| Group |
2023-27 |
Status |
completed |
| Title |
Real-time Language Translation Device |
| Supervisor |
J. Cai |
| Description |
We propose to develop a portable Language Translation Device that can accurately and efficiently translate spoken language in real-time. The device will cater to individuals in multilingual environments, travelers, and professionals who require quick and accurate translations for effective communication.
Deliverables:
•
Functional Language Translation Device prototype.
•
Software codebase for speech recognition and translation.
•
User manuals and documentation.
The device features a sleek and ergonomic design, making it easy to hold and operate with one hand. It is lightweight and portable, making it ideal for travelers, business professionals, and individuals in multilingual environments. The device employs advanced speech recognition technology to convert spoken words into text and/or speech with high accuracy. Users can experience real-time translation of conversations, enabling effective and natural communication in diverse language settings. Incoming audio signals are preprocessed to remove noise and enhance the quality of the audio data. This includes noise reduction techniques such as spectral subtraction and adaptive filtering.
The Language Translation Device is suitable for a wide range of use cases, including:
Travel: Facilitating communication with locals and navigating foreign destinations.
Business Meetings: Enabling effective communication in international business settings.
Multilingual Environments: Breaking down language barriers in diverse communities.
Education: Supporting language learning and cross-cultural exchange.
Accessibility: Assisting individuals with hearing impairments or language difficulties. |
| Student Requirement |
Programming Skills:
Proficiency in programming languages such as Python and C++ is essential for software development and microcontroller programming. (COEN 346 and COEN 352)
Machine Learning and Natural Language Processing (NLP):
Understanding of machine learning concepts, particularly in the context of speech recognition and machine translation, is required. (COMP 472 and COEN 320)
Signal Processing:
Knowledge of signal processing techniques, especially as they relate to audio and speech, is crucial for speech recognition and noise cancellation. (Elec 242 and ELEC 342)
User Interface (UI) Design:
Familiarity with UI design principles and tools is beneficial for creating an intuitive user interface. (Coen 390)
Software Development:
Proficiency in software development practices, including application development for mobile or desktop platforms (e.g., Android, iOS, Windows, macOS), is required.
Knowledge of cross-platform development frameworks (e.g., React Native, Flutter) can be beneficial. (Coen 390)
Software Methodology:
Familiarity with software development methodologies, particularly Agile methodologies (e.g., Scrum, Kanban), is necessary for project organization and iterative development. (
Proficiency in software development practices, including version control (e.g., Git) and software testing, is expected. |
| Tools |
Software:
•
Integrated Development Environment (IDE) for programming the microcontroller or processor.
•
Speech recognition libraries or APIs.
•
Machine translation libraries or APIs.
•
User interface design tools for designing the device interface.
Test Equipment:
•
Audio analyzers for testing microphone and speaker performance.
•
Multimeter for electrical measurements on the hardware components.
•
Noise cancellation testing equipment to ensure accurate speech recognition in noisy environments.
Hardware:
•
Microphones and speakers with noise cancellation features.
•
Microcontroller or processor suitable for real-time speech recognition and translation. (Raspberry pi)
•
Battery and power management components for extended usage.
•
Display and interface components for user interaction.
•
Enclosure and housing materials for the physical device. |
| Number of Students |
5-6 |
| Students |
M. Younes, A. Bouras, S. Farhat, C. Elias, C. Costa, V. Voznitsa |
| Comments: |
|
| Links: |
|