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Flex Conference (Physical / Digital)

International Conference on Speech Recognition using Machine Learning - (ICSRML-26)

26th - 27th September 2026 , Kyrenia - Cyprus

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Call For Papers

The (ICSRML-26) emphasizes interdisciplinary collaboration by bringing together experts from diverse fields. It encourages research that integrates multiple perspectives to address complex global challenges.

Key areas such as Machine Learning are explored to promote cross-domain knowledge exchange and collaborative innovation.

Authors are invited to submit papers addressing, but not limited to, the following areas:

  • Speech recognition advancements using ML
  • Natural language understanding in speech systems
  • Voice biometrics and security applications
  • Speech synthesis techniques with machine learning
  • Real-time speech recognition challenges
  • Machine learning for emotion recognition in speech
  • Applications of speech recognition in healthcare
  • Speech recognition for assistive technologies
  • Multilingual speech recognition systems
  • Deep learning for acoustic modeling
  • Speech recognition in noisy environments
  • Integration of NLP and speech recognition
  • Speech recognition for customer service automation
  • Ethics in speech recognition technologies
  • Machine learning for speaker identification
  • Speech recognition in smart devices
  • Challenges in deploying speech recognition systems
  • Future trends in speech recognition research
  • Data privacy in speech recognition applications
  • Machine learning for transcription services

Assessment

All submissions will undergo peer review to ensure quality and interdisciplinary relevance. Accepted papers will be presented and considered for publication in journals and conference proceedings.

Registration

Registering for the conference provides access to keynote sessions, technical presentations, and networking opportunities with global experts.

Publication

Publishing through the conference enhances the visibility of your research and connects your work with a broader academic audience.