Audio/signal processing Demos for GAP Processors
Greenwaves Technologies is a 5-year-old fabless semiconductor startup established in Grenoble, France. Our first product GAP8 is the world’s first IoT Application Processor armed with 8+1 RISC-V based cores and a high performance HW convolution engine. It is a simple yet very sophisticated unique processor architecture, which delivers an energy efficiency that is 20x better than the state-of-the-art, opening a large range of battery powered applications. Examples of applications are people counting, keyword spotting, combined with beamforming, object recognition, face detection and vibration analysis. GAP8 is especially effective on machine learning inference algorithms (CNN, SVM, Bayesian, Boosting, Cepstral analysis). Yet, GAP8 is by and large programmed just like a regular MCU.
Our technology is very much ahead of the state-of-art, and our chip is just about to prove its revolutionary potential on a wide open global market. For a team, it is a very motivating challenge that each of us could be part of in proportion to one’s own enthusiasm at work. As a growing and highly multicultural team with sharp personalities, Greenwaves Technologies is very proud of its specific collaborative management style. The company is and will be what each of us make of it, as we experience every day, and we are looking for talented, enthusiastic, curious and committed people, who will be ready to bring their energy and skills for a significant contribution to the success of the company’s project.
This internship is aimed to explorer audio based machine learning and deep learning algorithms for the following one (TBD) of the following use-cases:
- Abnormal sound detection (Sound classification)
- Speech enhancement
- Acoustic scene understanding
- Natural Language understanding
The aim of this internship is to review state of the art and test it with a sample dataset, following these results to develop a solution suitable for gap processors aiming to demonstrate the feasibility on windows/linux pc and optionally port/test the solution on GAP processors.
- Good knowledge of Python and C/C++ programming
- Good Knowledge of machine learning techniques and frameworks such as Tensorflow/Pytorch
- Good Knowledge of audio processing
- Software debug techniques
- Good level of spoken and written English;
- Strong team spirit and communication abilities, in a multisite environment;
- Ability to work autonomously and proactively on assigned tasks.
- Knowledge of parallel embedded architectures and DSP processors;
- Familiarity with versioning/revision control systems (e.g. git).
- Engineer or Master’s degree student in Computer Engineering;
- Course on audio signal processing