International Conference on Speech Recognition using Machine Learning

ICSRML

26th May – 27th May 2027 Tongi, Bangladesh

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Registration Summary

Conference ICSRML

Date 26th May – 27th May 2027

Location Tongi, Bangladesh

Participation Type Listener

Organizer Science Leagues

Registration Mode Standard / Physical

Registration Fee USD 0.00

Bank Convenience Charges (5.8%)i USD 0.00

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Total Payable USD 0.00

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Conference Session Tracks

Aligned with UN Sustainable Development Goals

The conference's session tracks effectively support the following SDGs.

01 Advancements in Deep Learning for Speech Recognition +

This track focuses on the latest developments in deep learning architectures and their applications in speech recognition. Researchers are invited to present innovative approaches that enhance the accuracy and efficiency of speech-to-text systems.

SDG 4 SDG 9

02 Feature Extraction Techniques in Audio Processing +

This session will explore novel feature extraction methods that improve the performance of speech recognition systems. Contributions should highlight the impact of these techniques on various audio processing tasks.

SDG 9

03 Neural Networks for Acoustic Modeling +

This track aims to discuss the role of neural networks in acoustic modeling for speech recognition. Papers should address advancements in model architectures and their effectiveness in capturing acoustic variations.

SDG 4 SDG 9

04 Language Modeling in Speech Recognition Systems +

This session will cover recent innovations in language modeling techniques that enhance speech recognition accuracy. Submissions should focus on statistical and neural approaches to language modeling.

SDG 4 SDG 9

05 Real-Time Recognition and Processing +

This track emphasizes the challenges and solutions in achieving real-time speech recognition. Researchers are encouraged to present systems that balance speed and accuracy in dynamic environments.

SDG 9

06 Natural Language Processing for Speech Applications +

This session will investigate the integration of natural language processing techniques within speech recognition frameworks. Papers should explore how NLP enhances understanding and context in spoken language.

SDG 4 SDG 10

07 Supervised vs. Unsupervised Learning in Speech Recognition +

This track will compare the effectiveness of supervised and unsupervised learning methodologies in speech recognition tasks. Contributions should provide insights into their respective advantages and limitations.

SDG 4 SDG 9

08 Reinforcement Learning in Voice Analytics +

This session will delve into the application of reinforcement learning techniques in voice analytics and recognition. Researchers are invited to present novel frameworks that leverage feedback mechanisms for improved performance.

SDG 9

09 Predictive Modeling in Speech Recognition +

This track focuses on the use of predictive modeling techniques to enhance speech recognition systems. Papers should discuss methodologies that anticipate user behavior and improve recognition outcomes.

SDG 4 SDG 9

10 Speaker Recognition and Anomaly Detection +

This session will explore advancements in speaker recognition technologies and their applications in anomaly detection. Contributions should highlight innovative approaches to identifying and verifying speakers in various contexts.

SDG 16

11 Adaptive Learning Systems for Speech Recognition +

This track will examine adaptive learning systems that evolve based on user interactions in speech recognition applications. Researchers are encouraged to present systems that demonstrate improved personalization and accuracy over time.

SDG 4 SDG 9