The document describes a system for spoken web search using audio queries in multiple languages. It discusses using parallel tokenizers followed by dynamic time warping detection to combine multiple resources for query matching. Unsupervised tokenizers like MFCC-GMM and phoneme recognizers are used to extract posteriorgrams from queries and test utterances. Pseudo-relevance feedback and score normalization are also used. Evaluation on the development and evaluation sets shows the best performance is achieved when combining all tokenizers, pseudo-relevance feedback, and score normalization.
Algorithms for extraction and visualization of
metadata from Domain Name Server records -- 2010 Third International Conference on Advances in Mesh Networks
Quality Assessment for Recognition and Task-based multimedia applications (QART)Mikołaj Leszczuk
Users of video to perform tasks require sufficient video quality to recognize the information needed for their application. Therefore, the fundamental measure of video quality in these applications is the success rate of these tasks (such as recognition), which is referred to as visual intelligibility or acuity. One of the major causes of reduction of visual intelligibility is loss of data, through various forms of compression. Additionally, the characteristics of the scene being captured have a direct effect on visual intelligibility and on the performance of a compression operation-specifically, the size of the target of interest, the lighting conditions, and the temporal complexity of the scene. The QART project is performing a series of tests to study the effects and interactions of compression and scene characteristics. An additional goal is to test existing or develop new objective measurements that will predict the results of the subjective tests of visual intelligibility.
IJERA (International journal of Engineering Research and Applications) is International online, ... peer reviewed journal. For more detail or submit your article, please visit www.ijera.com
Algorithms for extraction and visualization of
metadata from Domain Name Server records -- 2010 Third International Conference on Advances in Mesh Networks
Quality Assessment for Recognition and Task-based multimedia applications (QART)Mikołaj Leszczuk
Users of video to perform tasks require sufficient video quality to recognize the information needed for their application. Therefore, the fundamental measure of video quality in these applications is the success rate of these tasks (such as recognition), which is referred to as visual intelligibility or acuity. One of the major causes of reduction of visual intelligibility is loss of data, through various forms of compression. Additionally, the characteristics of the scene being captured have a direct effect on visual intelligibility and on the performance of a compression operation-specifically, the size of the target of interest, the lighting conditions, and the temporal complexity of the scene. The QART project is performing a series of tests to study the effects and interactions of compression and scene characteristics. An additional goal is to test existing or develop new objective measurements that will predict the results of the subjective tests of visual intelligibility.
IJERA (International journal of Engineering Research and Applications) is International online, ... peer reviewed journal. For more detail or submit your article, please visit www.ijera.com
A Novel Method for Speaker Independent Recognition Based on Hidden Markov ModelIDES Editor
In this paper, we address the speaker independent
recognition of Chinese number speeches 0~9 based on HMM.
Our former results of inside and outside testing achieved
92.5% and 76.79% respectively. To improve further the
performance, two important features of speech; MFCC and
cluster number of vector quantification, are unified together
and evaluated on various values. The best performance
achieve 96.2% and 83.1% on MFCC Number = 20 and VQ
clustering number = 64.
Emotion Recognition based on audio signal using GFCC Extraction and BPNN Clas...ijceronline
International Journal of Computational Engineering Research (IJCER) is dedicated to protecting personal information and will make every reasonable effort to handle collected information appropriately. All information collected, as well as related requests, will be handled as carefully and efficiently as possible in accordance with IJCER standards for integrity and objectivity.
Text Prompted Remote Speaker Authentication : Joint Speech and Speaker Recogn...gt_ebuddy
Joint Speech and Speaker Recognition using Hidden Markov Model/Vector Quantization for speaker independent Speech Recognition and Gaussian Mixture Model for speech independent speaker recognition- used MFCC (Mel-Frequency Cepstral Coefficient) for Feature Extraction (delta,delta delta and energy - 39 coefficients).
Developed in JAVA with client/server Architecture, web interface developed in Adobe Flex.
This project was done at TU, IOE - Pulchowk Campus, Nepal.
For more details visit http://ganeshtiwaridotcomdotnp.blogspot.com
ABSTRACT OF PROJECT>>>
Biometric is physical characteristic unique to each individual. It has a very useful application in authentication and access control.
The designed system is a text-prompted version of voice biometric which incorporates text-independent speaker verification and speaker-independent speech verification system implemented independently. The foundation for this joint system is that the speech signal conveys both the speech content and speaker identity. Such systems are more-secure from playback attack, since the word to speak during authentication is not previously set.
During the course of the project various digital signal processing and pattern classification algorithms were studied. Short time spectral analysis was performed to obtain MFCC, energy and their deltas as feature. Feature extraction module is same for both systems. Speaker modeling was done by GMM and Left to Right Discrete HMM with VQ was used for isolated word modeling. And results of both systems were combined to authenticate the user.
The speech model for each word was pre-trained by using utterance of 45 English words. The speaker model was trained by utterance of about 2 minutes each by 15 speakers. While uttering the individual words, the recognition rate of the speech recognition system is 92 % and speaker recognition system is 66%. For longer duration of utterance (>5sec) the recognition rate of speaker recognition system improves to 78%.
Advance Digital Video Watermarking based on DWT-PCA for Copyright protectionIJERA Editor
Now a days there is use of digital multimedia applications are increased. Digital image watermarking techniques can be classified into spatial or transform domains. The spatial domain methods are the simplest watermarking techniques but have low robustness against different attacks, unlike the transform domains watermarking methods are more complex and have high robustness against various attacks. Most commonly used methods of watermarking are discrete cosine transform (DCT), discrete wavelet transform (DWT).A hybrid digital video watermarking scheme based on Discrete Wavelet Transform (DWT) and Principal Component Analysis (PCA). These transform domain technique always give more robust output than DCT and DWT The video frames are first decomposed using DWT and the binary watermark is embedded in the principal components of the low frequency wavelet coefficients Here in order to improve the robustness of water mark Haar filtering must be used in order to get PSNR as much as possible Experimental result shows no visible difference between the watermarked frames and original frame. It shows robustness on the watermarked video against various attacks. Peak signal to noise ratio (PSNR) is calculated to measure efficiency of this all methods. And this value must be increased up to the level.
International Journal of Computational Engineering Research(IJCER) ijceronline
nternational Journal of Computational Engineering Research (IJCER) is dedicated to protecting personal information and will make every reasonable effort to handle collected information appropriately. All information collected, as well as related requests, will be handled as carefully and efficiently as possible in accordance with IJCER standards for integrity and objectivity.
Contribution of Non-Scrambled Chroma Information in Privacy-Protected Face Im...Wesley De Neve
Contribution of Non-Scrambled Chroma Information in Privacy-Protected Face Images to Privacy Leakage. Presentation given at the 10th International Workshop on Digital Forensics and Watermarking (IWDW'11).
Note that a more extensive objective and subjective study of privacy protection in video surveillance systems can be found in the following book chapter:
H. Sohn, D. Lee, W. De Neve, K.N. Plataniotis, and Y.M. Ro. An objective and subjective evaluation of content-based privacy protection of face images in video surveillance systems using JPEG XR. Effective Surveillance for Homeland Security: Balancing Technology and Social Issues. CRC Press / Taylor & Francis. May 2013. pp. 111-140.
http://www.citeulike.org/user/wmdeneve/article/10831550
http://www.crcpress.com/product/isbn/9781439883242
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.
Design of Optimal Linear Phase FIR High Pass Filter using Improved Particle S...IDES Editor
This paper presents a novel approach for designing
a linear phase digital high pass FIR filter using Improved
Particle Swarm Optimization (IPSO) algorithm. Design of
FIR filter is a multi-modal optimization problem. The
conservative gradient based optimization techniques are not
efficient for digital filter design. Given the specifications for
the filters to be realized, IPSO algorithm generates a set of
optimal filter coefficients and tries to meet the ideal frequency
response characteristics. This paper presents the realization
of the optimal FIR high pass filter of filter order 20 as per
given problem statements. The simulation results have been
compared to those obtained from well accepted classical
algorithms like Park and McClellan algorithm (PM), and
evolutionary algorithms like genetic algorithm (GA) and
particle swarm optimization (PSO). The results rationalize
that the proposed optimal filter design approach using IPSO
outperforms PM, RGA, PSO in the accuracy of the designed
filter, as well as in the convergence speed and solution quality
Realization and design of a pilot assist decision making system based on spee...csandit
A system based on speech recognition is proposed fo
r pilot assist decision-making. It is based
on a HIL aircraft simulation platform and uses the
microcontroller SPCE061A as the central
processor to achieve better reliability and higher
cost-effect performance. Technologies of
LPCC (linear predictive cepstral coding) and DTW (D
ynamic Time Warping) are applied for
isolated-word speech recognition to gain a smaller
amount of calculation and a better real-time
performance. Besides, we adopt the PWM (Pulse Width
Modulation) regulation technology to
effectively regulate each control surface by speech
, and thus to assist the pilot to make decisions.
By trial and error, it is proved that we have a sat
isfactory accuracy rate of speech recognition
and control effect. More importantly, our paper pro
vides a creative idea for intelligent human-
computer interaction and applications of speech rec
ognition in the field of aviation control. Our
system is also very easy to be extended and applied
⭐⭐⭐⭐⭐ Localización en ambiente de interiores basado en Machine Learning con r...Victor Asanza
Diseño de un método pasivo de ubicación de una persona en ambiente de interiores basado en aprendizaje automático con datos obtenidos a partir de enlaces de comunicaciones en la banda de 28 GHz
➡️ #DigitalSystems #DigitalElectronic #DigitalCircuits #HDL #VHDL #FPGA
⭐ Para más contenido visita nuestro blog:
https://vasanza.blogspot.com/
A Novel Method for Speaker Independent Recognition Based on Hidden Markov ModelIDES Editor
In this paper, we address the speaker independent
recognition of Chinese number speeches 0~9 based on HMM.
Our former results of inside and outside testing achieved
92.5% and 76.79% respectively. To improve further the
performance, two important features of speech; MFCC and
cluster number of vector quantification, are unified together
and evaluated on various values. The best performance
achieve 96.2% and 83.1% on MFCC Number = 20 and VQ
clustering number = 64.
Emotion Recognition based on audio signal using GFCC Extraction and BPNN Clas...ijceronline
International Journal of Computational Engineering Research (IJCER) is dedicated to protecting personal information and will make every reasonable effort to handle collected information appropriately. All information collected, as well as related requests, will be handled as carefully and efficiently as possible in accordance with IJCER standards for integrity and objectivity.
Text Prompted Remote Speaker Authentication : Joint Speech and Speaker Recogn...gt_ebuddy
Joint Speech and Speaker Recognition using Hidden Markov Model/Vector Quantization for speaker independent Speech Recognition and Gaussian Mixture Model for speech independent speaker recognition- used MFCC (Mel-Frequency Cepstral Coefficient) for Feature Extraction (delta,delta delta and energy - 39 coefficients).
Developed in JAVA with client/server Architecture, web interface developed in Adobe Flex.
This project was done at TU, IOE - Pulchowk Campus, Nepal.
For more details visit http://ganeshtiwaridotcomdotnp.blogspot.com
ABSTRACT OF PROJECT>>>
Biometric is physical characteristic unique to each individual. It has a very useful application in authentication and access control.
The designed system is a text-prompted version of voice biometric which incorporates text-independent speaker verification and speaker-independent speech verification system implemented independently. The foundation for this joint system is that the speech signal conveys both the speech content and speaker identity. Such systems are more-secure from playback attack, since the word to speak during authentication is not previously set.
During the course of the project various digital signal processing and pattern classification algorithms were studied. Short time spectral analysis was performed to obtain MFCC, energy and their deltas as feature. Feature extraction module is same for both systems. Speaker modeling was done by GMM and Left to Right Discrete HMM with VQ was used for isolated word modeling. And results of both systems were combined to authenticate the user.
The speech model for each word was pre-trained by using utterance of 45 English words. The speaker model was trained by utterance of about 2 minutes each by 15 speakers. While uttering the individual words, the recognition rate of the speech recognition system is 92 % and speaker recognition system is 66%. For longer duration of utterance (>5sec) the recognition rate of speaker recognition system improves to 78%.
Advance Digital Video Watermarking based on DWT-PCA for Copyright protectionIJERA Editor
Now a days there is use of digital multimedia applications are increased. Digital image watermarking techniques can be classified into spatial or transform domains. The spatial domain methods are the simplest watermarking techniques but have low robustness against different attacks, unlike the transform domains watermarking methods are more complex and have high robustness against various attacks. Most commonly used methods of watermarking are discrete cosine transform (DCT), discrete wavelet transform (DWT).A hybrid digital video watermarking scheme based on Discrete Wavelet Transform (DWT) and Principal Component Analysis (PCA). These transform domain technique always give more robust output than DCT and DWT The video frames are first decomposed using DWT and the binary watermark is embedded in the principal components of the low frequency wavelet coefficients Here in order to improve the robustness of water mark Haar filtering must be used in order to get PSNR as much as possible Experimental result shows no visible difference between the watermarked frames and original frame. It shows robustness on the watermarked video against various attacks. Peak signal to noise ratio (PSNR) is calculated to measure efficiency of this all methods. And this value must be increased up to the level.
International Journal of Computational Engineering Research(IJCER) ijceronline
nternational Journal of Computational Engineering Research (IJCER) is dedicated to protecting personal information and will make every reasonable effort to handle collected information appropriately. All information collected, as well as related requests, will be handled as carefully and efficiently as possible in accordance with IJCER standards for integrity and objectivity.
Contribution of Non-Scrambled Chroma Information in Privacy-Protected Face Im...Wesley De Neve
Contribution of Non-Scrambled Chroma Information in Privacy-Protected Face Images to Privacy Leakage. Presentation given at the 10th International Workshop on Digital Forensics and Watermarking (IWDW'11).
Note that a more extensive objective and subjective study of privacy protection in video surveillance systems can be found in the following book chapter:
H. Sohn, D. Lee, W. De Neve, K.N. Plataniotis, and Y.M. Ro. An objective and subjective evaluation of content-based privacy protection of face images in video surveillance systems using JPEG XR. Effective Surveillance for Homeland Security: Balancing Technology and Social Issues. CRC Press / Taylor & Francis. May 2013. pp. 111-140.
http://www.citeulike.org/user/wmdeneve/article/10831550
http://www.crcpress.com/product/isbn/9781439883242
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.
Design of Optimal Linear Phase FIR High Pass Filter using Improved Particle S...IDES Editor
This paper presents a novel approach for designing
a linear phase digital high pass FIR filter using Improved
Particle Swarm Optimization (IPSO) algorithm. Design of
FIR filter is a multi-modal optimization problem. The
conservative gradient based optimization techniques are not
efficient for digital filter design. Given the specifications for
the filters to be realized, IPSO algorithm generates a set of
optimal filter coefficients and tries to meet the ideal frequency
response characteristics. This paper presents the realization
of the optimal FIR high pass filter of filter order 20 as per
given problem statements. The simulation results have been
compared to those obtained from well accepted classical
algorithms like Park and McClellan algorithm (PM), and
evolutionary algorithms like genetic algorithm (GA) and
particle swarm optimization (PSO). The results rationalize
that the proposed optimal filter design approach using IPSO
outperforms PM, RGA, PSO in the accuracy of the designed
filter, as well as in the convergence speed and solution quality
Realization and design of a pilot assist decision making system based on spee...csandit
A system based on speech recognition is proposed fo
r pilot assist decision-making. It is based
on a HIL aircraft simulation platform and uses the
microcontroller SPCE061A as the central
processor to achieve better reliability and higher
cost-effect performance. Technologies of
LPCC (linear predictive cepstral coding) and DTW (D
ynamic Time Warping) are applied for
isolated-word speech recognition to gain a smaller
amount of calculation and a better real-time
performance. Besides, we adopt the PWM (Pulse Width
Modulation) regulation technology to
effectively regulate each control surface by speech
, and thus to assist the pilot to make decisions.
By trial and error, it is proved that we have a sat
isfactory accuracy rate of speech recognition
and control effect. More importantly, our paper pro
vides a creative idea for intelligent human-
computer interaction and applications of speech rec
ognition in the field of aviation control. Our
system is also very easy to be extended and applied
⭐⭐⭐⭐⭐ Localización en ambiente de interiores basado en Machine Learning con r...Victor Asanza
Diseño de un método pasivo de ubicación de una persona en ambiente de interiores basado en aprendizaje automático con datos obtenidos a partir de enlaces de comunicaciones en la banda de 28 GHz
➡️ #DigitalSystems #DigitalElectronic #DigitalCircuits #HDL #VHDL #FPGA
⭐ Para más contenido visita nuestro blog:
https://vasanza.blogspot.com/
[2017-05-29] DNASmartTagger : Development of DNA sequence tagging tools based on machine learning using public sequence annotation data, NIG International Symposium 2017.
Realtime, Non-Intrusive Evaluation of VoIP Using Genetic Programmingadil raja
Realtime, Non-Intrusive Evaluation of VoIP Using Genetic Programming
A presentation made and delivered for our entry in human competitive awards competition in GECCO 2007.
Essentials of Automations: Optimizing FME Workflows with ParametersSafe Software
Are you looking to streamline your workflows and boost your projects’ efficiency? Do you find yourself searching for ways to add flexibility and control over your FME workflows? If so, you’re in the right place.
Join us for an insightful dive into the world of FME parameters, a critical element in optimizing workflow efficiency. This webinar marks the beginning of our three-part “Essentials of Automation” series. This first webinar is designed to equip you with the knowledge and skills to utilize parameters effectively: enhancing the flexibility, maintainability, and user control of your FME projects.
Here’s what you’ll gain:
- Essentials of FME Parameters: Understand the pivotal role of parameters, including Reader/Writer, Transformer, User, and FME Flow categories. Discover how they are the key to unlocking automation and optimization within your workflows.
- Practical Applications in FME Form: Delve into key user parameter types including choice, connections, and file URLs. Allow users to control how a workflow runs, making your workflows more reusable. Learn to import values and deliver the best user experience for your workflows while enhancing accuracy.
- Optimization Strategies in FME Flow: Explore the creation and strategic deployment of parameters in FME Flow, including the use of deployment and geometry parameters, to maximize workflow efficiency.
- Pro Tips for Success: Gain insights on parameterizing connections and leveraging new features like Conditional Visibility for clarity and simplicity.
We’ll wrap up with a glimpse into future webinars, followed by a Q&A session to address your specific questions surrounding this topic.
Don’t miss this opportunity to elevate your FME expertise and drive your projects to new heights of efficiency.
GDG Cloud Southlake #33: Boule & Rebala: Effective AppSec in SDLC using Deplo...James Anderson
Effective Application Security in Software Delivery lifecycle using Deployment Firewall and DBOM
The modern software delivery process (or the CI/CD process) includes many tools, distributed teams, open-source code, and cloud platforms. Constant focus on speed to release software to market, along with the traditional slow and manual security checks has caused gaps in continuous security as an important piece in the software supply chain. Today organizations feel more susceptible to external and internal cyber threats due to the vast attack surface in their applications supply chain and the lack of end-to-end governance and risk management.
The software team must secure its software delivery process to avoid vulnerability and security breaches. This needs to be achieved with existing tool chains and without extensive rework of the delivery processes. This talk will present strategies and techniques for providing visibility into the true risk of the existing vulnerabilities, preventing the introduction of security issues in the software, resolving vulnerabilities in production environments quickly, and capturing the deployment bill of materials (DBOM).
Speakers:
Bob Boule
Robert Boule is a technology enthusiast with PASSION for technology and making things work along with a knack for helping others understand how things work. He comes with around 20 years of solution engineering experience in application security, software continuous delivery, and SaaS platforms. He is known for his dynamic presentations in CI/CD and application security integrated in software delivery lifecycle.
Gopinath Rebala
Gopinath Rebala is the CTO of OpsMx, where he has overall responsibility for the machine learning and data processing architectures for Secure Software Delivery. Gopi also has a strong connection with our customers, leading design and architecture for strategic implementations. Gopi is a frequent speaker and well-known leader in continuous delivery and integrating security into software delivery.
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.
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.
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/
Slack (or Teams) Automation for Bonterra Impact Management (fka Social Soluti...Jeffrey Haguewood
Sidekick Solutions uses Bonterra Impact Management (fka Social Solutions Apricot) and automation solutions to integrate data for business workflows.
We believe integration and automation are essential to user experience and the promise of efficient work through technology. Automation is the critical ingredient to realizing that full vision. We develop integration products and services for Bonterra Case Management software to support the deployment of automations for a variety of use cases.
This video focuses on the notifications, alerts, and approval requests using Slack for Bonterra Impact Management. The solutions covered in this webinar can also be deployed for Microsoft Teams.
Interested in deploying notification automations for Bonterra Impact Management? Contact us at sales@sidekicksolutionsllc.com to discuss next steps.
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 3DianaGray10
Welcome to UiPath Test Automation using UiPath Test Suite series part 3. In this session, we will cover desktop automation along with UI automation.
Topics covered:
UI automation Introduction,
UI automation Sample
Desktop automation flow
Pradeep Chinnala, Senior Consultant Automation Developer @WonderBotz and UiPath MVP
Deepak Rai, Automation Practice Lead, Boundaryless Group and UiPath MVP
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.
Search and Society: Reimagining Information Access for Radical FuturesBhaskar Mitra
The field of Information retrieval (IR) is currently undergoing a transformative shift, at least partly due to the emerging applications of generative AI to information access. In this talk, we will deliberate on the sociotechnical implications of generative AI for information access. We will argue that there is both a critical necessity and an exciting opportunity for the IR community to re-center our research agendas on societal needs while dismantling the artificial separation between the work on fairness, accountability, transparency, and ethics in IR and the rest of IR research. Instead of adopting a reactionary strategy of trying to mitigate potential social harms from emerging technologies, the community should aim to proactively set the research agenda for the kinds of systems we should build inspired by diverse explicitly stated sociotechnical imaginaries. The sociotechnical imaginaries that underpin the design and development of information access technologies needs to be explicitly articulated, and we need to develop theories of change in context of these diverse perspectives. Our guiding future imaginaries must be informed by other academic fields, such as democratic theory and critical theory, and should be co-developed with social science scholars, legal scholars, civil rights and social justice activists, and artists, among others.
Dev Dives: Train smarter, not harder – active learning and UiPath LLMs for do...UiPathCommunity
💥 Speed, accuracy, and scaling – discover the superpowers of GenAI in action with UiPath Document Understanding and Communications Mining™:
See how to accelerate model training and optimize model performance with active learning
Learn about the latest enhancements to out-of-the-box document processing – with little to no training required
Get an exclusive demo of the new family of UiPath LLMs – GenAI models specialized for processing different types of documents and messages
This is a hands-on session specifically designed for automation developers and AI enthusiasts seeking to enhance their knowledge in leveraging the latest intelligent document processing capabilities offered by UiPath.
Speakers:
👨🏫 Andras Palfi, Senior Product Manager, UiPath
👩🏫 Lenka Dulovicova, Product Program Manager, UiPath
Dev Dives: Train smarter, not harder – active learning and UiPath LLMs for do...
CUHK System for the Spoken Web Search task at Mediaeval 2012
1. Overview System Description System performance Conclusion Acknowledgement
The CUHK Systems for Spoken Web Search task at
MediaEval 2012
Haipeng Wang and Tan Lee
Department of Electronic Engineering
The Chinese University of Hong Kong
September 30, 2012
2. Overview System Description System performance Conclusion Acknowledgement
Outline
1 Overview
2 System Description
PTDTW framework
Tokenizers
DTW detection
Pseudo-relevance Feedback and Score Normalization
3 System configuration and performance
4 Conclusion
5 Acknowledgement
3. Overview System Description System performance Conclusion Acknowledgement
Overview
2012 Spoken Web Search task [Metze et al., 2012]
QbyE STD: Audio search using audio queries.
Multilingual: Four South African languages.
Low-resource: Less than 4-hour DEV audio data in total.
Extreme case: One example for each query term.
Overview of our systems
Aiming at language-independent QbyE STD system.
Multiple resources:
1) the DEV audio data; 2) rich-resource languages.
Combine different resources: PTDTW framework.
Pseudo-relevance feedback (PRF).
Score normalization.
4. Overview System Description System performance Conclusion Acknowledgement
Posteriorgram-based template matching
Training
Resources
Query Query
Example Posteriorgrams
Detection
Tokenizer
Score
Test Test
Utterance Posteriorgrams
DETECT by DTW
Figure: Posteriorgram-based template matching[Hazen et al., 2009]
Training resources: audio data with or without transcriptions.
Tokenizer: if trained without transcriptions, unsupervised;
otherwise, supervised.
Posteriorgrams: more robust than spectral features.
How to effectively combine different resources?
5. Overview System Description System performance Conclusion Acknowledgement
PTDTW framework
Query
Posteriorgrams 1 DTW
Tokenizer 1 distance
Test Matrix D1
Posteriorgrams 1
Query Query
Example Posteriorgrams 2 DTW
Tokenizer 2 distance DTW Raw
Test Matrix D2
Posteriorgrams 2 Distance Detection
Matrix D Score
Test
Utterance Query
Posteriorgrams N DTW DETECT by DTW
Tokenizer N distance
Test Matrix DN
Posteriorgrams N
Figure: PTDTW Framework
Parallel tokenizers followed by DTW detection (PTDTW).
Modified from the posteriorgram-based template matching
approach.
Key idea: Combining DTW distance matrices.
6. Overview System Description System performance Conclusion Acknowledgement
Unsupervised tokenizers
MFCC-GMM tokenizer [Zhang and Glass, 2009]
Unsupervised training from the DEV data without transcription.
1024 Gaussian components.
39-dim MFCC + MVN + VTLN
MFCC-ASM tokenizer [Lee et al., 1988, Wang et al., 2012]
Acoustic segment model, also named as self-organized unit
(SOU) [Siu et al., 2010].
Unsupervised training from the DEV data without transcription.
256 ASM units. Each unit has 3 state, with 16 gaussian
components for each state.
39-dim MFCC + MVN + VTLN
7. Overview System Description System performance Conclusion Acknowledgement
Phoneme recognizers
Czech, Hungarian, Russian phoneme recognizers
developed by BUT [Schwarz, 2009].
trained from SpeechDat-E corpora.
Mandarin phoneme recognizer
179 tonal phonemes.
About 15-hour training data from CallHome corpus and
CallFriend corpus.
English phoneme recognizer
40 phonemes.
About 15-hour training data from Fisher corpus and Swichboard
Cellular corpus.
8. Overview System Description System performance Conclusion Acknowledgement
Phoneme recognizers
Input Phoneme Taking PCA Gaussian
GMM
Data Recognizers Logarithm Transform Posteriorgrams
Figure: Tandem Structure
256 Gaussian components trained on the DEV data.
Using tandem structure, we have 5 tokenizers:
CZ-GMM, HU-GMM, RU-GMM, MA-GMM and EN-GMM.
9. Overview System Description System performance Conclusion Acknowledgement
DTW detection
DTW detection is performed with a sliding window.
Find the path minimizing the normalized distance:
K
ˆ 1 d(i(k), j(k))wk
d= min
K,i(k),j(k) Z(w)
where d(i(k), j(k)) is set to the inner-product distance, wk = 1,
and Z(w) = K.
Additional constraint: |i(k) − j(k)| ≤ R.
Due to the large variation of the query length, R is not set to a
fixed number, but in proportional to the query length I:
1
R = α × I. (α = 3 in our systems).
10. Overview System Description System performance Conclusion Acknowledgement
Pseudo-relevance Feedback and Score Normalization
Pseudo-revelance Feedback for each query:
1) The top H hits from all the test utterances were selected as the
relevance examples. Selection criterion included: a) H ≤ 3; b)
raw detection score should be larger than a pre-set threshold.
ˆ ˆ
2) The relevance examples were used to score the top H (H = 2
for this task) hits from each test utterance.
3) The scores obtained by the relevance examples were linearly
fused with the scores of the original query examples.
Score normalization for each query:
ˆq,t = (sq,t − µq )/δq
s
sq,t is the score of the qth query on the tth hit region.
2
µq and δq are the mean and variance of the scores for the qth
query estimated from the development data.
11. Overview System Description System performance Conclusion Acknowledgement
System Configuration and Performance
Table: System Configurations and ATWV performances.
System No. 1 2 3 4 5
√ √ √ √
MFCC-GMM
√ √ √ √
MFCC-ASM
√ √ √
PHNREC-GMM1
√ √
PRF
√ √ √ √ √
Score Normalization
devQ - devC 0.68 0.63 0.73 0.78 0.74
devQ - evlC 0.60 0.55 0.70 0.75 0.70
evlQ - devC 0.68 0.65 0.73 0.77 0.75
evlQ - evlC 0.64 0.59 0.72 0.74 0.74
System 1 and 2 belong to the require run condition.
System 3, 4 and 5 belong to the general run condition.
The best performance (system 4) is achieved when all the tokenizers, PRF and
Score normalization are used.
1
PHNREC-GMM denotes the combination of the five used tandem tokenizers: CZ-GMM,
HU-GMM, RU-GMM, MA-GMM, and EN-GMM.
12. Overview System Description System performance Conclusion Acknowledgement
System Configuration and Performance
Table: System Configurations and ATWV performances.
System No. 1 2 3 4 5
√ √ √ √
MFCC-GMM
√ √ √ √
MFCC-ASM
√ √ √
PHNREC-GMM
√ √
PRF
√ √ √ √ √
Score Normalization
devQ - devC 0.68 0.63 0.73 0.78 0.74
devQ - evlC 0.60 0.55 0.70 0.75 0.70
evlQ - devC 0.68 0.65 0.73 0.77 0.75
evlQ - evlC 0.64 0.59 0.72 0.74 0.74
Supervised tokenizers perform better than the unsupervised tokenizers.
Training resources for unsupervised tokenizers are limited in this task, but not
limited for supervised tokenizers.
The PTDTW framework provides a flexible way to combine all these resources.
13. Overview System Description System performance Conclusion Acknowledgement
System Configuration and Performance
Table: System Configurations and ATWV performances.
System No. 1 2 3 4 5
√ √ √ √
MFCC-GMM
√ √ √ √
MFCC-ASM
√ √ √
PHNREC-GMM
√ √
PRF
√ √ √ √ √
Score Normalization
devQ - devC 0.68 0.63 0.73 0.78 0.74
devQ - evlC 0.60 0.55 0.70 0.75 0.70
evlQ - devC 0.68 0.65 0.73 0.77 0.75
evlQ - evlC 0.64 0.59 0.72 0.74 0.74
Combination of supervised tokenizers and unsupervised tokenizers leads to
consistent improvement.
Pseudo-relevance Feedback provides consistent improvement.
14. Overview System Description System performance Conclusion Acknowledgement
Conclusion
A PTDTW framework was proposed for the query-by-example
STD task in this evaluation.
Supervised tokenizers performed better than unsupervised
tokenizers for this task. The combination of supervised and
unsupervised tokenizers provided consistent gain.
Pseudo-relevance feedback and score normalization were used.
15. Overview System Description System performance Conclusion Acknowledgement
Acknowledgement
Thank Cheung-Chi Leung from IIR for helpful discussions.
Thank the organizers for organizing this evaluation.
Thank BUT for sharing the phoneme recognizers and scripts.
This research is partially supported by the General Research
Funds (Ref: 414010 and 413811) from the Hong Kong Research
Grants Council.
16. Overview System Description System performance Conclusion Acknowledgement
Thank you!
17. Overview System Description System performance Conclusion Acknowledgement
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