variables of the research are the preference elements and steps, choice
elements and steps, utilization of antenatal care and delivery place. Data were collected through questionnaires
and secondary data were then analyzed with descriptive statistics in the form of a frequency distribution, shown
by the schematic diagram.
The result showed that the preference elements and steps showed almost half (42.9%) desire to give birth
in a health care because of information got from someone else, while the choice element and step shows the
bulk (57.1%) of the criteria of delivery place chosen is a safe, comfortable and cheap delivery place, the labor
place which is the main choice most (57.1%) is cheap, comfortable, close.
Conclusion of the research based on the preferences and choice theory can be found three (3) new
theories, they are preferences become choice, preferences do not become choice, choice is preceded by
preferences
PHP Frameworks: I want to break free (IPC Berlin 2024)Ralf Eggert
In this presentation, we examine the challenges and limitations of relying too heavily on PHP frameworks in web development. We discuss the history of PHP and its frameworks to understand how this dependence has evolved. The focus will be on providing concrete tips and strategies to reduce reliance on these frameworks, based on real-world examples and practical considerations. The goal is to equip developers with the skills and knowledge to create more flexible and future-proof web applications. We'll explore the importance of maintaining autonomy in a rapidly changing tech landscape and how to make informed decisions in PHP development.
This talk is aimed at encouraging a more independent approach to using PHP frameworks, moving towards a more flexible and future-proof approach to PHP development.
State of ICS and IoT Cyber Threat Landscape Report 2024 previewPrayukth K V
The IoT and OT threat landscape report has been prepared by the Threat Research Team at Sectrio using data from Sectrio, cyber threat intelligence farming facilities spread across over 85 cities around the world. In addition, Sectrio also runs AI-based advanced threat and payload engagement facilities that serve as sinks to attract and engage sophisticated threat actors, and newer malware including new variants and latent threats that are at an earlier stage of development.
The latest edition of the OT/ICS and IoT security Threat Landscape Report 2024 also covers:
State of global ICS asset and network exposure
Sectoral targets and attacks as well as the cost of ransom
Global APT activity, AI usage, actor and tactic profiles, and implications
Rise in volumes of AI-powered cyberattacks
Major cyber events in 2024
Malware and malicious payload trends
Cyberattack types and targets
Vulnerability exploit attempts on CVEs
Attacks on counties – USA
Expansion of bot farms – how, where, and why
In-depth analysis of the cyber threat landscape across North America, South America, Europe, APAC, and the Middle East
Why are attacks on smart factories rising?
Cyber risk predictions
Axis of attacks – Europe
Systemic attacks in the Middle East
Download the full report from here:
https://sectrio.com/resources/ot-threat-landscape-reports/sectrio-releases-ot-ics-and-iot-security-threat-landscape-report-2024/
Neuro-symbolic is not enough, we need neuro-*semantic*Frank van Harmelen
Neuro-symbolic (NeSy) AI is on the rise. However, simply machine learning on just any symbolic structure is not sufficient to really harvest the gains of NeSy. These will only be gained when the symbolic structures have an actual semantics. I give an operational definition of semantics as “predictable inference”.
All of this illustrated with link prediction over knowledge graphs, but the argument is general.
Builder.ai Founder Sachin Dev Duggal's Strategic Approach to Create an Innova...Ramesh Iyer
In today's fast-changing business world, Companies that adapt and embrace new ideas often need help to keep up with the competition. However, fostering a culture of innovation takes much work. It takes vision, leadership and willingness to take risks in the right proportion. Sachin Dev Duggal, co-founder of Builder.ai, has perfected the art of this balance, creating a company culture where creativity and growth are nurtured at each stage.
LF Energy Webinar: Electrical Grid Modelling and Simulation Through PowSyBl -...DanBrown980551
Do you want to learn how to model and simulate an electrical network from scratch in under an hour?
Then welcome to this PowSyBl workshop, hosted by Rte, the French Transmission System Operator (TSO)!
During the webinar, you will discover the PowSyBl ecosystem as well as handle and study an electrical network through an interactive Python notebook.
PowSyBl is an open source project hosted by LF Energy, which offers a comprehensive set of features for electrical grid modelling and simulation. Among other advanced features, PowSyBl provides:
- A fully editable and extendable library for grid component modelling;
- Visualization tools to display your network;
- Grid simulation tools, such as power flows, security analyses (with or without remedial actions) and sensitivity analyses;
The framework is mostly written in Java, with a Python binding so that Python developers can access PowSyBl functionalities as well.
What you will learn during the webinar:
- For beginners: discover PowSyBl's functionalities through a quick general presentation and the notebook, without needing any expert coding skills;
- For advanced developers: master the skills to efficiently apply PowSyBl functionalities to your real-world scenarios.
Transcript: Selling digital books in 2024: Insights from industry leaders - T...BookNet Canada
The publishing industry has been selling digital audiobooks and ebooks for over a decade and has found its groove. What’s changed? What has stayed the same? Where do we go from here? Join a group of leading sales peers from across the industry for a conversation about the lessons learned since the popularization of digital books, best practices, digital book supply chain management, and more.
Link to video recording: https://bnctechforum.ca/sessions/selling-digital-books-in-2024-insights-from-industry-leaders/
Presented by BookNet Canada on May 28, 2024, with support from the Department of Canadian Heritage.
Kubernetes & AI - Beauty and the Beast !?! @KCD Istanbul 2024Tobias Schneck
As AI technology is pushing into IT I was wondering myself, as an “infrastructure container kubernetes guy”, how get this fancy AI technology get managed from an infrastructure operational view? Is it possible to apply our lovely cloud native principals as well? What benefit’s both technologies could bring to each other?
Let me take this questions and provide you a short journey through existing deployment models and use cases for AI software. On practical examples, we discuss what cloud/on-premise strategy we may need for applying it to our own infrastructure to get it to work from an enterprise perspective. I want to give an overview about infrastructure requirements and technologies, what could be beneficial or limiting your AI use cases in an enterprise environment. An interactive Demo will give you some insides, what approaches I got already working for real.
GraphRAG is All You need? LLM & Knowledge GraphGuy Korland
Guy Korland, CEO and Co-founder of FalkorDB, will review two articles on the integration of language models with knowledge graphs.
1. Unifying Large Language Models and Knowledge Graphs: A Roadmap.
https://arxiv.org/abs/2306.08302
2. Microsoft Research's GraphRAG paper and a review paper on various uses of knowledge graphs:
https://www.microsoft.com/en-us/research/blog/graphrag-unlocking-llm-discovery-on-narrative-private-data/
"Impact of front-end architecture on development cost", Viktor TurskyiFwdays
I have heard many times that architecture is not important for the front-end. Also, many times I have seen how developers implement features on the front-end just following the standard rules for a framework and think that this is enough to successfully launch the project, and then the project fails. How to prevent this and what approach to choose? I have launched dozens of complex projects and during the talk we will analyze which approaches have worked for me and which have not.
UiPath Test Automation using UiPath Test Suite series, part 4DianaGray10
Welcome to UiPath Test Automation using UiPath Test Suite series part 4. In this session, we will cover Test Manager overview along with SAP heatmap.
The UiPath Test Manager overview with SAP heatmap webinar offers a concise yet comprehensive exploration of the role of a Test Manager within SAP environments, coupled with the utilization of heatmaps for effective testing strategies.
Participants will gain insights into the responsibilities, challenges, and best practices associated with test management in SAP projects. Additionally, the webinar delves into the significance of heatmaps as a visual aid for identifying testing priorities, areas of risk, and resource allocation within SAP landscapes. Through this session, attendees can expect to enhance their understanding of test management principles while learning practical approaches to optimize testing processes in SAP environments using heatmap visualization techniques
What will you get from this session?
1. Insights into SAP testing best practices
2. Heatmap utilization for testing
3. Optimization of testing processes
4. Demo
Topics covered:
Execution from the test manager
Orchestrator execution result
Defect reporting
SAP heatmap example with demo
Speaker:
Deepak Rai, Automation Practice Lead, Boundaryless Group and UiPath MVP
UiPath Test Automation using UiPath Test Suite series, part 4
PSoC BASED SPEECH RECOGNITION SYSTEM
1. International Refereed Journal of Engineering and Science (IRJES)
ISSN (Online) 2319-183X, (Print) 2319-1821
Volume 4, Issue 3 (March 2015), PP.01-07
www.irjes.com 1 | Page
PSoC BASED SPEECH RECOGNITION SYSTEM
1
Shubhasini Sugumaran, 2
Mr.V.R.Prakash
1
Department of Electronics and Communication Hindustan University Chennai, India
2
Department of Electronics and Communication Hindustan University Chennai,India
Abstract:– Speech Recognition Systems(SRS) have been implemented by various processors including the
digital signal processors(DSPs) and field programmable gate arrays(FPGAs) and their performance has been
reported in literature. The fundamental purpose of speech is communication, i.e., the transmission of
messages.In the case of speech, the fundamental analog form of the message is an acoustic waveform, which we
call the speech signal. Speech signals can be converted to an electrical waveform by a microphone, further
manipulated by both analog and digital signal processing, and then converted back to acoustic form by a
loudspeaker, a telephone handset or headphone, as desired.The recognition of speech requires feature extraction
and classification. The systems that use speech as input require a microcontroller to carry out the desired
actions. In this paper, Cypress Programmable System on Chip (PSoC) has been studied and used for
implementation of SRS. From all the available PSoCs, PSoC5 containing ARM Cortex-M3 as its CPU is used.
The noise signals are firstly nullified from the speech signals using LogMMSE filtering. These signals are then
sent to the PSoC5 wherein the speech is recognized and desired actions are performed.
Keywords: PSoC, LogMMSE, Speech Recognition
I. INTRODUCTION
The basic idea of speech is the transmission of messages. A message is represented as a sequence of
discrete symbols that quantifies its information in bits and the rate at which information is transmitted as bits per
second (bps). Speech recognition techniques have seemed to be more efficient and convenient for human-
machine interaction. The speech recognition systems with fixed vocabulary were deployed in many
applications[8] and [9]. Speech recognition systems for voice operated application have been implemented using
various hardware platforms such as the DSPs [3], FPGAs [5] and microprocessors [10]. In speech production,
the information to be transmitted is encoded in the form of a continuously varying analog waveform that can be
transmitted, recorded, manipulated, and ultimately decoded by a human listener. This analog signal is the speech
signal. These signals tend to be corrupted by noise in the real world. If the noise can be estimated from the noise
source, this estimated noise can then be subtracted from the primary channel resulting in the desired signal. This
task is usually done by linear filtering. In real time situations, the corrupting noise is a nonlinear distortion
version of the source noise, so a nonlinear filter should be a better choice. To reduce the influence of noise in the
speech, speech enhancement is done. The recognition algorithm without the use of enhancement algorithms
proved to be less efficient.
Programmable System on Chip (PSoC) have and are being employed in a number of applications. They
are cost effective due to which they have limited storage and computational power. In context to this, the
recognition accuracy becomes important for PSoC and is addressed in the paper.
II. PROGRAMMABLE SYSTEM ON CHIP (PSOC)
Programmable System on Chip(PSoC) has been designed and implemented by Cypress semiconductors
[2] and [4]. Every PSoC contains a microcontroller, programmable analog blocks such as ADC, DAC, I/O
drivers and digital blocks such as Universal Digital Blocks (UDBs), CAN, I2C, PWM in a single chip.
Embedded Development kits from Cypress contain one of the three PSoCs – PsoC1, PSoC3 and PSoC5. The
processing performance, functionality, internal memories and configurability of the PSoC increases from
PSoC1through PSoc5.
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Table 1: Comparison of PSoCs
PSoC5 uses PSoC Creator for its development and implementation. PSoC Creator is a visual
development tool and Integrated Development Environment for PSoC. It has a rich library of prebuilt
components and a schematic design entry tool. It combines C based development flow with an automatically
generated Application programmable interface (API). API rduces the errors in code and ensures proper
interfacing with the peripheral devices which enables the software development to be faster, easier and less
prone to errors. The PSoC Creator also has powerful, modern debugger, which is built in the IDE. It is used to
display the values after execution at each point.
III. SPEECH RECOGNITION SYSTEM
The block diagram is as shown in Fig.1 below.
Speech Recognition System
The speech is given as input through a microphone. The given speech might contain external
disturbances called noise. This noise is cancelled using LogMMSE algorithm. The speech signal after noise
cancellation is amplified and filtered to remove further disturbances in the signal. The speech signal in analog
form is then converted into digital signal using inbuilt analog to digital converter of PSoC. The feature
extraction and pattern recognition is done using MFCC algorithm. The analog to digital conversion is done
using delta sigma ADC present in PSoC5.
The sampling rate of ADC can be adjusted depending on the speech signal as required. The delta sigma
ADC contains three blocks – an amplifier, a modulator and a decimator. The decimator is a four stage CIC
decimation filter. It also contains a post processing unit. Continuous mode of the ADC is being used for
conversion. The output of the speech recognition system is shown through the movement of a robot in different
directions.
FEATURES PSoC1 PSoC3 PSoC5
CPU 8-bit M8C
core
8-bit 8051 32-bit ARM
Cortex
Flash 4 to 32kB 8 to 64kB 32 to 256kB
Interface I²C, SPI,
UART,
FS USB 2.0
I²C, SPI,
UART,
LIN,
FS USB
2.0, I²S,
CAN
I²C, SPI,
UART, LIN,
FS USB 2.0,
I²S,CAN
ADCs 1 delta-
sigma
1 Delta-
Sigma
1 Delta-Sigma,
2SARs
DACs 2(6 bit) 4(8 bit) 4(8 bit)
I/Os 64 72 72
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IV. TECHNIQUES USED
The performance of the SRS degrades when implemented in real world environment. This degradation
is due to acoustic model mismatch. The acoustic model mismatch describes the difference between the
environment in which the SRS is tested and the actual environment in which it is deployed. This can include
echoes, background noise, speaker variability and transmission effects.
1. Log MMSE Filtering
Fig.2 Noise reduction using Log MMSE
1.1 Preprocessing
In preprocessing of audio signals start with pre-emphasis refers to a system process designed to
increase the magnitude of some frequencies with respect to the magnitude of other frequencies in order to
improve the overall signal-to-noise ratio by minimizing the adverse effects of such phenomena as attenuation
distortion or saturation of recording media in subsequent parts of the system. The mirror operation is called de-
emphasis, and the system as a whole is called emphasis.
Pre-emphasis is achieved with a pre-emphasis network which is essentially a calibrated filter. This
network composed of two resistors and one capacitor. The frequency response is decided by special time
constants. The cutoff frequency can be calculated from that value. Pre-emphasis is commonly used
in telecommunications, digital audio recording, record cutting, in FM broadcasting transmissions, and in
displaying the spectrograms of speech signals.
De-emphasis is the complement of pre-emphasis, in the anti noise system called emphasis. Emphasis is
a system process designed to decrease, (within a band of frequencies), the magnitude of some (usually higher)
frequencies with respect to the magnitude of other (usually lower) frequencies in order to improve the overall
signal-to-noise ratio by minimizing the adverse effects of such phenomena as attenuation differences or
saturation of recording media in subsequent parts of the system.
1.2 Segment
The signal samples are segmented into fixed number of frames and each frame samples are evaluated with
hamming window coefficients.
The total frames are calculated by,
Fn = (Ls – Ns)/ (Ns*Sp) +1
Where,
Ls = length of signal
Ns = Length of each frame
Sp = Shift Percentage
Finally the samples of each frames are separated from input signal using Fn and Sp and its scaled by the
hamming window coefficients.
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Fig.3 Segmented signal
1.3 Filtering
After the signal segmentation, the magnitude and phase spectrum from noisy signal are computed by
applying fast fourier transform.The magnitude of noisy signal spectrum is further utilized for filtering process
and signal phase kept same.
The restored signal magnitude spectra is obtained by,
Rs = G .* Y
Where, G – Log spectral amplitude Gain function
Y – Magnitude response of noisy signal
The log spectral gain function is defined by,
G = x./(1+x) exp(eint (v))
Where, v = x./(1+x) * r
x and r– Priori and posteriori signal to noise ratio
eint – Exponential integral
The posteriori snr is defined by,
r = (Y.^2)/ lamda
lamda = E[(Y).^2]
Where, lamda - Noise power spectrum variance
E – Mean value
Complex spectrogram obtained by Filtered magnitude spectrum is combined with noisy signal phase spectrum.
The restored signal is reconstructed by applying inverse fast fourier transform to this complex spectrogram.The
performance of filtering is measured with SNR evaluation and it is defined by,
SNR= 10log10 (Msig^2/(sum(in-out)^2/Ls))
Where, Msig = Maximum amplitude of signal
in, out= Noisy input signal and restored output.
1.4 Concatenate
The signals that were obtained on segmentation are now filtered and the noise content is reduced. These signals
are then concatenated to reform the original signal.
1.5 Restore
The restored noiseless signal is restored to its original form.
2. MEL FREQUENCY CEPSTRUM COEFFICIENT(MFCC)
To increase the robustness in the frame selection process, a robust feature extraction with short time
Fourier transform (STFT) domain uncertainty propagation (STFT-UP) was used. Our implementation followed
using STFT-UP to compute a minimum mean square error (MMSE) estimate directly in the mel-frequency
cepstral coefficient (MFCC) domain. For this particular implementation, amplitude based MFCCs with cepstral
mean subtraction were used to attain improved performance.
0 20 40 60 80 100 120 140 160 180 200
-0.06
-0.04
-0.02
0
0.02
0.04
0.06
0 20 40 60 80 100 120
0
0.1
0.2
0.3
0.4
0.5
0.6
0.7
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Fig. 4 MFCC
In speech recognition, the Mel-frequency cepstrum (MFC) is a representation of the shortterm power
spectrum of a sound, based on a linear cosine transform of a log power spectrum on a nonlinear Mel scale of
frequency.
MFCC = DCT [ LOG [ ABS [ FFT (SPEECH) ]]]
Mel-frequency cepstral coefficients (MFCCs) are coefficients that collectively make up an MFC. The difference
between the cepstrum and the mel-frequency cepstrum is that in the MFC, the frequency bands are equally
spaced on the mel scale, which approximates the human auditory system's response more closely than the
linearly spaced frequency bands used in the normal cepstrum. This frequency warping can allow for better
representation of sound.
V. TRAINING AND TESTING
The goal of the system training and inventory design stage is twofold: we need to divide the inventory
into collections of phonetically similar segments with varying lengths and we need to arrive at a statistical
description that tells us which set of collections is most likely to contain the inventory subsection that best
matches the underlying clean frame of an incoming noisy frame . The division of the inventory into the
collections is performed in a step-by-step fashion. First, is segmented and all silent segments are removed. The
non-silent part of the inventory is then divided into sections that each belong to one of 40 phonetic classes.
We are applying the feature extraction to the entire segment stream of the inventory. Because the inventory
signal is assumed to be virtually undistorted, it is sufficient to only retain the resulting short-time MFCC feature
means and to discard the associated variance estimates. The feature means become, thereby, essentially feature
vectors in their own right and we can develop a cluster model for them. We have decided to use the means and
not the actual cepstral vectors at this stage to ensure that the impact of the mean-extraction-processing is
captured in our feature representation.
VI. RESULTS
Fig. 5 Noisy Signal
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Fig. 6 Log MMSE Filtering
Fig. 7 MFCC Feature Extraction
For experimental basis, speech signals from noisy environments were taken. The result shown is fr a
signal in the airport. The noise is cancelled using LogMMSE Filtering and feature extraction is done by MFCC.
VI. CONCLUSION
In this paper speech recognition is done and appliances are controlled using speech commands. The
commands are given by the user in the form of speech. These signals are filtered using LogMMSE filtering due
to which environmental noise is nullified. Further as a part of feature extraction, MFCC is used. A database is
created where all the commands are saved. These commands are then given as input to the PSoC5 kit where the
PSoC is programmed to give the desired result. According to the PSoC, the robot connected to the PSoC moves
in different directions as specified.
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